middle east current psychiatrypsychiatry-research-eg.com/texts/current-psychiatry-v18n... ·...

Editorial boardEditor in Chief

Farouk Lotaief

Chairman of the Board

Ahmed Okasha

Honorary Editor

Mahmoud S. AbdelgawadMoustafa KamelMounir Fawzi

Assistant to Editor in Chief

Tarek AsaadTarek OkashaYasser A. Elsayed

Associate Editor

Mohamed Ghanem

International Advisory Board:

Tarek Abdel-Gawad (Egypt)Ahmed Abdel-Latief (Egypt)Abdullah Abdelrahman (Sudan)Mohamed Abouzied (Egypt)Tsuyoshi Akiyama (Japan)Abdel Moniem Ashour (Egypt)Zienab Bishry (Egypt)Haroon R. Chaudhry (Pakistan)Safia Effat (Egypt)Abdou El-Dod (Egypt)Mohamed El-Fiky (Egypt)Tarek El-Habib (Saudi Arabia)Suzan El-Kholi (Egypt)Tarek El-Maadawy (Bahrain)Naglaa El-Mahalawy (Egypt)Gihan El-Nahas (Egypt)Ali El-Roey (Libya)Heba Essawy (Egypt)Wolfgang Gabel (Germany)Hamid Ghodse (UK)Oye Gureje (Nigeria)

Amany Haroon (Egypt)Helen Herrman (Australia)Afzal Javed (UK)Eli Karam (Lebanon)Siegfried Kasper (Austria)Levent Kuey (Turkey)Juan Lopez-Ibor (Spain)Felice Lee Mac (China)Mario Maj (Italy)Mona Mansour (Egypt)Jari Mari (Brazil)Driss Moussaoui (Morocco)Nahla Nagy (Egypt)Abdel Naser Omar (Egypt)Ossama Osman (UAE)Hisham Ramy (Egypt)Richard Rawson (USA)Pedro Ruiz (USA)Ahmed Saad (Egypt)Victor Samy (Egypt)Waleed Sarhan (Jordan)Norman Sartorius (Switzerland)Maha Sayed (Egypt)Christopher Sazbo (China)Adel El Sheshaie (Egypt)Constantine Soldatos (Greece)Alaa Soliman (Egypt)Costas Stefanis (Greece)Peter Tyrer (UK)

Editorial Manager:

Aida Sief El DawlaGhada El KholyHisham Sadek

Scientific Editorial Manger:

Dina IbrahimHussien ElkholyMenan Rabie

General Secretary:

Neveen Farouk

For subscriptions to the printed journal, please contact: Neveen Farouk, General Secretary, MECPsych official journal of OkashaInstitute of Psychiatry, Faculty of Medicine, Ain Shams University. Tel. & Fax. 02 26824738; Mobile: 0106609575.

Advertisements, statements or opinions expressed in Middle East Current Psychiatry reflect the views of the advertiser or author(s)and are not the opinion of Lippincott Williams & Wilkins or the Editorial Board unless so stated. Readers are advised that newmethods and techniques described involving drug usage should be followed only in conjunction with drug manufacturer’s ownpublished literature.

MIDDLE EAST CURRENT PSYCHIATRY

Vol 18 No 4 October 2011

Table of contents

Editorial

185 COPE membership for MECPsych: a message behind the news

Mounir Fawzi

Review article

190 The dilemma in the concept and the management of bipolar disorder

Ahmed Okasha

Original articles

195 Diagnosis of Alzheimer’s disease: possible role of functional imaging technique

Mohamed Ezzat El-Hadidy and Salwa Mohamed Etiaba

203 Cognitive functions after hemorrhagic stroke: follow-up study

Hala Ahmed El-Boraie, Mohamed Abd El-Salam Mohamed, Mostafa Amr and Salwa Tobar

211 Characteristics of substance dependence in adolescents with and without a history of trauma

Hosam El-Sawy and Mohamed Abd Elhay

217 Duration of untreated psychosis in two Arab samples from Egypt and Saudi Arabia: Clinical and sociocultural correlates

Mohab M. Fawzi, Hany M. El-Amin and Mounir H. Fawzi

226 Shyness and sociability in a sample of Egyptian patients with schizophrenia and its relation to resting frontal EEG

Hoda Abdou Hussein, Heba Fathy, Sherine Mohamed Abdel Mawla, Fadia Zyada and Reem A. El Hadidy

231 Prevalence and risk factors of unexplained somatic symptoms in school-aged children of Sharkia Governorate

Nagy M. Fawzy, Haitham M. Hashim and Hadeel M.A. Rahman

237 Psychological manifestations in adolescents with thalassemia

Hani Hamed, Osama Ezzat and Tamer Hifnawy

245 Central auditory processing in attention deficit hyperactivity disorder: an Egyptian Study

Saffeya Effat, Somaya Tawfik, Hanan Hussein, Hanan Azzam and Safaa El Eraky



Instructions for Authors

Note: These instructions comply with those formulated by the International Committee of Medical Journal Editors (ICMJE). Forfurther details, authors should consult the following article: International Committee of Medical Journal Editors. ‘‘UniformRequirements for Manuscripts Submitted to Biomedical Journals’’ New Engl J Med 1997, 336:309–315. The complete documentappears at www.icmje.org.

Scope

Middle East Current Psychiatry (MECPsych) is one of the Middle East’s leading psychiatric journals. It covers all branches of thesubject, with particular emphasis on the clinical aspects of each topic. MECPsych is committed to keeping the field of psychiatry inthe Middle East updated and relevant by publishing the latest advances in the diagnosis and treatment of mental illness. MECPsychpublishes high-quality, scientific articles in English, representing clinical and experimental work in psychiatry. The journal acts as aninternational forum for the dissemination of information advancing the science and practice of psychiatry, MECPsych encouragesarticles in compliance with the Madrid and Helsinki Declarations.

Original articles are welcomed, especially those that bring new knowledge or extend the present understanding of mental disorders.Equal priority is given to review articles. All manuscripts published have been assessed by at least two experienced internationalreferees.

The ultimate responsibility for any decision lies with the Editor-in-Chief, to whom any appeals against rejection should be addressed.

Covering letter

A cover letter should accompany your submission. A standard letter is available on the journal’s submission sitewww.editorialmanager.com/mecpsych, or you can submit your own version. Please use the letter to explain why your manuscriptshould be published in the journal and to elaborate on any issues relating to our editorial policies detailed in these instructions.

Redundant or duplicate publication

We ask you to confirm that your paper has not been published in its current form or a substantially similar form (in print orelectronically, including on a web site), that it has not been accepted for publication elsewhere, and that it is not under considerationby another publication. The ICMJE has provided details of what is and what is not duplicate or redundant publication. If you are indoubt (particularly in the case of material that you have posted on a web site), we ask you to proceed with your submission but toinclude a copy of the relevant previously published work or work under consideration by other journals. In your covering letter to theeditors, draw attention to any published work that concerns the same patients or subjects as the present paper.

Conflicts of interest

MECPsych requires authors to state all possible conflicts of interest, including financial and other relationships on a separate line inthe Acknowledgements section of the paper. If you are sure that there is no conflict of interest, please state so. The ICMJE providesfurther information on conflicts of interest. Remember that sources of funding should also be acknowledged in your paper on aseparate line (see paragraph: Acknowledgements).

Permissions to reproduce previously published material

MECPsych requires you to send us copies of permission to reproduce material (such as illustrations) from the copyright holder ofthe previously published material. Articles cannot be published without these permissions.

Patient consent forms

The protection of a patient’s right to privacy is essential. Please send copies of patients’ consent forms on which patients or othersubjects of your experiments clearly grant permission for the publication of photographs or other material that might identify them. Ifthe consent form for your research did not specifically include this, please obtain it or remove the identifying material. A statement tothe effect that such consent had been obtained should be included in the ‘Methods’ section of your paper.

Ethics committee approval

Submission of a manuscript to MECPsych implies that all authors have read and agreed to its content and that any experimentalresearch that is reported in the manuscript has been performed with the approval of an appropriate ethics committee. Researchcarried out on humans must be in compliance with the Madrid and Helsink Declarations. A statement to this effect must appear inthe Methods section, including the name of the body which gave approval. Informed consent must also be documented. Similarly, forexperiments involving animals you must state the care of animal and licensing guidelines under which the study was performed. If



ethics clearance was not necessary, or if there was any deviation from these standard ethical requests, please state why it was notrequired. Please note that the editors may ask you to provide evidence of ethical approval. If you have approval from a National DrugAgency (or similar) please state this and provide details, this can be particularly useful when discussing the use of unlicensed drugs.Manuscripts may be rejected if the editorial office considers that the research has not been carried out within an ethical framework.

Authorship

We ask that all authors sign the covering letter. We ask all authors to confirm that they have read and approved the paper. Second,we ask all authors to confirm that they have met the criteria for authorship as established by the ICMJE, believe that the paperrepresents honest work, and are able to verify the validity of the results reported.

All persons designated as authors should qualify for authorship and all those who qualify should be listed. Each author should haveparticipated sufficiently in the work to take public responsibility for appropriate portions of the content. One or more authors shouldtake responsibility for the integrity of the work as a whole, from inception to published article. Authorship credit should be based onlyon 1) substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data; 2) drafting thearticle or revising it critically for important intellectual content; 3) final approval of the version to be published. Conditions 1, 2 and 3must all be met. Acquisition of funding, the collection of data or general supervision of the research group, by themselves, do notjustify authorship. All others who contributed to the work who are not authors should be named in the Acknowledgements section.

Copyright assignment

Papers are accepted for publication on the understanding that exclusive copyright in the paper is assigned to the Publisher. Authorsare asked to sign a copyright assignment form at the revision stage and to submit it with their revised manuscript. Without thesigned copyright form, the manuscript cannot be published. Authors may use material from their paper in other works published bythem.

Submissions

Manuscripts must be submitted by one of the authors and should not be submitted by anyone on their behalf. The submitting authortakes responsibility for the article during submission and peer review. All manuscripts and materials must be submitted through theweb-based tracking system at www.editorialmanager.com/mecpsych. A covering letter should be included in the submission as a’supporting document’. The site contains instructions and advice on how to use the system. Authors should NOT in addition thenpost a hard copy submission to the editorial office, unless you are supplying artwork, letters or files that cannot be submittedelectronically, or have been instructed to do so by the editorial office. Include the following where appropriate: subject consentforms; transfer of copyright form; permission to reproduce previously published material.

The manuscript should include the following sections, each starting on a separate page: Title Page, Abstract and Keywords, Text,Conflict of interests, Acknowledgements, References, Tables and Figures, captions, Statistics, and Arabic summary. Two letterabbreviations should be avoided. Longer abbreviations should be defined on their first appearance in the text; those not accepted byinternational bodies should be avoided.

Manuscript

Title Page

The Title Page should carry the full title of the paper (be specific, clear and limit to two lines with no abbreviations) and a short title tobe used as a ‘running head’ (and which should be so identified). Please, include the study design in the title; for instance,‘‘randomized trial’’, or ‘‘systematic review’’. The first name, middle initial and last name of each author and their affiliations shouldappear. Academic degrees should not be stated. If the work is to be attributed to a department or institution, its full name should beincluded. The name and address of the corresponding author and the name and address of the author to whom requests for reprintsshould be made should also appear on the Title Page.

Structured Abstract

The second page should carry an abstract, which will be printed at the beginning of the paper and should not be more than 250words. The abstract should state the background or objective, methods, results, and conclusions, with an emphasis on the newaspects of the study. The abstract should be usable as it stands by abstracting journals. Because of this it should contain somenumerical data (if appropriate), not just statistical statements, and it should not contain abbreviations or references.

Key Words

The abstract should be followed by a list of 3–10 key words or short phrases which will assist the cross-indexing of the article.When possible, the terms used should be from the Medical Subject Headings list of the National Library of Medicine.

Text

The remainder of the text should be divided into sections headed Introduction, Materials and Methods (including ethical andstatistical information), Results, and Discussion (including a conclusion). Other descriptive headings and sub-headings may be usedif appropriate. Contents of the study should be presented as clearly and as concisely as possible.

Conflicts of Interest

You must make reference to any conflicts of interest related to this study. If there are no conflicts of interest, please state: none.

Acknowledgements

The acknowledgements section should contain three distinct statements:

1. Assistance with the study. Acknowledgements should be made only to those who have made a substantial contribution to thestudy. Authors are responsible for obtaining written permission from people acknowledged by name in case readers infer theirendorsement of data and conclusions.

2. Financial support and sponsorship. You must make reference to any funding bodies, or sponsorship of any type. If there are nofinancial support or sponsorship, please state: none.

For example:

Acknowledgements

We would like to thank Dr John A. Smith for his assistance with the study.

This work was supported by the Department of Anaesthesiology, London Hospital, London, UK.

References

Number references consecutively in the order in which they are first mentioned in the text. Identify references in the text, tables andlegends using numerals. References cited only in tables or in legends to figures should be numbered in accordance with thesequence established by the first identification in the text of the particular table or illustration.

Use the Vancouver reference system as adopted by the U.S. National Library of Medicine ensuring that all journal titles conform toIndex Medicus approved abbreviations.

Avoid citing abstracts unless from a MEDLINE or EMBASE indexed journal. Unpublished observations and personalcommunications should not be used as references, although references to written (not verbal) communications may be inserted(in parentheses) in the text. Manuscripts that have been accepted but not yet published (e.g. Epub ahead of print) should beincluded in the list, followed by (in press). Information from manuscripts not yet accepted may be cited only in the text as(unpublished observations). Authors should verify references against the original documents before submitting the article.

Electronic or online references should be cited in the reference list only if the material referenced is a specific article (e.g. a paperpublished in a web-based journal); see below for correct style. Less specific references (e.g. the web pages of societies,organisations and university departments) should not appear in the references, instead the URL should be cited in full in the text.

Authors must confirm that the details of these references are accurate and complete. In the full list of references give the names andinitials of all authors. If there are more than six, cite only the first three names followed by et al. The authors’ names are followed bythe title of the article: the title of the journal (italics) abbreviated according to the style of Index Medicus: the year of publication: thevolume number (in bold): the first and last page numbers in full followed by a full stop. Titles of books should be followed by the townand country of publication, the publisher, the year and inclusive page numbers. See the following examples:

Journal articlesPollard BJ, Bryan A, Bennett D et al. Recovery after oral surgery with halothane, enflurane, isoflurane or propofol anaesthesia. Br JAnaesth 1994; 72: 559–566.

BooksKorttila K. Recovery period and discharge. In: White P, ed. Outpatient Anaesthesia. New York, USA: Churchill Livingstone Inc, 1990:369–395.

Chapter in a book:Pessayre D, Feldmann G, Haouzi D, Fau D, Moreau A, Neumann M. Hepatocyte apoptosis triggered by natural substances(cytokines, other endogenous molecules and foreign toxins). In Cameron RG, Feuer G (editors): Apoptosis and its Modulation byDrugs. Handbook of Experimental Pharmacology. Berlin: Springer-Verlag; 2000, pp. 59–108.

Electronic articles:Margolis PA, Stevens R, Bordley WC, Stuart J. From concept to application: the impact of a community-wide intervention to improvethe delivery of preventive services to children. Pediatrics [online serial] 2001; 108:e42.

http://www.pediatrics.org/cgi/content/full/108/3/e42. [Accessed 20 September 2001].

Tables

References to tables should be made in order of appearance in the text and should be in numerals in parentheses, e.g. (Table 1).Each table should be typed on a separate sheet. Tables should not be submitted as photographs. Each table should have a brief titleas a heading. Vertical rules should not be used. Place explanatory matter in footnotes, not in the heading. Authors are discouragedfrom using abbreviations in tables. If abbreviations are necessary then please explain them in the table’s footnotes. Identify statisticalmeasures of variations, such as standard deviation (SD) and standard error of the mean (SEM).

Be sure that each table is cited in the text. If you use data from another published or unpublished source, obtain permission andacknowledge the source fully.

Statistics

Statitstical methods should be specified explicitly and referenced if they are non-standard. Estimates presented should beaccompanied by indicies of precision (e.g. means accompanied by confidence intervals).

Arabic summary

A short Arabic summary is required at the end of the manuscript in a seperate section.

Units of measurement

Scientific measurements should be given in SI units. Blood pressure, however, may be expressed in mmHg and haemoglobin asg dL

-1.

Abbreviations and symbols

Authors are discouraged from using abbreviations. If an abbreviation is necessary please use only standard abbreviations. Avoidabbreviations in the title and abstract. The full term for which an abbreviation stands should precede its first use in the text unless it isa standard unit of measurement.


Official Journal of the Okasha Institute of Psychiatry, Ain Shams University

WHO Collaborative Center for Trainin and Research

Aims and Scope

MECPsych is one of the Middle East’s leading psychiatric journals. It covers all branches of the subject, with particular emphasis onthe clinical aspects of each topic. MECPsych is committed to keeping the field of psychiatry in the Middle East updated and relevantby publishing the latest advances in the diagnosis and treatment of mental illness. MECPsych publishes high-quality, scientificarticles in English, representing clinical and experimental work in psychiatry. The journal acts as an international forum for thedissemination of information advancing the science and practice of psychiatry MECPsych encourages articles in compliance with theMadrid and Helsinki Declarations.

Original articles are welcomed, especially those that bring new knowledge or extend the present understanding of mental disorders.Equal priority is given to review articles. All manuscripts published have been assessed at least by two experienced internationalreferees.



COPE membership for MECPsych: a message behind the newsMounir Fawzi

Department of Psychiatry, Faculty of Medicine,Zagazig University, Zagazig, Egypt

Correspondence to Mounir Fawzi, FRCPsych,Professor of Psychiatry, Department of Psychiatry,Faculty of Medicine, Zagazig University, Zagazig, EgyptTel:/fax: + 002055 2304560;e-mail: [email protected]

Middle East Curr Psychiatry 18:185–189& 2011 Okasha Institute of Psychiatry, Ain Shams University2090-5408

Good news! In June 2011, along with all Lippincott/

Williams & Wilkins journals, Middle East Current

Psychiatry (MECPsych) became a new member of the

Committee on Publication Ethics (COPE). Thus, I was

spurred to write this Editorial with a number of aims. I

wanted first to congratulate the Editor-in-Chief and all

staff members of the MECPsych on this membership. I

also wanted to briefly introduce COPE to our interested

readers and to try to construe the message behind the

news. Moreover, I saw this as an opportunity to draw the

attention of readers and contributors to some of the main

processes of research ethics that aim to ensure transpar-

ency and integrity of the scientific process that all COPE

members including the most recent one, the MECPsych,

are very concerned about and to finally discuss in brief

the impact of cultural factors on the practice of these

ethics.

It is no wonder that our editorial team should feel proud

because MECPsych is the first in the history of

psychiatric journals in Egypt to obtain the COPE

membership. However, my congratulations should be

extended to all Egyptian psychiatric academics and

clinicians who can see that out of all scientific publica-

tions in the Middle East region, there is at least one

psychiatric journal from Egypt that has earned the

membership of COPE. My wish, however, is to see as

many more as possible, if not all the journals of Egypt and

the Middle East becoming members of highly reputable

organizations concerned with publishing Ethics such

as COPE.

COPE was inaugurated in 1997 as a small self-help group

of medical journal editors in the UK providing a forum for

editors to share problems around difficult ethical cases. It

also took on the role of a pressure group to force the

government to place research misconduct on the national

agenda, and in this, it has been successful (http://www.publicationethics.org/). COPE has continued to flour-

ish. By 2000, COPE had over 90 members. Currently, it

includes more than 6000 members worldwide from all

academic fields. All COPE members are expected to

follow the Code of Conduct for Journal Editors. COPE

takes on the responsibility of investigating complaints

that a member has not followed the Code.

Well, as far as I can see, there is a clear message behind

the news that MECPsych has become a member of

COPE. The message is that articles in this Journal can be

considered trustworthy, that MECPsych is aiming for the

highest ethical standards, striving to follow COPE’s Code

of Conduct, and will take suitable action in cases of

possible scientific misconduct. This is vital because

basically, academic publishing has to be dependent on

trust. Editors trust peer reviewers to provide fair

assessments, authors trust editors to select appropriate

peer reviewers, and readers place their trust in the peer-

review process [1]. Scientists are generally perceived as

well-intentioned seekers of truth and as producers of

knowledge vital to the health and welfare of society, while

fraudsters are seen as just a ‘few bad apples’ [2], and the

public is reassured that fraudulent scientists are ulti-

mately caught and punished. Nevertheless, dark clouds of

distrust and concern are hanging over research. Highly

publicized instances of scientific fraud have led to

increased scrutiny of research ethics. Although this

scrutiny has extended across all branches of medicine, it

has been most extensive on psychiatric research. Perhaps

this is because mental illness is less well understood by

scientists and the general public or perhaps individuals

with mental illness are viewed as more susceptible to

exploitation. In addition, some ethical issues relevant to

psychiatric research have arisen primarily from the risks

posed by some research methodologies. Ethical questions

concerning the recent rapid progress in the acquisition

and application of knowledge and technologies stemming

from the sciences of the mind have led to the

development of a novel eld called ‘neuroethics.’ Ob-

viously, biologically informed psychiatry falls within the

purview of neuroethics. So too does the prescription of

antidepressants, antipsychotics, and other psychopharma-

ceuticals [3]. Some distinction has been attempted

between ethics of neuroscience and neuroscience of

ethics. The ethics of neuroscience deal with ethical

problems arising from advances in neuroimaging and

other new forms of interventions into the brain, whereas

the neuroscience of ethics investigates the neural

mechanisms that may possibly underlie moral concepts

and practices [4]. In any case, sensitivity is required in

the design of psychiatric research [5]. To safeguard the

adoption of ethical principles in research, various forms of

Editorial 185

2090-5408 & 2011 Okasha Institute of Psychiatry, Ain Shams University DOI: 10.1097/01.XME.0000403778.57074.30

national commissions, institutional review boards, re-

search ethics committees, and hospital ethics committees

have been developed. A number of international organi-

zations, such as the World Association of Medical Editors,

the International Committee of Medical Journal Editors

(ICMJE), and of course, COPE have also been estab-

lished. They all cater to one and the same goal: to bring

together different opinions, expectations, forms of

expertise, social interests, and to practice the art of

deliberation and confrontation in a tolerant and demo-

cratic spirit [6]. COPE has issued a number of important

publications. These include a series of ‘owcharts’ to

evaluate and respond to the most common questions of

misconduct, ‘Code of Conduct for Journal Editors,’ to

provide a set of minimum standards to which all COPE

members are expected to adhere, and ‘Best Practice

Guidelines,’ which is an extension of the Code as a gold

standard to which to aspire. The two guidelines were

revised in 2011 and combined into a single document but

in which the mandatory Code of Conduct and the more

aspirational Best Practice Guidelines remained distin-

guishable. Obviously, I cannot go into the details of these

publications here. They can be freely obtained from the

COPE’s website (http://www.publicationethics.org/). This

editorial, however, represents an opportunity to draw

the attention of readers and contributors to some basic

processes of research ethics that aim to ensure transpar-

ency and honesty of the scientific process.

TransparencySources of funding for research or publication should be

totally disclosed.

Conflicts of interest

Editors, authors, and peer reviewers have a responsibility

to disclose interests that might appear to affect their

ability to present or review data objectively. These

include relevant financial, personal, political, intellectual,

or religious interests. Readers will benefit from transpar-

ency, including knowing authors’ and contributors’

affiliations and interests. Editors should strive to maintain

transparent policies and procedures regarding authorship

and disclosure of conflicts of interest.

Informed consent

As the use of human beings as a means to the ends of

others without their knowledge and freely granted per-

mission constitutes exploitation and is therefore unethi-

cal, informed consent is fundamental. People may submit

themselves to possible risk or inconvenience or forego the

certainty of specific treatments to participate in a study

as an expression of their personal autonomy, individual

rights, and humanitarian interest. However, this is only

ethical if the research participants have been fully

informed about the study and have signed the consent

form to enter into the study voluntarily. Thus, informed

consent is not a signed consent [7]. A signed consent is a

documentary evidence of the consent process. To confuse

them with each other may be a violation of the ethical

intent of informed consent, which is an educational

process to generate discussion, in an atmosphere of trust

and respect, between researchers and prospective parti-

cipants to ensure that the decision to participate is made

voluntarily and knowingly. Voluntariness implies that the

consent is obtained willingly without using force, threats,

or coercion. The concept of knowledge means that the

prospective participant is allowed to enquire about the

needed details of the study and is given all of the relevant

information, which must be complete and understand-

able, to make a decision on whether or not to participate.

It is important to note that failure to disclose material

facts when obtaining a patient’s consent for research is

fraud. Consent needs to be in writing. If verbal consent is

used, one has to provide the rationale for doing so, for

example, patient illiteracy or visual impairment, but still,

in this case, a short form must be signed or fingerprinted

by the patient and cosigned by an independent witness to

what was said. Some researchers have advocated the

documentation of the process of informed consent by

audiorecording, videorecording, and photography when

patients cannot read [8]. If the participant is not able to

provide consent, as in some patients with psychiatric

disorders, it should then be obtained from the partici-

pant’s legally acceptable representative, for example,

parent, guardian, or designated other, before involvement

in any research-related activity. However, research has not

supported the assumption that all psychiatric patients by

virtue of their illness are not competent enough to

understand the issues and to provide informed consent.

Indeed, many of these patients are able to provide

informed consent.

Research honestyResearch honesty or integrity is the maintenance of

truthfulness and proper crediting of research sources. It

encompasses a wide range of topics relating to the ethical

conduct of research involving humans and animals.

Animal welfare concerns

It is essential that researchers do everything possible to

promote and ensure the humane care and treatment of

animals used in research. Animals to be used in the

laboratory must be acquired lawfully, properly fed and

sheltered and, under no circumstances, subjected to

unnecessary pain or discomfort.

Human use concerns

The origin of advancing scientific knowledge through

human experimentation using vulnerable groups can be

traced back to ancient history, when Herophilus per-

formed vivisections on prisoners. In recent times, the

principles of conducting human research were first deve-

loped as the ‘Nuremberg code’ in 1947 to try 23 Nazi

physicians and officials as war criminals for conducting

‘studies’ of prisoners. The three basic principles of the

Nuremberg Code (voluntary informed consent, favorable

risk/benefit analysis, and right to withdraw without

repercussions) became the basis for subsequent ethical

186 Middle East Current Psychiatry

codes and research regulations [9,10]. In 1964, the World

Medical Association established the Declaration of

Helsinki, which states that ‘concern for the interests

of the subject must always prevail over the interests of

science and society.’ The Declaration of Helsinki has

since been amended six times in efforts to maintain

relevance to current science. The current (2008) version

is the only official one. For the psychiatric profession, the

Declaration of Hawaii [11] was the first positional

statement concerning ethical questions [12]. This was

updated in 1996 by the Declaration of Madrid, which was

enhanced by the World Psychiatric Association General

Assemblies in Hamburg (Germany) in 1999, in Yokohama

(Japan) in 2002, and in Cairo (Egypt) in 2005. The

Declaration of Madrid includes seven guidelines that

focus on the aims of psychiatry to treat mentally ill

patients, prevent mental illness, promote mental health,

and provide care and reinsertion for patients [13].

AuthorshipThe list of authors should accurately reflect who carried

out the study. However, authorship relates more to the

intellectual rather than to the practical implementation

of the project. According to the ICMJE (http://www.icmje.org), authorship requires the fulfillment of three condi-

tions: (a) substantial contributions to conception and

design, or acquisition of data, or analysis and interpreta-

tion of data; (b) drafting the article or revising it critically

for important intellectual content; and (c) final approval

of the version to be published. All three conditions should

be fulfilled for assigning authorship. Although the ICMJE

criteria are clear, many authors are unaware of them or

prefer to use their own ad-hoc criteria for deciding

authorship [14]. Two forms of ethical problems concern-

ing authorship have been frequently recognized: (a) Gift

(guest or honorary) authorship, that is, inclusion of

authors who did not contribute substantially to the study,

for example, those who provide technical help only,

writing assistance, or the head of the department who

provides only general support. These people are relegated

to the acknowledgments section. Another form of gift

authorship occurs between colleagues and collaborators.

In this case, a name of a colleague is unjustifiably added

to the manuscript in the expectation that the favor will be

returned. In this way, both authors unethically increase

the number of their publications. (b) Ghost authorship,

that is, exclusion of authors who did contribute sig-

nificantly to the study. This usually involves people,

such as postgraduate students, who are too junior to

protest.

Listing individuals’ contributions to the research and

publication process provides greater transparency than

the traditional listing of authors and may discourage

inappropriate authorship practices such as ‘ghost’ authors

and gift authors. A declaration should be made that all

authors meet the journal’s criteria for authorship and that

nobody who meets these criteria has been excluded from

the list. Authors should also declare that they have

acknowledged all significant contributions made to their

publication by individuals who did not meet the journal’s

criteria for authorship. If an authorship dispute or

discrepancy comes to light before publication (for

example, changes to the list of authors are proposed

after submission), editors should take care to explain the

journal’s authorship policy to the corresponding author

and to establish that all authors agree to the change

before proceeding with publication. If an authorship

dispute emerges after publication (for example, some-

body contacts the editor claiming they should have been

an author of a published paper or requesting that their

name be withdrawn from a paper), the editor should

contact the corresponding author and, where possible, the

other authors to establish the veracity of the case. If

authorship policies have been clearly set out and an

explicit authorship declaration(s) has been received

(stating that all authors meet the agreed criteria and

that nobody deserving authorship has been excluded),

then genuine errors are unlikely; however, editors should

consider publishing a correction in the case of such errors.

Has the work been published before?Duplicate publication

This is the publication of an article that is identical or

overlaps substantially with an article already published

elsewhere, with or without acknowledgment. Duplicate

publication is considered misconduct because, aside from

the obvious attempt to inflate one’s own publication

record, duplication (and redundant) publication has the

potential to skew the evidence base (if the same data

were counted more than once, the outcomes of meta-

analysis used to establish the best practice would be

invalid). Guidelines on good publication practice state

that the authors can only submit their manuscript to a

single journal at a time. However, there are some

exceptions to the rule, for example, publication of results

in an abstract form (and as a poster or oral communica-

tion) at a congress. Once a manuscript has been publi-

shed, data should not then be submitted to a congress.

Authors may resubmit the same or a revised version to

another journal only if the first journal makes the decision

not to publish it or it is withdrawn by the author.

Other research misconductsThe most important other forms of research misconduct

include the trio ‘FF&P’: fabrification, falsification, and

plagiarism.

(1) Fabrication: Fabrication of data refers to the invention

or the making up of fictitious data, that is, data are

made up or ‘cooked’ and then presented as research

findings;

(2) Falsification: Falsification is the changing of data or

exclusion of critical data to produce a desired

outcome or to avoid a complicating or an inexplicable

result;

COPE membership for MECPsych Fawzi 187

(3) Plagiarism (from the Latin word plagiarius, meaning

the theft of words as well as slaves): Plagiarism is the

use of someone else’s words, ideas, or results without

appropriate attribution. It is a form of academic

dishonesty and can be a criminal offense.

However, not all research misconduct allegations are true.

A surprising number of plagiarism allegations turn out to

be misunderstandings of exactly what constitutes plagiar-

ism or proper citation procedure. On the basis of

contemporary guidelines, I further discussed research

misconduct elsewhere [15]. It is true that there are

certain universal concepts, but it should be noted that

the standards or the requirements of publishing, as other

human endeavors, undergo a natural evolution, and

standards acceptable even 10–20 years ago are no longer

acceptable [16]. Moreover, these guidelines are western-

oriented and although the problem of ensuring ethical

practices in research on humans appears to be universal,

the influence of traditional and hierarchical social norms

of physician–patient relationships, in the developing

world, adds yet another dimension to the difficulties in

ensuring that research is conducted in an ethical manner.

Some observers in the Western world noted that many of

those found guilty of scientific misconduct were from

foreign cultures. Applying theories from sociological

criminology, Davis [17] posited that the culture brought

to the West by some researchers may be at odds with the

norms of academic science and may emphasize ends more

than means. Nonetheless, in the developing world, the

influence of traditional and hierarchical social norms of

physician–patient relationships adds yet another dimen-

sion to the difficulties in ensuring that research is

conducted in an ethical manner [18].

In some cultures, it is still customary for physicians to

withhold certain information from patients. Clinicians

may provide diagnoses (as well as prognoses) of some

serious conditions to family members, but not to the

patients. As a result, the patient’s consent to certain

procedures, if sought, may not be fully informed. Hence,

valid informed consent (for either treatment or research

participation) can be difficult. In some cultural contexts,

the appropriateness of requiring information to be

disclosed about the use of a placebo and the randomiza-

tion of participants may also be queried. Some have

recommended, therefore, that researchers should develop

culturally appropriate ways to disclose information that is

necessary for adherence to the ethical standard of

informed consent, with particular attention to disclosures

relating to diagnosis and risk, research design, and

possible posttrial benefits. Researchers have to explain

to the Ethics Review Committee(s) their plan for

disclosing such information to participants [19]. More-

over, in some cultures where people may not understand

or accept scientific explanations of health and disease,

the challenge of obtaining informed consent can be

daunting. Yet, researchers can devise innovative methods

to surmount these obstacles and to ensure that potential

participants do, in fact, comprehend the information

contained in the consent process. In some countries,

community education is performed before obtaining

individual consent.

We should also bear in mind that in the Eastern

Mediterranean Region, the foundations of ethical princi-

ples can be found within the three major religions of

Judaism, Christianity, and Islam. In Egypt, the numerous

ethical issues that are emerging as result of the

technological advances tend to be addressed in accor-

dance with Islamic principles [20]. Acknowledging the

role of culture in the adherence to research ethics,

however, underscores the importance of education and

training of both researchers and administrators in the

responsible conduct of research and cultural diver-

sity [17].

Culture also has an impact on the definitions of scientific

misconduct, which differ from country to country and

from one institution or government agency to an-

other [21]. However, the increasing globalization of

scientific research calls for an international agreement

on the definition of scientific misconduct. Universal

spiritual and moral principles on which ethical standards

are generally based indicate that it is possible to reach

international agreement on the ethical principles under-

lying good scientific practice without creating unneces-

sary obstacles to research. This is very much needed for

research, especially in developing countries. Ethical stan-

dards promote high-quality research. It is crucial, there-

fore, to draw attention to and follow such standards [16].

To conclude, I think one can see that getting a

membership of COPE is a message signifying that this

Journal will be taking part in the development of local

and international research ethical standards. So, once

more, congratulations!!

AcknowledgementsConflicts of interestThere is no conflict of interest to declare.

References1 Graf C, Wager E, Bowman A, Fiack S, Scott Lichter D, Robinson A. Best

practice guidelines on publication ethics: a publisher’s perspective. Int J ClinPract Suppl 2007; 152:1–26.

2 Lafollette MC. The evolution of the ‘scientific misconduct’ issue: an historicaloverview. Proc Soc Exp Biol Med 2000; 224:211–215.

3 Levy N, Clarke S. Neuroethics and psychiatry. Curr Opin Psychiatry2008; 21:568–571.

4 Roskies A. Neuroethics for the new millennium. Neuron 2002; 35:21–23.

5 DuVal G. Ethics in psychiatric research: study design issues. Can J Psy-chiatry 2004; 49:55–59.

6 Lolas F. Ethics in psychiatry: a framework. World Psychiatry 2006; 5:185–187.

7 Jones JW, McCullough LB, Richman BW. Informed consent: it’s not justsigning a form. Thorac Surg Clin 2005; 15:451–460.

8 Benitez O, Devaux D, Dausset J. Audiovisual documentation of oral consent:a new method of informed consent for illiterate populations. Lancet2002; 359:1406–1407.

9 Orticio LP. Protecting human subjects in research. Insight J Am Soc OphthalRegister Nurses 2009; 34:14–16.

10 Rice TW. The historical, ethical and legal background of human-subjectsresearch. Respir Care 2008; 53:1325–1329.

11 World Psychiatric Association (WPA). The Declaration of Hawaii. Hawaii:WPA General Assembly; 1977.


12 Okasha A. The Declaration of Madrid and its implementation. An update.World Psychiatry 2003; 2:65–67.

13 World Psychiatric Association (WPA). Madrid declaration on ethical stan-dards for psychiatric practice. Hawaii: WPA General Assembly; 1996.

14 Gollogly L, Momen H. Ethical dilemmas in scientific publication: pitfalls andsolutions for editors. Rev Saude Publica 2006; 40 (Spec. Iss.):24–29.

15 Fawzi M. Publish or perish! But avoid scientific misconducts. Egypt JPsychiatry 2010; 30:1–6.

16 Brand RA, Heckman JD, Scott J. Changing ethical standards in scientificpublication. J Bone Joint Surg B 2004; 86:937–938.

17 Davis MS. The role of culture in research misconduct. Account Res2003; 10:189–201.

18 Moazam F. Research and developing countries: hopes and hypes. EastMediterr Health J 2006; 12 (Suppl 1):S30–S36.

19 Crigger BJ. National Bioethics Advisory Commission Report: ethical andpolicy issues in international research. IRB 2001; 23:9–12.

20 Khayat MH. Research ethics: challenges in the Eastern MediterraneanRegion. East Mediterr Health J 2006; 12 (Suppl 1):S13–S20.

21 Mojon Azzi SM, Mojon DS. Scientific misconduct: from salami slicing to datafabrication. Ophthalmic Res 2004; 36:1–3.

COPE membership for MECPsych Fawzi 189

The dilemma in the concept and the management of

bipolar disorderAhmed Okasha

WHO Collaborating Center for Research and Trainingin Mental Health, Okasha Institute of Psychiatry,Ain Shams University, Cairo, Egypt

Correspondence to Ahmed Okasha, MD, PhD, FRCP,FRC, Psych, FACP (Hon) Director, WHO CollaboratingCenter for Research and Training in Mental HealthOkasha Institute of Psychiatry, Ain Shams University,Cairo, EgyptTel: +202 29200900/1/2/3/4;fax: +202 29200907/8;e-mail: [email protected];

[email protected]

Received 25 July 2011Accepted 1 August 2011

Middle East Current Psychiatry

2011, 18:190–194

Bipolar disorder is underdiagnosed, misdiagnosed and undertreated. The emphasis

now is on the bipolar spectrum and its management is under continuous revision,

for example, the controversial use of antidepressants. The recent change in the

conceptualization of bipolar disorder has changed the lifetime prevalence, the difficulty

in diagnosis, the syndromal and functional outcome. The bipolar spectrum

encompasses many psychiatric disorders that requires a change in its diagnosis and

management. There has been a shift in pharmacological and psychotherapeutic

management in bipolar disorder. The dilemma in management will be discussed with a

personal experience of approximately 50 years in psychiatry. Cultural and economical

sensitivity will be taken into consideration. A brief account will be presented for the

management and maintenance treatment of mixed, rapid cycler and psychotic bipolar

disorder, whether psychopharmacological or psychotherapeutic.

Keywords:

bipolar disorder, bipolar spectrum, lithium, mood stabilizers, mixed episode, rapid cyclar


One in four people will suffer from a mental or a

neurological disorder at some point during their lifetime;

450 million people are currently affected by these

disorders, 121 million people suffer from depression, 24

million from schizophrenia, 50 million from epilepsy and

one million people commit suicide every year [1]. There

are many Caveats in International Classifications, mainly

the high rates of comorbidities among patients with these

disorders that may undermine the hypothesis that the

syndromes represent distinct etiologies. A high degree of

short-term diagnostic instability for many disorders is a

challenge; the lack of treatment specificity is the rule

rather than the exception for almost all psychiatric

disorders [2]. The study by Berrettini and Pekkarinen [3]

indicated that three of the putative susceptibility loci

associated with bipolar disorder also contribute to the risk

of schizophrenia. Bipolar disorder is the second highest

cause for years of life lost with a disability among

neuropsychiatric conditions [4]. The reasons for the

underdiagnosis of bipolar disorders are patients’ impaired

insight into mania, failure to involve family members in

the diagnostic process, inadequate understanding by

clinicians of manic symptoms and the fact that increased

energy is representative of more than irritability or

euphoria. Bipolar disorder is a recurrent illness in more

than 90% of patients; functional recovery often lags

behind symptomatic and syndromal recovery. Recurrent

episodes may lead to progressive deterioration in

functioning and the number of episodes may affect the

subsequent treatment response and prognosis. The

mortality and disability in bipolar disorder is high, and

considered the sixth leading cause of disability world-

wide [5]. At least 25% of the patients attempt suicide,

suicide rates ranging between 11 and 19% and 25–50%

suicidal ideation is found in mixed mania.

The recent change in the conceptualization of bipolar

disorder shows that in the past, lifetime prevalence in the

community was low (1–1.6%) whereas at present it is

relatively high (3–6.5%); the diagnosis was easy and

reliable but at present it is rarely so and the outcome was

good and now often poor. In the past, pharmacological

treatment was straightforward and effective; currently, it

is complex and inconstantly effective, and it was believed

that psychotherapies have no role but now several types

are useful [6].

The spectrum of bipolar disorders includesthe following:

(1) ‘Typical’ cases: Manic episodes (with euphoric or

irritable mood or increased energy) and major

depressive episodes;

(2) ‘Atypical’ and complicated cases: With mixed episodes

(either dysphoric mania or agitated depression), with

continuous circular course or rapid cycling, with mood-

incongruent psychotic features, complicated or masked

by alcohol or drug abuse or by anxiety disorders;

(3) ‘Pseudounipolar’ cases: Bipolar disorder II, III and IV

and possibly other forms;

(4) ‘Subthreshold’ cases: Cyclothymic and hyperthymic

forms.

‘Pseudounipolar’ forms indicate bipolar disorder II (major

depressive and hypomanic episodes), bipolar disorder III

(major depressive episodes and antidepressant-associated

hypomania) and bipolar disorder IV (major depressive

episodes superimposed on hyperthymic temperament);

others may include recurrent depression with an abrupt

190 Review article

2090-5408 & 2011 Okasha Institute of Psychiatry, Ain Shams University DOI: 10.1097/01.XME.0000405314.98496.3f

onset and offset, and seasonal depression, even without

discernible hypomanic episodes [5]. Some bipolar dis-

order II features are more prevalent than bipolar disorder

I in the community. It is frequently misdiagnosed as

recurrent major depression (from 27 to 65% of patients

with this diagnosis are reported to be bipolar II disorder),

with a high frequency of interpersonal conflicts, marital

instability and family breakdown. Other conditions that

may be considered for inclusion in the bipolar spectrum

are episodic obsessive–compulsive forms, periodic states

of irritability, acute suicidal crises in the absence of clear-

cut affective symptoms, cyclical neurasthenic or sleep

complaints, severe brief recurrent depressions, impulse-

ridden behaviours in the control of aggression, gambling

and paraphilias. Conditions that may overlap with bipolar

disorder include schizoaffective disorder, borderline

personality disorder, substance use disorders and adult

attention-deficit hyperactivity disorder (ADHD) [5].

Some findings of the Stanley Foundation Bipolar Network

can be stated: the average age of onset of the first

symptoms of bipolar disorder is 19.4 years. The average

age of the first treatment of bipolar disorder is 29.2 years.

The onset of illness is earlier in patients with a family

history of affective illness and in those who experienced

early extreme stressors (i.e. physical or sexual abuse) [7].

The United States Department of Health, Education and

Welfare stated that without adequate treatment, a person

with bipolar disorder from age 25 years can expect to lose

14 years of effective major activity (e.g. work, school,

family role function) and 9 years of life (mainly because of

suicide). With appropriate treatment, 6.5 years of life

expectancy can be regained. Less than one of five

patients with bipolar disorder have intact marital relation-

ships [8]. There are predictors of a less favourable

outcome in bipolar disorder: consistently reported high

number of previous episodes, the presence of mood-

incongruent psychotic features, comorbid substance

abuse, inconsistently reported and rapid cycling. Are

schizophrenia and bipolar disorder phenomenologically

and nosologically clearly separable? New findings from

neurobiological research have made this question as one

of the major issues today. First illness episodes of

schizophrenia and affective disorder show similar mor-

phological brain abnormalities, increased ventricle–brain

ratios and decrease in grey matter in the frontal and

temporal lobe and volume reduction in the hippocampus–

amygdala area. Schizophrenic psychosis and severe

unipolar disorder or bipolar disorder share various

aetiological risk factors. Their onset is marked by a very

similar prodromal core syndrome, which includes func-

tional impairment, and emerges long before the climax of

the first episode. Therapies target current symptom

patterns such as depression, mania, psychosis and the

associated neurotransmitter dysfunctions rather than

specific underlying disease processes [9].

The current disease concepts of schizophrenia, bipolar

disorder and unipolar depression, understood as compris-

ing different aspects of symptom dimensions, will usher

in a farewell to the dichotomous classification of the early

Kraepelin [9], as they overlap in their symptomatology.

Functional disability in bipolar disorder is prevalent. After

6 months of treatment, syndromal recovery is 84%

whereas functional recovery is only 30%, and after 2

years, it is 98 and 38%, respectively [10,11].

Follow-up of bipolar disorders showed that bipolar

disorder subtypes tend to have a chronic course, and

after 20 years of follow-up, 47.5% of BP-I patients

and 54% of BP-II patients were symptomatic. Syndromal

and subsyndromal symptoms fluctuated. Minor subsyndro-

mal manic and depressive symptoms were three times

more common than syndromal ones. Depressive symptoms

dominated the course, wherein the ratio was depression:-

mania = 3 : 1 in BP-I, 30 times more common in BP-II [12].

The goals of therapy in bipolar disorder mania are to

1- Control dangerous symptoms, such as suicide, agitation

and psychosis. 2- Stabilize mood, control mania without

inducing depression. 3- Treating all phases of mania

including depressive, anxious and psychotic elements and

restore premorbid functioning [5].

Mood-stabilizing agents include lithium, anticonvulsants

[carbamazepine (tegretol), oxcarbazepine (trileptal),

valproate (depakine), lamotrigine (lamictal), gabapentin

(neurontin), topiramate (topamax)] benzodiazepines

(clonazepam), conventional antipsychotics (e.g. haloper-

idol), Second generation antipsychotics (e.g. clozapine,

olanzapine, risperidone, quetiapine, aripiprazole, etc.) [5].

The features of an ideal mood stabilizer over time and

across episodes include the following: rapid efficacy for

mania, treatment of psychotic symptoms of mania, broad

efficacy (e.g. mixed, rapid cycling), reduction of depres-

sive symptoms, favourable cognitive effects, long-term

usefulness, well tolerated by patients and easy to use [5].

The efficacy of lithium ranges between 49 and 70% and

the onset of action is approximately 5–21 days, whereas

prophylaxis takes approximately 9 months. Predictors of

response are classic mania, few episodes and bipolar

disorder episode sequence. Lithium may cause neuro-

cognitive, renal, gastrointestinal and endocrinologic side

effects and weight gain. The risk of recurrence is

increased in the months after discontinuation of lithium.

Lithium may help exert an antisuicidal effect on patients

with bipolar disorder [5].

Mixed-state (dysphoric mania) prevalence is approxi-

mately 30%, and it is a distinct entity. It is intermediate

on the spectrum between mania and depression, and is

considered to be a more severe form of bipolar, with

significant morbidity and mortality [5].

The best treatment strategy for bipolar disorder is that which

results in the fewest, mildest or briefest episodes [13].

Clinical suggestions include combination therapy with

the addition of new medication and anticipation of

transitional side effects. The new medication should be

titrated to a therapeutic dose and the response to this

should be awaited before any other alterations can be

made; if the response is positive, ineffective medications

can be weaned off but if the response is partial,

medication should be continued.

The dilemma in the concept and the management of bipolar disorder Okasha 191

There are aspects of overlap in bipolar disorder with other

disorders. Anxiety in bipolar may be present in unipolar

depression and social phobia, and hyperactivity symptoms

may be linked to ADHD and substance abuse. Depressive

symptoms may occur in personality disorder, unipolar

depression, schizophrenia and schizoaffective disorders,

whereas psychotic symptoms can occur in delusional

disorders, schizophrenia and schizoaffective disorders.

Comorbidities are the rule not the exception. Medical

disorders include (pain disorder, diabetes mellitus,

cardiovascular, obesity, migraine) whereas psychiatric

diagnoses include substance abuse, eating disorders,

anxiety disorders, impulse control, ADHD and person-

ality disorder [14]. Bipolar disorder is associated with

numerous comorbidities; comorbid psychiatric disorders

are reported in 31–75% of patients. Comorbid anxiety is

reported in 24–28% of patients. A range of anxiety

disorders, substance and alcohol abuse are highly

prevalent [15,16].

We should be aware of the antipsychotic switching

syndrome ‘Withdrawal triad’ namely: cholinergic rebound

(nausea, vomiting, restlessness, sweating, tremors, etc),

supersensitivity psychosis and withdrawal dyskinesias

(and other motor syndromes). Antipsychotic switching

strategies include either an abrupt switch, which is not

advisable, or taper switch, involving gradual discontinua-

tion of current antipsychotic and immediate start of the

new antipsychotic (AP) or cross taper switch, that is,

taper current AP and gradually start new AP; however,

better switch is we treat with both current and new AP is

gradual start of new AP and taper current AP.

Systematic Treatment Enhancement Program for Bipolar

Disorder, National Institute of Mental Health is a clinical

research programme designed to study treatment effec-

tiveness with both naturalistic and randomly assigned

treatment protocols. All patients received mood stabili-

zers or atypical antipsychotics, and patients who also

received antidepressants were compared with those who

did not receive antidepressants [13]. The study found

that recovery from depression was independent of

whether or not patients received adjunctive antidepres-

sant treatment. These results mirror another recent

publication from Systematic Treatment Enhancement

Program for Bipolar Disorder, which found no advantage

in adding antidepressants to mood stabilizers in the

treatment of bipolar depression without concurrent

manic symptoms and may lead to a risk of causing mania.

These findings are also consistent with a double-blind,

placebo-controlled study of bipolar depression that found

that if lithium was dosed to a serum level of at least

0.8 meq/l, then the addition of an antidepressant

(paroxetine, imipramine) provided no additional benefit

in symptom improvement [17,18].

There is a high rate of misdiagnosis; the most frequent

being unipolar depression of approximately 60%. An

average of 3.5 misdiagnoses and four consultations occur

before an accurate diagnosis is made and 35% of patients

are symptomatic for 10 years or more before a correct

diagnosis is made (Table 1) [19].

Psychotic symptoms in bipolar disorderAt least 58% psychotic symptoms are present, with

auditory hallucinations being 47%, delusions being

53%, catatonia being 23% and Schneiderian first rank

symptoms being 8% [20–23].

High rates of death and suicide in patientswith bipolar disorderIn the United Kingdom, death rates of 18% were reported

for patients with bipolar disorder over a 35-year study

period, and attempted suicide rates varied between 21

and 54%. An Italian study reported that 22% of men and

54% of women with bipolar disorder I had a history of

suicide attempts. In a French study, 40% of patients with

bipolar disorder had attempted suicide at least once.

Vieta et al. [24] found that 38% of patients with bipolar

disorder with a comorbidity had attempted suicide, com-

pared with only 21% of patients without a comorbidity

[24–27].

Approximately 70% of patients with bipolar disorder are

not gainfully employed; only 30% of patients with bipolar

disorder in Germany were employed full time at a level

that was appropriate for their qualifications. In Europe,

Table 1 Food and Drug Administration approved labelling for antipsychotic medications

Antipsychotic SchizophreniaAcute bipolar manic/

mixed episodes Acute bipolar depressionMaintenance treatment

of bipolar disorder I Prevention

Chlorpromazine (largactil) + + – – –Haloperidol (haldol) + – – – –Perphenazine (trilafon) + – – – –Clozapine (leponex) + – – – –Aripiprazole (abilify) + + – + –Olanzapine (zyprexa) + + + (only in Combination with Fluxetine) + –Paliperidone (invega) + – – – –Quetiapine (seroquel) + + + + +Risperidone (risperidone) + + – – –Ziprasidone (zoldox) + + – – –

+ , approved by Food and Drug administration;– , not approved by Food and Drug administration.


34% of patients with bipolar disorder have difficulty

finding a job and 34% have difficulty retaining a job. An

Italian study found that 63–67% of patients with bipolar

disorder were unemployed. A Europe-wide survey re-

vealed that patients with bipolar disorder disease feel

stigmatized and also have difficulties in maintaining

relationships with friends and family and enjoying leisure

activities [28–30].

The impact of bipolar disorder on lifestyle of patients

with bipolar disorder shows interference in: relationships

with family – 54%, relationships with friends – 44%,

relationships with partners – 43%, retaining job – 34%,

finding job – 34%, career prospect – 29%, relationships

with colleagues – 26%, education – 24%. while present

lifestyle difficulties exhibit feeling stigmatized – 55%

carrying out job – 45% relationships with family – 44%

enjoying leisure activities – 41% feeling ridiculed – 39%

relationships with friends–37% expressing own opi-

nion [29].

A survey of European psychiatrists indicated that over

60% of patients with bipolar disorder had to undergo at

least two changes of therapy before stabilization. The

average number of therapy changes before patients were

stabilized was 2.4 [31].

A few developments have led to renewed interest in

psychotherapies for bipolar disorder, especially the lack of

effectiveness of long-term pharmacotherapy under ordin-

ary clinical conditions and the significant role of patients’

poor adherence in reducing the effectiveness of pharma-

cotherapy; however, there is evidence that life stressors

and social support can have an influence on the course of

the disorder and that social, family and occupational

dysfunction is very frequent in patients with bipolar

disorder. Psychotherapeutic techniques that can be used

systematically in patients with bipolar disorder include

cognitive-behavioural techniques, interpersonal and social

rhythm therapies, psychoeducational techniques and

family and couple interventions. The common psy-

chotherapeutic techniques of proven efficacy in bipolar

disorder include providing information on the disorder,

focusing on triggers of episodes, seeing the individual as

part of a group and formulating a patient-specific action

plan [6].

Need for new and effective treatments inbipolar disorderThere is a recognized need for new and effective

treatments in bipolar disorder maintenance. The episodic

and chronic nature of bipolar disorder requires long-term

treatment in all patients, and yet, there is an unmet need

for well tolerated and clinically effective maintenance

therapy with enhanced patient adherence. A substantial

number of patients with bipolar disorder do not respond,

have relapses or cannot tolerate the side effects of

common treatments for bipolar disorder. Treatment

guidelines for bipolar disorder recommend a wide range

of treatments, with no obvious trend in recommendations

across guidelines. This suggests that there is an unmet

need for treatment that is effective across all phases of

bipolar disorder (Tables 2 and 3) [33–37].

Table 2 Food and Drug Administration approved treatments

for bipolar disorder

Phases of bipolar disorders Mania Depression

Acute treatment Lithium (Lithium)a

Valproate (Lamotrigine)a

(carbamazepine)a Olanzapine/fluoxetineOlanzapine (SSRIs)a, c

RisperidoneQuetiapine Quetiapine

Maintenance treatment Lithiumc

Lamotrigined

Quetiapine

aOff label for this indication.bNot recommended as monotherapy (can induce mania and rapidcycling).cPredominantly effective against mania.dPredominantly effective against depression.

Table 3 Food and Drug Administration approved treatments/bipolar disorder

Maintenance Depression

Mania Mixed Mania Depression Bipolar disorder I Bipolar disorder II

Mood stabilizerLithium + – + – – –Divalproex DR + – – – – –Divalproex ER + + – – – –Carbamazepine ER + + – – – –

Atypical antipsychoticsRisperidone + + – – – –Olanzapine + + + – – –Quetiapine + + + + + +Ziprasidone + + – – – –Aripiprazole + + + – – –

OtherLamotrigine – – + + – –Olanzapine/fluoxetine – – – – + –

Physicians’ Desk Reference 2009 [32].+ , approved by Food and Drug administration;– , not approved by Food and Drug administration;DR, Delayed release;ER, Extended release.

The dilemma in the concept and the management of bipolar disorder Okasha 193

SummaryBipolar disorder is a lifelong illness and is associated with a

substantial health, social and economic burden. An

accurate diagnosis of bipolar disorder is essential to initiate

effective treatment and prevent relapse. Evidence sup-

ports a range of treatments for the improvement of manic

and depressive symptoms in bipolar disorder. The ideal

treatment would achieve mood stabilization by effectively

treating mania and depression and preventing relapse

among patients with bipolar disorders I and II and rapid

cyclers. The most successful treatment strategy would

involve a holistic approach that is tailored to the individual

patient inclusive of the following aspects: physical

(symptom control), emotional (become calmer, feel good

about themselves), mental (able to think clearly, make

sense of life and regain control) and social (return to work,

reengage in social activities and family).


References1 Mental Health Resources in the World. Initial results of Project ATLAS. J Adv

Nurs 2001; 36:7–8.

2 Asaad T, Okasha T, Okasha A. Sleep EEG findings in ICD-10 borderlinepersonality disorder in Egypt. J Affect Disord 2002; 71 (1–3):11–18.

3 Berrettini WH, Pekkarinen PH. Molecular genetics of bipolar disorder. AnnMed 1996; 28:191–194.

4 Murray CJL, Lopez AD. The global burden of disease: a comprehensiveassessment of mortality and disability form diseases, injuries and risk factorsin 1990 and projected to 2020. Cambridge: Harvard School of PublicHealth; 1996.

5 Tandon R, Belmaker RH, Gattaz WF, Lopez Ibor JJJ, Okasha A, Singh B, et al.World Psychiatric Association Pharmacopsychiatry Section statementon comparative effectiveness of antipsychotics in the treatment ofschizophrenia. Schizophr Res 2008; 100:20–38.

6 Hafner H, Maurer K. Prodromal symptoms and early detection ofschizophrenia. In: Maj M, Lopez Ibor JJ, Sartorius N, Sato M, Okasha A,editors. Early detection and management of mental disorders. 1st editionWiley; 2005.

7 Post RM, Speer AM, Hough CJ, Xing G. Neurobiology of bipolar illness:implications for future study and therapeutics. Ann Clin Psychiatry2003; 15:85–94.

8 Gitlin MJ, Swendsen J, Heller TL, Hammen C. Relapse and impairment inbipolar disorder. Am J Psychiatry 1995; 152:1635–1640.

9 Hafner H, Maurer K, Trendler G, An der Heiden W, Schmidt M, Konnecke R.Schizophrenia and depression: challenging the paradigm of two separatediseases – a controlled study of schizophrenia, depression and healthycontrols. Schizophr Res 2005; 77:11–24.

10 Tohen M, Jacobs TG, Grundy SL, McElroy SL, Banov MC, Janicak PG, et al.Efficacy of olanzapine in acute bipolar mania: a double-blind, placebo -controlled study. The Olanzipine HGGW Study Group. Arch Gen Psychiatry2000; 57:841–849.

11 Robb JC, Cooke RG, Devins GM, Young LT, Joffe RT. Quality of life and lifestyledisruption in euthymic bipolar disorder. J Psychiatr Res 1997; 31:509–517.

12 Judd LL, Schettler PJ, Akiskal HS, Maser J, Coryell W, Solomon D, et al.Long-term symptomatic status of bipolar I versus bipolar II disorders. Int JNeuropsychopharmacol 2003; 6:127–137.

13 Sachs GS, Thase ME, Otto MW, Bauer M, Miklowitz D, Wisniewski SR, et al.Rationale, design and methods of the systematic treatment enhancement pro-gram for bipolar disorder (STEP-BD). Biol Psychiatry 2003; 53:1028–1042.

14 McIntyre RS, Konarski JZ, Yatham LN. Comorbidity in bipolar disorder: aframework for rational treatment selection. Hum Psychopharmacol 2007;19:369–386.

15 Faravelli C, Rosi S, Alessandra Scarpato M, Lampronti L, Amedei SG,Rana N. Threshold and subthreshold bipolar disorders in theSesto Fiorentino Study. J Affect Disord 2006; 94:111–119.

16 Henry C, Den Bulke DV, Bellivier F, Etain B, Rouillon F, Leboyer M. Anxietydisorders in 318 bipolar patients: prevalence and impact on illness severityand response to mood stabilizer. J Clin Psychiatry 2003; 64:331–335.

17 Binder EB, Kinkead B, Nemeroff CB. Neuropeptides. In: Brier A, Bymaster F,Tran P, Lewis M, editors. Current issues in the psychopharmacology ofschizophrenia. Lippincott Williams & Wilkins; 2001.

18 Sachs GS, Nierenberg AA, Calabrese JR, Marangell LB, Wisniewski SR,Gyulai L, et al. Effectiveness of adjunctive antidepressant treatment forbipolar depression. N Engl J Med 2007; 356:1711–1722.

19 Hirschfeld RM, Baker JD, Wozniak P, Tracy K, Sommerville KW. Thesafety and early efficacy of oral-loaded divalproex versus standard-titrationdivalproex, lithium, olanzapine and placebo in the treatment of acute maniaassociated with bipolar disorder. J Clin Psychiatry 2003; 64:841–846.

20 Goodwin FK, Jamison KR. Manic-depressive illness: bipolar disorders andrecurrent depression. 2nd edition. USA: Oxford University Press; 2007.

21 Keck PE, McElroy SL, Strakowski SM. Anticonvulsants and antipsychoticsin the treatment of bipolar disorder. J Clin Psychiatry 1998; 59 (Suppl 6):74–81. discussion 82.

22 Pope HGJ, Lipinski JFJ. Diagnosis in schizophrenia and manic-depressiveillness: a reassessment of the specificity of ‘schizophrenic’ symptoms in thelight of current research. Arch Gen Psychiatry 1978; 35:811–828.

23 Taylor MA, Abrams R. Manic-depressive illness and good prognosisschizophrenia. Am J Psychiatry 1975; 132:741–742.

24 Vieta E, Colom F, Corbella B, Martınez Aran A, Reinares M, Benabarre A,et al. Clinical correlates of psychiatric comorbidity in bipolar I patients.Bipolar Disord 2001; 3:253–258.

25 Dutta R, Boydell J, Kennedy N, Van Os J, Fearon P, Murray RM. Suicide andother causes of mortality in bipolar disorder: a longitudinal study. PsycholMed 2007; 37:839–847.

26 Benedetti A, Fagiolini A, Casamassima F, Mian MS, Adamovit A, Musetti L,et al. Gender differences in bipolar disorder type 1: a 48-week prospectivefollow-up of 72 patients treated in an Italian tertiary care center. J Nerv MentDis 2007; 195:93–96.

27 Henry JD, Rendell PG, Kliegel M, Altgassen M. Prospective memory inschizophrenia: primary or secondary impairment? Schizophr Res 2007;95:179–185.

28 Hummel B, Dittmann S, Forsthoff A, Matzner N, Amann B, Grunze H.Clozapine as add-on medication in the maintenance treatment of bipolarand schizoaffective disorders: a case series. Neuropsychobiology 2002;45 (Suppl 1):37–42.

29 Morselli PL, Elgie R. GAMIAN-Europe/BEAM Survey I: global analysis of apatient questionnaire circulated to 3450 members of 12 European advocacygroups operating in the field of mood disorders. Bipolar Disord 2003;5:265–278.

30 Pini S, Cassano GB, Dell’Osso L, Amador XF. Insight into illness inschizophrenia, schizoaffective disorder and mood disorders with psychoticfeatures. Am J Psychiatry 2001; 158:122–125.

31 Altamura AC, Armadoros D, Jaeger M, Kernish R, Locklear J, Volz HP. Im-portance of open access to atypical antipsychotics for the treatment ofschizophrenia and bipolar disorder: a European perspective. Curr Med ResOpin 2008; 24:2271–2282.

32 Physicians’ Desk Reference. Physicians’ desk reference 2009; 63rd edition.Thomson Reuters, 2008.

33 Vieta E, Rosa AR. Evolving trends in the long-term treatment of bipolardisorder. World J Biol Psychiatry 2007; 8:4–11.

34 Suppes T, Dennehy EB, Hirschfeld RM, Altshuler LL, Bowden CL, Calabrese JR,et al. The Texas implementation of medication algorithms: update to the algo-rithms for treatment of bipolar I disorder. J Clin Psychiatry 2005; 66:870–886.

35 Scottish Intercollegiate Guidelines Network (SIGN). Bipolar affectivedisorder: a national clinical guideline. 200582. Scottish IntercollegiateGuidelines Network (SIGN).

36 Grunze H, Kasper S, Goodwin G, Bowden C, Baldwin D, Licht R, et al.World Federation of Societies of Biological Psychiatry (WFSBP) guidelinesfor biological treatment of bipolar disorders, Part I: treatment of bipolardepression. World J Biol Psychiatry 2002; 3:115–124.

37 Yatham LN, Kennedy SH, O’donovan C, Parikh SV, Macqueen G, MclntyreRS, et al. Canadian Network for Mood and Anxiety Treatments (CANMAT)guidelines for the management of patients with bipolar disorder:update 2007. Bipolar Disord 2006; 8:721–739.


Diagnosis of Alzheimer’s disease: possible role of functional

imaging techniqueMohamed Ezzat El-Hadidya and Salwa Mohamed Etiabab

aDepartments of Psychiatry andbDiagnostic Radiology, Faculty of Medicine,Mansoura University, Mansoura, Egypt

Correspondence to Mohamed Ezzat El-Hadidy, MD,Associate Professor of Psychiatry, Department ofPsychiatry, Mansoura University Hospitals, Facultyof Medicine, Mansoura University, Mansoura,Egypt, Mansoura 35111, EgyptTel: + 010 2243352;e-mail: [email protected]

Received 15 March 2011Accepted 4 May 2011


2011, 18:195–202

Background

The combination of clinical diagnosis of Alzheimer’s disease (AD) with

diffusion-weighted imaging (DWI) may improve the diagnostic accuracy of AD.

Objectives

This study primarily aims to determine the relationship between the measures of DWI

and clinically diagnosed AD and its severity.

Participants and methods

The sample evaluated comprised three groups: 14 patients with AD, nine patients with

minimal cognitive impairment of amnesic type (a-MCI), and 11 healthy controls. They

were recruited from 2008 to 2009. The diagnosis of AD was made according to the

Diagnostic and Statistical Manual of Mental Disorders fourth edition text revision and

that of a-MCI was made according to Mayo Clinic’s criteria. Dysfunctional severities

were assessed using the Mini-Mental State Examination and Alzheimer’s disease

Assessment Scale. The magnetic resonance DWI technique was used to estimate the

diffusivity of water through different cerebral regions as the assumed imaging marker.

Results

DWI measures of AD in different cerebral regions were found to be higher but not

significantly different from that of the control group. Apparent diffusion coefficient

means of the a-MCI group were closer to and not significantly different from that of the

AD group. In addition, there was no significant relation between the diffusivity

measures in such regions and the total scores of assessments for the

dysfunctional severities.

Conclusion

The only trend toward increased diffusivity was shown with conventional DWI but no

statistically conclusive results were obtained either for gray or for white matter among

patients with AD.

Keywords:

Alzheimer’s disease, diffusion-weighted imaging, minimal cognitive impairment


IntroductionThe diagnosis of definite Alzheimer’s disease (AD) can

only be made by postmortem neuropathological con-

firmation of individuals who had been studied in life and

met the criteria for dementia [1]. Clinical AD is still

diagnosed by excluding other causes of dementia. A

combination of clinical examination with neuroimaging

may improve diagnostic accuracy using neuropathology as

the standard of comparison. Temporal lope atrophy

progresses 10 times faster in AD than in normal aging.

Indices of atrophy are statistically related to cognitive

performance [2]. Such variables were correlated with the

severity of neuropathological changes. Hence, Hentschel

and Forstel [3] concluded that hippocampal imaging has

proven to be a clinically useful and feasible method for

identifying patients with early AD, which is demon-

strated by diffusion-weighted imaging (DWI) technique.

This technique involves noninvasive functional imaging,

that is, processing through high-speed magnetic reso-

nance imaging (MRI), with images acquired in a few

seconds or less, thus providing motion-free images. The

advent of a high-speed gradient has made DWI an

everyday routine scan and has led to its establishment as

an Food and Drug Administration-approved clinical

screening examination for nearly all neurology examina-

tions today [4].

With the modest but important breakthrough in the

treatment of AD, the diagnostic focus has increasingly

shifted to the accurate detection of the earliest phase of

the illness. The challenge of distinguishing preclinical

AD from changes in normal aging or established AD has

been recognized during several attempts at clinical

classification. Of these attempts, Mayo Clinic’s MCI

has received significant attention. However, as not all

individuals diagnosed as having MCI will develop AD;

hence, there is a need to predict progression reliably [5].

The diagnosis and prognosis of a-MCI has been studied

most thoroughly. It is frequently a prodrome to AD,

whereas the prognostic significance of other subtypes of

MCI is not well understood. Brain imaging studies are not

Original article 195

2090-5408 & 2011 Okasha Institute of Psychiatry, Ain Shams University DOI: 10.1097/01.XME.0000403815.41947.e1

routinely used for the diagnosis of MCI, although imaging

techniques are rapidly developing and may prove to be

clinically useful in future [6].

The aim of this study was to determine the relationship

between the measures of diffusivity of water molecules

and clinically diagnosed AD and its prototype a-MCI.

Changes in DWI in the right and left cerebral regions of

AD were assessed. In addition, the relationship between

the severity of cognitive and behavioral manifestations of

AD as measured by neuropsychological assessments and

the DWI was tested. Determination of such a relationship

may help in differentiating between normal aging, MCI,

and AD and hence, improving the diagnostic accuracy.

Participants and methodsParticipants

The sample evaluated comprised three groups: 14 patients

(eight men and six women) with AD, nine patients (five

men and four women) with a-MCI, and 11 controls (six

men and five women). The original sample comprised 16

patients with AD, with two dropouts, 11 patients with a-

MCI, also with two dropouts. These were because of

nonconcordant diagnoses. Data were collected from 2008 to

2009. Patients were recruited from outpatients of the

geriatric unit of the Psychiatric Department of the

Mansoura University Hospitals. The diagnosis of AD was

made according to the Diagnostic and Statistical Manual ofMental Disorders fourth edition text revision [7] and that of

a-MCI was made according to Mayo Clinic’s criteria [8,9].

All patients were diagnosed through information obtained

from an extensive clinical history and physical examination

by two independent senior psychiatrists. Participants were

aged between 50 and 80 years without a history of brain

trauma, epilepsy, brain tumor, stroke, psychiatric disorders,

and other systemic disease that could affect brain function.

Patients with atherosclerotic white matter disease as shown

by MRI were also excluded despite the absence of clinical

correlates to nullify the confounding effect of mixed

pathology. Eleven healthy controls were matched with age

and sex of cases and not receiving medical treatment that

could affect the brain metabolism. They were attendants of

psychiatric patients of the Mansoura University Hospital.

Informed consent was obtained from all participants.

Assessments

(I) Assessment Scales:

1. Mini-Mental State Examination (MMSE) [10]: this

is a screening instrument that provides a brief

assessment of an individual’s orientation to time and

place, recall ability in terms of short memory, and

arithmetic ability. The MMSE has been used

extensively in clinical settings. It is emphasized

that this instrument should not be used to diagnose

dementia but rather as a bedside instrument to

grade the cognitive function of a patient.

2. Alzheimer’s disease Assessment Scale (ADAS) [11]:

this is a rater scale that measures the severity of

dysfunction in cognitive and noncognitive behaviors

characteristic of AD. Cognitive and memory task

items compromise 60% of the total possible points.

The ADAS appears to be sensitive to increasing

dysfunction as the illness progress.

(II) Brain imaging: DWI; a new noninvasive functional

MRI) technique was implemented at the Depart-

ment of Diagnostic Radiology of the Mansoura

University Hospitals. The random movement of

water molecules affects the magnetic resonance

gradient-echo intensity. Hence, DWI estimates the

diffusivity of water molecules through the inter-

stitial tissue. Lesions with reduced water mobility

appear very hyperintense and vice versa. The

resultant signal intensity of a voxel of tissue

containing moving protons of the hydrogen atoms

1H in the water molecules for a given pixel is

measured using the apparent diffusion coefficient

(ADC). The average ADC was electronically gener-

ated incorporating all planes, axial, coronal, and

sagittal, for each pixel to remove artifacts because

of the direction of acquisition [4]. In this study,

conventional ADC values, with applied strength (b

value) = 1000, were calculated from the DWI in the

regions of interest located in the left and right

corpus striatum, basal ganglia, thalamus, amygdala,

hippocampus, and white and gray matter of the

frontal and parietal areas. Areas with less water

diffusion indicated more intense regions. Such

regions were selected as mostly implicated in AD.

Analysis

Analysis was performed using the Statistical Package for

Social Sciences (SPSS, version 12.0 for Windows, SPSS

Inc., Chicago, USA). The reliability between the two

psychiatrists was examined using the Kappa method. The

ADC variables for the groups were analyzed using the

independent-samples t test for equality of means in

which Equal variances were assumed. Paired samples

statistics were used to assess the differences in diffusion

in both cerebral hemispheres among the Alzheimer’s a-

MCI and control groups. Regression analysis was carried

out to assess the effect of ADC of the AD group in

different cerebral regions as predictors for the severity of

the dysfunction as measured by MMSE and ADAS. These

scales have total scores that measure interpenetrated

global functions of different brain areas. As the statistical

summation of the diffusivity measures of different brain

areas may not be practically informative for comparison

with these total scores, the possible separate contribu-

tions of ADC in specific areas to different functions were

examined using the regression analysis method. Different

predictor regions were tested because several brain

functions were measured by the assessment scales.

Levels of significance are reached when P value is less

than or equal to 0.05 at a confidence interval of 95%.

ResultsConsidering the diffusivity measures, the AD group’s

means differed nonsignificantly from that of the control


group. Such insignificant findings were obtained despite

the higher mean ADC scores of AD groups in all the

cerebral regions included. (Table 1). The ADC means of

a-MCI patients were closer to that of patients with AD,

with no significant difference (Table 2). Table 3 shows

a comparison of ADC measures of different regions

between the two cerebral hemispheres in the AD group.

In addition, no significant difference in the ADC on both

sides was found regardless of the region. However, the

diffusivity measures were significantly correlated among

some of these regions between the right and the left

sides, namely the corpus striatum (Po0.001), amygdala

(Po0.005), hippocampus (Po0.005), frontal gray matter

(Po0.05), and parietal white matter (Po0.005). Sig-

nificant correlations were found between certain regions

on both sides in the a-MCI group (Table 4) including the

corpus striatum (P = 0.001), thalamus (Po0.01), hippo-

campus (Po0.005), and frontal gray matter (Po0.01).

Low significant correlations were found only in the

corpus striatum (P = 0.01) and thalamus (Po0.05) in the

control group (Table 5).

The ADCs of the AD group in each of the selected

cerebral regions were implicated by regression analysis as

pathological predictors for the severity of the dysfunc-

tions. Such dysfunctions measured using the assessment

scales were assumed to be dependent variables. There

was no significant relation between the diffusivity

measures in such regions and the total scores of cognitive

dysfunction measured by MMSE (Table 6) and the

severity scores of cognitive and noncognitive dysfunction

measured by ADAS (Table 7).

DiscussionAD is a neurodegenerative disorder that involves mostly

the gray matter, although white matter components such

as axons and oligodendrocytes have been strongly

implicated by histopathological studies [12]. General

brain atrophy occurs, but temporal lobe structures and

periventricular white matter including the corpus callo-

sum have been implicated in MRI studies [13]. Most

commonly, clinicians refer to clinical criteria to distin-

guish between normal aging, MCI, and AD. Presumably,

there are features of neuroimaging measures that may

help distinguish between these conditions for which

further studies are needed [14,15]. It may ultimately be

the case that a combination of clinical features, neurop-

sychological testing, biomarkers, and neuroimaging may

be necessary to improve the diagnostic accuracy [9].

In this study, higher but nonsignificant mean scores of

diffusivity measures were found in the AD group

compared with the control group in all of the selected

regions. This might account for the low tissue densities

Table 1 Comparison of the ADC between AD and control groups in different cerebral regions

Regions Groups N Mean Standard deviation t Significancea (2-tailed)

Left corpus striatum Alzheimer 14 108.814 18.3483 2.273 0.033Control 11 94.755 10.2186

Right corpus striatum Alzheimer 14 107.729 15.0114 1.881 0.073Control 11 97.482 11.2861

Left basal ganglia Alzheimer 14 103.936 28.0499 1.679 0.107Control 11 88.736 11.7747

Right basal ganglia Alzheimer 14 101.750 17.6190 2.779 0.011Control 11 85.300 9.6332

Left thalamus Alzheimer 14 105.393 25.5568 1.445 0.162Control 11 93.936 6.4615

Right thalamus Alzheimer 14 103.707 13.5036 2.416 0.024Control 11 92.855 6.9888

Left amygdala Alzheimer 14 106.543 20.6455 0.846 0.406Control 11 99.109 23.2309

Right amygdala Alzheimer 14 109.621 16.4808 1.999 0.058Control 11 96.373 16.4050

Left hippocampus Alzheimer 14 107.936 26.1145 1.101 0.282Control 11 97.882 17.1712

Right hippocampus Alzheimer 14 113.471 34.6008 1.423 0.168Control 11 97.027 18.3253

Left frontal white matter Alzheimer 14 107.500 23.9186 1.674 0.108Control 11 94.473 10.6951

Right frontal white matter Alzheimer 14 104.921 14.5526 0.466 0.646Control 11 102.336 12.6945

Left frontal gray matter Alzheimer 14 116.493 33.2244 1.580 0.128Control 11 100.245 7.9998

Right frontal gray matter Alzheimer 14 112.921 31.0600 0.696 0.493Control 11 104.882 25.1784

Left parietal white matter Alzheimer 14 110.464 22.9256 1.625 0.118Control 11 98.873 6.1311

Right parietal white matter Alzheimer 14 126.564 48.5468 2.040 0.053Control 11 96.464 4.7096

Left parietal gray matter Alzheimer 14 143.036 63.2490 0.465 0.646Control 11 133.064 36.2246

Right parietal gray matter Alzheimer 14 148.407 67.3828 1.304 0.205Control 11 119.373 33.4168

ADC, Apparent diffusion coefficient.aDegrees of freedom = 23.

Diagnosis of Alzheimer’s disease El-Hadidy and Etiaba 197

Table 2 Comparison of the ADC between AD and MCI groups in different cerebral regions

Regions Groups N Mean Standard deviation t Significancea (2-tailed)

Left corpus striatum Alzheimer 14 108.814 18.3483 0.310 0.760MCI 9 106.511 15.7345

Right corpus striatum Alzheimer 14 107.729 15.0114 – 0.574 0.572MCI 9 111.822 19.0953

Left basal ganglia Alzheimer 14 103.936 28.0499 0.670 0.510MCI 9 97.189 13.3407

Right basal ganglia Alzheimer 14 101.750 17.6190 0.412 0.684MCI 9 98.133 24.5348

Left thalamus Alzheimer 14 105.393 25.5568 0.097 0.924MCI 9 104.478 14.8212

Right thalamus Alzheimer 14 103.707 13.5036 0.092 0.928MCI 9 103.178 13.4440

Left amygdale Alzheimer 14 106.543 20.6455 1.252 0.224MCI 9 97.067 11.4703

Right amygdala Alzheimer 14 109.621 16.4808 1.361 0.188MCI 9 95.000 34.8901

Left hippocampus Alzheimer 14 107.936 26.1145 1.067 0.298MCI 9 97.522 16.1679

Right hippocampus Alzheimer 14 113.471 34.6008 0.066 0.948MCI 9 112.278 52.7150

Left frontal white matter Alzheimer 14 107.500 23.9186 1.314 0.203MCI 9 95.744 14.9052

Right frontal white matter Alzheimer 14 104.921 14.5526 0.726 0.476MCI 9 100.778 11.1294

Left frontal gray matter Alzheimer 14 116.493 33.2244 0.980 0.338MCI 9 104.700 16.9758

Right frontal gray matter Alzheimer 14 112.921 31.0600 0.712 0.484MCI 9 105.033 14.0602

Left parietal white matter Alzheimer 14 110.464 22.9256 – 1.060 0.301MCI 9 122.567 31.9545

Right parietal white matter Alzheimer 14 126.564 48.5468 – 1.075 0.294MCI 9 221.478 328.9487

Left parietal gray matter Alzheimer 14 143.036 63.2490 0.253 0.803MCI 9 136.600 53.2760

Right parietal gray matter Alzheimer 14 148.407 67.3828 0.310 0.760MCI 9 140.344 48.6679

AD, Alzheimer’s disease; ADC, apparent diffusion coefficient; MCI, minimal cognitive impairment.aDegrees of freedom = 23.

Table 3 Differencea of the ADC between the two cerebral hemispheres in the AD group

Regions Mean Standard deviation Correlation Significance t Significance (2-tailed)

Corpus striatumLeft 108.814 18.3483 0.941 0.000 0.616 0.549Right 107.729 15.0114

Basal gangliaLeft 103.936 28.0499 0.306 0.288 0.290 0.776Right 101.750 17.6190

ThalamusLeft 105.393 25.5568 0.234 0.421 0.243 0.812Right 103.707 13.5036

AmygdalaLeft 106.543 20.6455 0.699 0.005 – 0.773 0.454Right 109.621 16.4808

HippocampusLeft 107.936 26.1145 0.699 0.005 – 0.834 0.419Right 113.471 34.6008

Frontal white matterLeft 107.500 23.9186 0.326 0.255 0.409 0.689Right 104.921 14.5526

Frontal gray matterLeft 116.493 33.2244 0.545 0.044 0.435 0.671Right 112.921 31.0600

Parietal white matterLeft 110.464 22.9256 0.747 0.002 – 1.725 0.108Right 126.564 48.5468

Parietal gray matterLeft 143.036 63.2490 0.192 0.510 – 0.242 0.813Right 148.407 67.3828

ADC, apparent diffusion coefficient.aPaired-samples statistics, degrees of freedom = 13.


among patients with AD that may attain significance with

large-scale research projects. Some conventional DWI

studies of AD obtained no statistically significant results

for either white or gray matter [16,17]. However, some

other conventional studies showed significant elevation in

the hippocampal ADC [18,19]. Several other AD studies

used more sophisticated techniques and showed more

conclusive results. One study concluded that a high

b value DWI is more sensitive to AD-related white matter

degeneration than conventional DWI [20]. However,

Moseley and Bammer [4] argued that the quantification

of the ADC at higher b values will not be totally correct.

Table 5 Differencea of the ADC between the two cerebral hemispheres in the control group


Corpus striatumLeft 94.755 10.2186 0.736 0.010 – 1.149 0.277Right 97.482 11.2861

Basal gangliaLeft 88.736 11.7747 0.361 0.275 0.932 0.373Right 85.300 9.6332


AmygdalaLeft 99.109 23.2309 0.482 0.133 0.432 0.675Right 96.373 16.4050

HippocampusLeft 97.882 17.1712 0.360 0.277 0.141 0.891Right 97.027 18.3253

Frontal white matterLeft 94.473 10.6951 0.408 0.213 – 2.032 0.070Right 102.336 12.6945

Frontal gray matterLeft 100.245 7.9998 – 0.145 0.670 – 0.559 0.588Right 104.882 25.1784

Parietal white matterLeft 98.873 6.1311 0.076 0.824 1.074 0.308Right 96.464 4.7096

Parietal gray matterLeft 133.064 36.2246 – 0.210 0.536 0.838 0.422Right 119.373 33.4168


Table 4 Differencea

of the ADC between the two cerebral hemispheres in the a-MCI group


Corpus striatumLeft 106.511 15.7345 0.904 0.001 – 1.916 0.092Right 111.822 19.0953

Basal gangliaLeft 97.189 13.3407 0.629 0.069 – 0.148 0.886Right 98.133 24.5348


AmygdalaLeft 97.067 11.4703 0.571 0.108 0.208 0.841Right 95.000 34.8901

HippocampusLeft 97.522 16.1679 0.846 0.004 – 1.107 0.300Right 112.278 52.7150

Frontal white matterLeft 95.744 14.9052 0.655 0.056 – 1.331 0.220Right 100.778 11.1294

Frontal gray matterLeft 104.700 16.9758 0.808 0.008 – 0.100 0.923Right 105.033 14.0602

Parietal white matterLeft 122.567 31.9545 – 0.117 0.765 – 0.888 0.400Right 221.478 328.9487

Parietal gray matterLeft 136.600 53.2760 0.654 0.056 – 0.264 0.799Right 140.344 48.6679



In another research, with a map of subcortical mean

diffusivity superimposed on the corresponding anatomic

image, significant mean diffusivity elevation was observed

in the medial aspect of the right frontal, bilateral parietal,

and right temporal lobes [21]. Diffusion differences

between patients and controls were observed after

controlling for volumetric differences in some of the

cerebral regions, whereas independent volumetric differ-

ences were observed in other regions [22].

This result showed a marked correlation of diffusivity

measures between the right and the left sides regarding

the corpus striatum, amygdala, hippocampus, parietal

white matter, and frontal gray matter in order, in the AD

group. In addition, similar correlations were found in the

a-MCI group including the corpus striatum, hippocam-

pus, gray matter, and thalamus. Only low significant

correlations were found in the corpus striatum and

thalamus in the control group. This may suggest that in

the dementia and predementia stages, microstructural

diffusion changes in such regions occur on both sides.

However, the DWI did not predict the cognitive or the

behavioral dysfunctional severities of AD manifestations

measured by the neuropsychological ratings. In a previous

study, diffusion measures did not correlate with the

severity of dementia [18]. Weak correlations were found

in another study between clinical scales and ADC values

in the hippocampi, temporal lobes, left frontal lobe, and

left occipital lobe [23]. However, more sophisticated

diffusivity techniques might be helpful.

In this study, the ADC means of the MCI group were

closer and not significantly different from that of the AD

group in almost all regions. These differences from the

control group may reach significance in large-scale

research projects. It was argued that brain imaging

provides useful information, but these diagnostic tools

remain imprecise and have not been validated for routine

use. The process of the diagnosis must therefore focus

on the analysis of the cognitive impairment of the

predementia phase of AD. This will help identify

‘hippocampal amnesia syndrome’ suggestive of the

Table 6 ADC Predictability for MMSE scores of the AD group in different cerebral regions

Predictors Standardized coefficients b t Significance F (Significance)a

Left corpus striatum – 0.885 – 1.035 0.359 0.857 (0.642)Right corpus striatum – 0.464 – 0.406 0.705Left basal ganglia 0.997 1.033 0.360Right basal ganglia – 0.491 – 0.410 0.703Left thalamus – 0.676 – 0.628 0.564Right thalamus 1.279 0.745 0.498Left amygdala – 0.700 – 1.470 0.216Right amygdala 0.240 0.533 0.622Left hippocampus – 0.143 – 0.195 0.855Hippocampus right 0.413 0.442 0.682Left frontal white matter – 0.601 – 1.275 0.271Right frontal white matter 0.447 0.974 0.385Left frontal gray matter 0.365 0.669 0.540Right frontal gray matter – 0.223 – 0.319 0.766Left parietal white matter 0.711 1.768 0.152Right parietal white matter 0.005 0.005 0.996Left parietal gray matter 0.251 0.531 0.624Right parietal gray matter – 0.336 – 0.665 0.542

ADC, apparent diffusion coefficient; MMSE, Mini-Mental State Examination.aRegression analysis’ dependent variable: MMSE total.

Table 7 ADC Predictability in different cerebral regions for the total ADAS scores of the AD group

Predictors Standardized coefficients b t Significance F (Significance)a

Left corpus striatum 0.526 0.517 0.632 0.542 (0.836)Right corpus striatum 0.869 0.640 0.557Left basal ganglia – 0.273 – 0.238 0.824right basal ganglia 0.611 0.430 0.690Left thalamus – 0.440 – 0.343 0.749Right thalamus – 1.802 – 0.883 0.427Left amygdala 0.342 0.605 0.578Right amygdala – 0.023 – 0.043 0.968Left hippocampus 0.093 0.107 0.920Right hippocampus – 0.879 – 0.791 0.473Left frontal white matter 0.651 1.162 0.310Right frontal white matter – 0.100 – 0.183 0.864Left frontal gray matter – 0.660 – 1.017 0.367Right frontal gray matter 0.429 0.516 0.633Left parietal white matter – 0.130 – 0.272 0.799Right parietal white matter 0.846 0.660 0.545Left parietal gray matter – 0.022 – 0.040 0.970Right parietal gray matter – 0.365 – 0.609 0.576

ADAS, Alzheimer’s disease Assessment Scale; ADC, apparent diffusion coefficient.aRegression analysis’ dependent variable: ADAS total.


diagnosis of AD [14]. However, higher baseline hippo-

campal diffusivity was associated with a greater hazard of

progression to AD in a-MCI [24]. Hence, it was argued

that DWI may help identify patients with a-MCI who will

progress to AD as efficiently as or better than structural

MRI measures of hippocampal atrophy.

Limitations

The sample size was small as it was difficult to recruit

pure concordantly diagnosed AD and a-MCI cases. The

wide age range (50–80 age years) may result in

differences between individuals in different stages of

age-related brain involution changes.

ConclusionConventional DWI only showed a trend toward increased

diffusivity, with no statistically significant results ob-

tained for either gray or white matter. This may reach

significance with large-scale research projects. In addi-

tion, the use of more sophisticated diffusion techniques

may yield more precise results. In the dementia and

predementia stages, microstructural diffusion changes in

certain regions occur on both sides. These can contribute

toward the diagnostic accuracy of AD and the prede-

mentia stage but may not help in the assessment of

cognitive or behavioral dysfunctional severity.

AcknowledgementsThe authors thank faculty members at the Psychiatric and DiagnosticRadiological Departments of the Mansoura University Hospitals. Theresearchers work at El-Mansoura Faculty of Medicine, a Government-funded institute that serves as a primary educational and researchfacility for the east Delta areas. The current research has nospecial fund.

Conflicts of interestThere is no conflict of interest to declare.

References1 Petersen RC, Doody R, Kurz A, Mohs RC, Morris JC, Rabins PV, et al.

Current concepts in mild cognitive impairment. Arch Neurol 2001; 58:1985–1992.

2 Chetelat G, Baron JC. Early diagnosis of Alzheimer’s disease: contribution ofstructural neuroimaging. Neuroimage 2003; 18:525–541.

3 Hentschel F, Forstel H. Neuroimaging and neurophysiology in the elderly. In:Jacoby R, Oppenheimer C, Dening T, Thomas A, editors. Oxford textbookof old age psychiatry. Oxford: Oxford University Press; 2008. pp. 181–192.

4 Moseley ME, Bammer R. Diffusion-weighted magnetic resonance imaging.In: Latchaw R, Kucharczyk J, Moseley ME, editors. Imaging of the nervoussystem: diagnostic and therapeutic applications. Philadelphia, PA: Elsevier-Mosby; 2005. pp. 227–248.

5 Chong MS, Sahadevan S. Preclinical Alzheimer’s disease: diagnosis andprediction of progression. Lancet Neurol 2005; 4:576–579.

6 Rosenberg PB, Johnston D, Lyketsos CG. A clinical approach to mildcognitive impairment. Am J Psychiatry 2006; 163:1884–1890.

7 American Psychiatric Association. Diagnostic and statistical manual ofmental disorders. 4th edition. USA: American Psychiatric Pub; 2000.

8 Petersen RC, Stevens JC, Ganguli M, Tangalos EG, Cummings JL, DeKoskyST. Practice parameter: early detection of dementia: mild cognitive impair-ment (an evidence-based review). Report of the Quality Standards Sub-committee of the American Academy of Neurology. Neurology 2001;56:1133–1142.

9 Petersen RC. Mild cognitive impairment as a diagnostic entity. J Intern Med2004; 256:183–194.

10 Folstein MF, Folstein SE, McHugh PR.‘Mini-mental state’. A practical methodfor grading the cognitive state of patients for the clinician. J Psychiatr Res1975; 12:189–198.

11 Rosen WG, Mohs RC, Davis KL. A new rating scale for Alzheimer’s disease.AmJPsychiatry 1984; 141:1356–1364.

12 Brun A, Englund E. A white matter disorder in dementia of the Alzheimertype: a pathoanatomical study. Ann Neurol 1986; 19:253–262.

13 Hampel H, Teipel SJ, Alexander GE, Horwitz B, Teichberg D, Schapiro MB,et al. Corpus callosum atrophy is a possible indicator of region- and cell type-specific neuronal degeneration in Alzheimer disease: a magnetic resonanceimaging analysis. Arch Neurol 1998; 55:193–198.

14 Sarazin M, Dubois B. Mild cognitive impairment or pre-demential Alzheimer’sdisease? Rev Neurol 2002; 158 (10 Suppl):S30–S34.

15 Wolf H, Jelic V, Gertz HJ, Nordberg A, Julin P, Wahlund LO. A critical dis-cussion of the role of neuroimaging in mild cognitive impairment. Acta NeurolScand Suppl 2003; 179:52–76.

16 Hanyu H, Sakurai H, Iwamoto T, Takasaki M, Shindo H, Abe K, Diffusion-weighted MR. imaging of the hippocampus and temporal white matter inAlzheimer’s disease. J Neurol Sci 1998; 156:195–200.

17 Bozzao A, Floris R, Baviera ME, Apruzzese A, Simonetti G. Diffusion andperfusion MR imaging in cases of Alzheimer’s disease: correlations with cor-tical atrophy and lesion load. AJNR Am J Neuroradiol 2001; 22:1030–1036.

18 Sandson TA, Felician O, Edelman RR, Warach S. Diffusion-weighted mag-netic resonance imaging in Alzheimer’s disease. Dement Geriatr CognDisord 1999; 10:166–171.

19 Kantarci K, Jack CR. Jr, Xu YC, Campeau NG, O’Brien PC, Smith GE, et al.Mild cognitive impairment and Alzheimer disease: regional diffusivityof water. Radiology 2001; 219:101–107.

20 Yoshiura T, Mihara F, Tanaka A, Ogomori K, Ohyagi Y, Taniwaki T, et al. High bvalue diffusion-weighted imaging is more sensitive to white matter degen-eration in Alzheimer’s disease. Neuroimage 2003; 20:413–419.

21 Yoshiura T, Noguchi T, Koga H, Ohyagi Y, Hiwatashi A, Togao O, et al.Cortical damage in Alzheimer’s disease. Estimation in medial and lateralaspects of the cerebrum using an improved mapping method based ondiffusion-weighted magnetic resonance imaging. Acad Radiol 2008;15:193–200.

22 Canu E, McLaren DG, Fitzgerald ME, Bendlin BB, Zoccatelli G, AlessandriniF, et al. Microstructural diffusion changes are independent of macrostructuralvolume loss in moderate to severe Alzheimer’s disease. J Alzheimer’s Dis2010; 19:963–976.

23 Fayed N, Davila J, Oliveros A Jr, Medrano J, Castillo J. Correlation of findingsin advanced MR techniques with global severity scales in patients with somegrade of cognitive impairment. Neurol Res 2010; 32:157–165.

24 Kantarci K, Petersen RC, Boeve BF, Knopman DS, Weigand SD, O’BrienPC, et al. DWI predicts future progression to Alzheimer disease in amnesticmild cognitive impairment. Neurology 2005; 64:902–904.


Cognitive functions after hemorrhagic stroke: follow-up studyHala Ahmed El-Boraiea, Mohamed Abd El-Salam Mohamedb, Mostafa Amra

and Salwa Tobara

aDepartments of Psychiatry andbNeurology, Mansoura University, Mansoura, Egypt

Correspondence to Hala Ahmed El-Boraie,Department of Psychiatry, Mansoura University,Mansoura, EgyptTel: + 123103929l; fax: + 2050 2248487;e-mail: [email protected]

Received 5 March 2011Accepted 7 April 2011


2011, 18:203–210

Objectives

There are scarce data on long-term cognitive outcomes after first-ever hemorrhagic

stroke.

Aim

This study was carried out to determine the frequency of cognitive impairment,

no dementia after an intracerebral hemorrhagic stroke and to study their evolution

toward dementia (transitions in cognitive state) during a 2-year follow-up.

Methods

Thirty-five patients with first-ever hemorrhagic strokes and in an age-matched and sex-

matched comparison group (nonstroke, n = 20) were followed up for 2 years by three

serial assessments. Stroke patients at 3, 12, 24 months after discharge were

evaluated together with nonstrokes, by an extensive neuropsychological battery and

clinical psychiatric interview based on Diagnostic and Statistical Manual of Mental

Disease, 4th edition TR criteria. Rates of cognitive change were compared using

repeated-measures analyses. Factors associated with incident dementia and cognitive

impairment, no dementia at 2 years were determined by multinomial logistic regression.

Results

The majority of patients (71.4%) were cognitively stable. Fewer cases improved

(11.5%) and 71.1% of the stroke cases worsened at the end of the 24-month

follow-up. There was impaired cognitive function in nearly all cognitive domains of

stroke cases compared with nonstroke cases. Overall, stroke cases showed a

statistically significant decline in mini-mental state examination (MMSE), spatial ability,

and in the executive function domain; however, there was no improvement in attention

nonverbal memory domains. Age at stroke onset was independently associated with

cognitive impairment at the 2-year follow-up P = 0.03.

Conclusion

Cognitive evolution 2 years after hemorrhagic stroke is different among patients, but a

substantial number of patients remain stable. Additional studies are required to reliably

identify individuals at risk for cognitive decline for whom pharmacologic or other

therapeutic interventions would be more suitable and who will probably spontaneously

improve. Classification of stroke by etiology may be more useful to determine patients

at a higher risk of stroke and for its prevention.

Keywords:

longitudinal study, neuropsychology, stroke, vascular cognitive impairment, vascular

dementia


IntroductionStroke remains a major healthcare problem. Approximately

795 000 people in the United States have stroke each

year. About 610 000 are first events, and 6.4 million

Americans are stroke survivors [1]. Stroke is also a leading

cause of functional impairments, with 20% of survivors

requiring institutional care after 3 months and 15–30%

being permanently disabled. Effective prevention re-

mains the best approach for reducing the burden of

stroke. Primary prevention is particularly important

because greater than 77% of strokes are first events [2].

Cognitive decline after stroke is more common than

stroke recurrence. Stroke doubles the risk of dementia

and is a major contributor to vascular cognitive impair-

ment (VCI) and vascular dementia [3].

There are few prospective data on the long-term

cognitive changes and predictors of incident dementia

after a first stroke [4]. Stroke is not only a preventable

but also a treatable disease. However, as the treatment is

only safe and licensed within the first 3 h after stroke,

advancements neurologic services are needed, with an

emphasis on immediate care [5].

Fewer studies have focused on the behavioral and

cognitive manifestations after stroke and these disorders

are often overlooked in clinical practice. Frequently

occurring symptoms are personality changes [6] and


2090-5408 & 2011 Okasha Institute of Psychiatry, Ain Shams University DOI: 10.1097/01.XME.0000405026.17236.f5

neuropsychiatric disorders, such as poststroke depression,

anxiety disorders, or apathy [7]. In addition, neuropsycho-

logical disorders, such as amnesia, executive dysfunction, or

unilateral neglect, are common clinical manifestations after

stroke and may be the single or dominant presenting

features [8].

Most studies on the relation between stroke and cognitive

impairment have reported on vascular dementia or

poststroke dementia in general. The concept of vascular

dementia has recently been discarded by most researchers

because of the inconsistent criteria used to define vascular

dementia [9] and because the level of cognitive impair-

ment required for a diagnosis of dementia does not allow

early identification of patients with less severe but

seriously invalidating cognitive disturbances [10]. Subse-

quently, a range of conceptsthat include milder forms of

cognitive impairment have been developed over the past

few years, such as VCI [11], ‘mild cognitive impair-

ment’ [12], or ‘cognitive impairment, no dementia’

(CIND) [13]. Although these concepts are preferable to

that of vascular dementia, they will attempt to capture a

very diverse phenomenon under one header, resulting in

poor prognostic value and confusion in the literature.

Moreover, these concepts do not provide information on

the nature of the underlying cognitive disorder and the

specific disability that might arise from these deficits.

Nevertheless, early diagnosis of specific cognitive deficits

such as amnesia or executive dysfunction could be very

important to determine an appropriate discharge destina-

tion and in particular to facilitate rehabilitation. Also,

interventions aimed at restoring specific cognitive func-

tions can be initiated at an earlier stage, as studies have

shown that the brain displays a heightened sensitivity to

rehabilitation early after the stroke as compared with later

stages [14,15].

Although the brain is capable of reorganization and

significant cognitive recovery may occur in the first

months after stroke, many patients do not show

improvement at all or even show deterioration in the

long term [16], resulting in poststroke dementia [17].

Clinical criteria for VCI as well as vascular CIND are still

lacking, and major discussions are ongoing in this field.

Detection of cognitive impairment has two difficulties: a

neuropsychological battery fitted to the VCI profile is yet

to be established and limits from normal cognition are

still undefined [18]. Although clinical criteria are still

undefined, considerable work has been carried out to

determine the frequency, characteristics, and evolution of

VCI and V-CIND. Importantly, there is a growing interest

in V-CIND, because patients with only mild cognitive

deficits also have significant disability, may be at an

increased risk of cognitive deterioration, and have more

opportunities for treatment and prevention [19]. There

are few prospective data from population-based studies

on the long-term cognitive changes and predictors of

incident dementia after a first stroke. It is also uncertain

whether early poststroke cognitive status is associated

with a high risk of future incident dementia. The aim of

this study was to determine the frequency of CIND after

intracerebral hemorrhagic stroke and to study their

evolution toward dementia (transitions in cognitive state)

during a 2-year follow-up.

Patients and methodsThis study was carried out in Mansoura University

Hospitals from February 2007 to September 2009.

The study included 35 patients from the neurology

department. All patients had a diagnosis of first-ever

incident hemorrhagic stroke (with no history of prior

stroke). The patient group comprised 28 men and seven

women who completed the assessment tools during the

scheduled follow-up visits. They were included in the

study on the basis of certain inclusion and exclusion

criteria. Inclusion criteria included fully conscious patients.

The exclusion criteria were as follows: (a) patients above

the age of 75 years, (b) other areas of lesions such as

subarachnoid hemorrhage, cerebral infarction, or tumor, (c)

major neurological diseases for example, Alzheimer’s

disease, other dementias, Parkinson’s disease, or epilepsy,

(d) history of any psychiatric diagnosis, (e) history of

psychoactive substance use disorders or current use of

sedating medications, (f) medical conditions such as

hepatic, renal, or pulmonary disease, and (g) patients with

dysphasia or inadequate vision or hearing.

The control group included 20 participants and were

selected to match the patient group in terms of age, sex,

and level of education. None of the control participants

had a history suggestive of any psychiatric, neurological

diseases, head injury, substance use, history of previous

stroke, transient ischemia attack, or medical conditions

such as hepatic, renal, or pulmonary diseases.

Methods

Clinical assessment included neurological examination

and collection of data on demographic distribution,

hypertension diabetes mellitus (DM), myocardial infarc-

tion, and smoking. Moreover, computed tomography or

MRI were carried out for all participants to confirm the

diagnoses. The psychiatric assessment included a clinical

psychiatric interview along with a semistructured psy-

chiatric interview on the basis of Diagnostic and

Statistical Manual of Mental Disease, 4th edition TR

criteria [20] for the diagnosis of dementia.

A neuropsychological battery was designed to cover the

main cognitive functions and to detect early or minimal

cognitive impairment with tests applicable to low-

educated patients with eventual sensorimotor deficits.

The battery included the MMSE scale [21], which is a

5-min screening test that is designed to evaluate basic

mental functions in a number of different areas. Selected

subtests from the Wechsler memory scale were used to

assess memory [22]: the logical memory A–B test

to assess verbal memory, digit forward, and digit backward

to assess attention and short-term verbal memory, visual

reproduction I, II to assess nonverbal memory and word

association to assess executive functioning, which includes

verbal attention (fluency), working memory, abstract


reasoning, and planning. Moreover, the trail making test

was used in its two forms (trail A and B) [23] to assess

executive functions. The Wechsler adult intelligence

scale [24] was used to detect visuo-spatial function

(performance part): The test comprises 11 subtests made

up of six verbal subtests and five performance subtests.

The Bender–Gestalt test (BG) was used also to assess

short-term visual memory and visuo-spatial/visual con-

struction functions.

Tests were grouped into six cognitive domains: (a)

orientation (temporal and spatial orientation from MMSE),

(b) executive ability (trail making A, B, and word

association), (c) verbal memory [logical memory A, B, and

BG (recall)], (d) nonverbal memory visual reproduction I

and II, (e) spatial ability (Wechsler adult intelligence and

BG), and (f) attention (digit forward and backward).

The clinical dementia rating (CDR) scale [25] was used

to characterize and track the level of impairment/

dementia (0 = normal, 0.5 = cognitive decline without

dementia, 1 = mild dementia, 2 = moderate dementia,

and 3 = severe dementia). An overall CDR scale score

may be calculated using an algorithm.

Diagnosis of dementia and cognitive impairment

Diagnostic criteria for dementia

Patients were diagnosed as having dementia or not having

dementia according to the Diagnostic and Statistical

Manual of Mental disorders, 4th edition DSM IV TR, on

the basis of a progressive decline in memory and at least

one other cognitive domain from baseline, the cognitive

changes recorded in the CDR scale, and the neuropsy-

chological battery scores. The final diagnosis was always

made after a thorough assessment of the clinical and

neuropsychological data and controlling for the effects of

sensory-motor defects.

Diagnostic criteria for cognitive impairment, no dementia

CIND was diagnosed in the absence of dementia when

there was cognitive impairment without clinically evident

progression from the previous assessment established

with the CDR (0.5 = cognitive decline without demen-

tia). Neuropsychological examination defined CIND as

failure in at least one cognitive domain. Missing values,

attributable to the inability of the patient to perform a

test, were considered as failure on the test.

Follow-up

After obtaining informed consent, patients were evalu-

ated at admission and reexamined 3, 12, and 24 months

after stroke. In these visits, neurological examinations,

functional psychiatric assessment, neuropsychological

battery, and the diagnosis of dementia were performed.

Patients were classified at each follow-up as having

dementia, CIND, or being noncognitively impaired. The

control group was interviewed at the same intervals to be

comparable with stroke cases.

The statistical analysis of data carried out using an excel

program for graphs and Statistical Package for Social

Science version 17 (SPSS, New York, New York, USA).

The data were in the form of mean ± standard deviation

for quantitative data and frequency and proportion for

qualitative data. The data were analyzed to determine

statistically significant differences between groups. The

one-way analysis of variance test was used to compare

more than two groups, followed by the post-hoc test least

significant difference for intergroup comparisons. For

quantitative data, the student t-test was used to compare

between two groups. A paired-sample t-test was used to

compare one group at different times. The w2 test was

used for qualitative data. Correlation coefficiency was

calculated to detect an association between variables.

Multivariate regression analysis was done for significant

factors. P was considered significant if less than or equal

to 0.05 at a confidence interval of 95%.

ResultsTable 1 shows that in the patient group, most of the

patients were men, half of them had no education, and

one-fourth had more than 10 years of education. Stroke

cases were more likely to have a history of hypertension,

DM, and smoking (Table 2). The site of hematoma was in

subcortical structures in 70.4% of the cases, n = 25 (51.4%

thalamic and 20% basal ganglia), and lobar structures in

28.6% (n = 10) of the cases. Table 3 shows that at

baseline, 14 patients were cognitively normal (CDR = 0,

40%) and 21 patients showed a cognitive decline without

dementia (CDR = 0.5, 60%). Among the controls, 16

participants were cognitively normal (CDR = 0, 80%)

versus four participants, who showed a cognitive decline

without dementia (CDR = 0.5, 20%). During the entire

study period, CIND was diagnosed in 18 stroke cases

(51.4%) and four nonstroke cases (20%). A new incidence

Table 1 Demographic data of the total sample

Stroke group(n = 35)

Mean ± SD

Nonstroke(n = 20)

Mean ± SDSignificant

testP

value

Age 58.46 ± 8.037 57.85 ± 8.41 t = 0.265 0.792Sex

Male, n (%) 28 (80%) 15 (75%) w2 = 0.187 0.666Female, n (%) 7 (20%) 5 (25%)

EducationIlliterate 19 (54.3%) 9 (45%) w2 = 4.95 0.17r6 years 5 (14.3%) 3 (15%)7–9 years 3 (8.6%) 6 (30%)Z10 years 8 (22.9%) 2 (10%)

SD, standard deviation.

Table 2 Risk factors among the total sample

No. (%)

Item Stroke group Nonstroke group

Hypertension 15 (42.9) 6 (3)DM 7 (20) 2 (10)Ischemic heart 3 (8.6) 2 (10)MI 1 (2.9) –Smoking 16 (45.7) 4 (20)

DM, diabetes mellitus; MI, myocardial infarction.

Cognitive functions after hemorrhagic stroke El-Boraie et al. 205

Table 3 Transitions of cognitive state over 2 years after first-ever stroke

Second-year follow-up

Cognition at the 3-month interview First-year follow-up diagnosis Normal CIND Dementia

Stroke groupNormal (n = 14) Normal 11 8 — —

CIND 3 — 5 —Dementia — — — 1

Impaired (n = 21) Normal 2 4 — —CIND 15 — 13 —Dementia 4 — — 4

Nonstroke groupNormal (n = 16) Normal 15 14 — —

CIND 1 — 2 —Dementia — — — —

Impaired (n = 4) — — — — —Normal 1 1 — —CIND 3 — 2 —Dementia — — — 1

CIND, cognitive impairment no dementia.

Table 4 Comparison of cognitive function between the stroke and the nonstroke group at baseline (after 3 months)

Baseline time stroke

Cognitive abilityStroke groupMean ± SD

Nonstroke groupMean ± SD t-test Significance

MMSE 22.3 ± 4.2 25.6 ± 5.1 – 2.59 0.01Verbal memory

Logical memory A, B 11 ± 6.69 17.6 ± 5.86 – 3.7 0.001BG (recall) 6.08 ± 4.37 14.9 ± 4.38 7.19 0.000

Nonverbal memoryVisual reproduction 1.94 ± 1.8 3.25 ± 1.1 – 2.89 0.006Visual reproduction II 2.14 ± 1.98 4.2 ± 1.28 – 4.15 0.000

Spatial abilityWAIS (performance part) 72.3 ± 20.60 88.8 ± 16.56 – 3.06 0.004BG (copy) 9.31 ± 6.63 16 ± 4.77 – 3.951 0.000

AttentionDigit forward 4.97 ± 1.75 6.55 ± 1.57 – 3.32 0.002Digit backward 2.54 ± 1.00 3.85 ± 1.38 – 2.96 0.005

Executive functionTrail making A 237.67 ± 97.01 600.59 ± 61.15 – 0.164 0.870Trail making B 600.89 ± 6.40 568.85 ± 11.13 – 0.498 0.621Word association 3.8 ± 3.81 10.05 ± 2.72 – 6.408 0.000

BG, Bender–Gestalt test; MMSE, mini-mental state examination; SD, standard deviation; WAIS, Wechsler adult intelligence scale.

Table 5 Cognitive change from baseline to the first-year and second-year follow-up in the stroke group

First yeara Second yearb

Cognitive ability Mean ± SD t-test Significance Mean ± SD t-test Significance

MMSE 21.06 ± 5.18 2.47 0.019 20.71 ± 5.09 2.42 0.02Verbal memory

Logical memory A, B 10.08 ± 6.87 1.96 0.05 9.74 ± 7.09 1.81 0.08BG (recall) 6.08 ± 4.37 0.000 1.00 5.91 ± 4.41 0.322 0.75

Nonverbal memoryVisual reproduction I 1.88 ± 1.081 0.466 0.644 2.00 ± 1.93 – 0.291 0.77Visual reproduction II 2.06 ± 1.86 0.517 0.609 2.2 ± 1.95 – 0.91 0.77

Spatial abilityWAIS (performance) 68.57 ± 21.65 1.97 0.057 66.97 ± 20.92 2.183 0.04BG (copy) 9.23 ± 6.39 0.131 0.896 9.05 ± 6.59 0.325 0.74

AttentionDigit forward 4.68 ± 1.66 1.378 0.177 4.66 ± 1.7 0.123 0.23Digit backward 2.31 ± 1.65 1.276 0.211 2.26 ± 1.74 1.51 0.14

Executive functionTrail making A 254.55 ± 93.9 – 2.139 0.040 256.7 ± 94.9 – 2.13 0.04Trail making B 631.87 ± 25.3 – 1.823 0.077 643.9 ± 25.7 – 2.19 0.03Word association 3.74 ± 3.57 0.367 0.716 3.71 ± 3.44 0.260 0.79

BG, Bender–Gestalt test; MMSE, mini-mental state examination; SD, standard deviation.aComparison of the first year with 3 months (baseline).bComparison of the second year with 3 months (baseline).


of CIND was diagnosed in three cases of stroke group

(CDR = 0.5) and one case of the nonstroke group

between the first-year and the second-year follow-up

interviews. Dementia was diagnosed in five stroke cases

and one nonstroke case. Of these, four stroke cases had

developed a new incidence of dementia (two cases

CDR = 1, one case CDR = 2, one case CDR = 3)

between the first-year and the second-year follow-up

interviews, whereas the other two cases developed

dementia (CDR = 1) at the 2-year follow-up. However,

by the end of the follow-up, the majority of the patients

(25, 70.1%) and (17, 85%) controls were cognitively

stable. Fewer stroke cases than nonstroke cases showed

an improvement from being cognitively impaired at

baseline to being unimpaired at 2 years [19.4% (4/21)

and 25% (1/4), respectively]. Also, 42.8% (6/14) of stroke

cases worsened from being cognitively unimpaired at

baseline to being impaired at 2 years versus 12.5% (2/16)

of nonstroke cases. Table 4 shows that there is impaired

cognitive function in nearly all domains with a significant

difference between stroke and nonstroke groups. Overall

stroke cases declined the most in MMSE, spatial ability,

and in executive function between baseline and the first

and the second year of follow-up with a statistically

significant difference and to a lesser extent in other

domains with no statistically significant difference. There

was also a lack of improvement in attention and nonverbal

memory (Table 5). Nonstroke cases, in contrast, showed

stable performance in all cognitive domains (Table 6).

Table 7 shows that sex was a significant predictor of

executive dysfunction when a multivariate regression

analysis was carried out for significant factors in univariate

analysis. Also, in multivariable analysis, only the age at

stroke onset was independently associated with cognitive

impairment at the second year of follow-up (Table 8).

DiscussionIn the early phase of stroke, a cognitive disorder is usually

related to the direct local effects of the lesion, indicating

that the afflicted brain area is an essential component in

a network subserving that specific cognitive function.

In case of ischemic stroke, these local effects are related

to the core area of the infarct and the ischemic zone

surrounding the infarct, whereas an intracerebral hemor-

rhage usually causes symptoms by exerting pressure on

the surrounding brain tissue. Indirect effects may also

play a role in causing cognitive impairment, such as (a)

‘diaschisis’, in which the lesion cuts off neural input to a

remote area of the brain, causing a dysfunction of that

remote area [8], (b) ‘hypoperfusion’, in which neural

dysfunction is caused by a decreased cerebral blood flow

in case of occlusion of one or more cerebropetal arteries

[26], or (c) neuronal metabolic abnormalities throughout

the entire brain beyond the effects of the stroke lesion

[27]. In patients with stroke, CIND is associated with

disability and a rate of progression to dementia, but its

operational definition is not straightforward.

Table 6 Cognitive change from baseline to the first-year and the second-year follow-up of the nonstroke group

First year Second year

Cognitive ability Mean ± SD t-test Significance Mean ± SD t-test Significance

MMSE 25.75 ± 4.89 – 0.125 0.902 25 ± 5.803 0.656 0.519Verbal memory

Logical memory A, B 17.65 ± 5.9 0.000 1.00 17.00 ± 6.46 0.712 0.485BG (recall) 15.1 ± 4.38 – 0.300 0.768 14.5 ± 4.77 0.487 0.632

Nonverbal memoryVisual reproduction I 3.25 ± 1.12 0.000 1.00 3.1 ± 1.2 0.825 0.419Visual reproduction II 4.20 ± 1.28 0.000 1.00 4.05 ± 1.43 0.616 0.545

Spatial abilityWAIS 89.25 ± 16.1 – 0.240 0.813 87.400 ± 18 6.00 0.556BG (copy) 16 ± 4.78 – 0.000 1.00 15.40 ± 5.18 0.940 0.359

AttentionDigit forward 6.55 ± 1.57 0.000 1.00 6.35 ± 1.76 0.748 0.464Digit backward 3.75 ± 1.52 0.623 0.541 3.55 ± 1.73 1.37 0.186

Executive fugitiveTrail making A 239.8 ± 60.1 1.339 0.739 244.24 ± 60.9 – 0.377 0.710Trail making B 576.9 ± 12.9 – 0.563 0.580 599.21 ± 15.6 – 1.46 0.158Word association 10 ± 2.55 0.092 0.928 9.55 ± 2.98 0.768 0.452

BG, Bender–Gestalt test; MMSE, mini-mental state examination; SD, standard deviation; WAIS, Wechsler adult intelligence scale.

Table 7 Odds ratios of factors predicting executive dysfunction

derived from logistic regression analysis

Variable Odds ratio 95% Confidence interval Significant

Age 0.1 0.79–1.05 0.185Sex 8.89 0.001–21.3 0.05Diagnosis of

hypertension1.86 0.6–68.5 0.122

Site of lesionThalamic 2.29 0.43–226 0.11Lobar 2.123 0.61–181 0.10Basal ganglia 0.02 0.03–28 0.99

Table 8 Predictors of cognitive impairment at the second-year

follow-up: multivariate logistic regression

B SE 95% CI P

Age at stroke onset 0.55 0.26 1.04–2.9 0.03Baseline cognition – 0.91 1.5 0.02–7.8 0.54Site of lesion – 1.6 1.9 0.004–9.18 0.4

B, beta standardized coefficient; CI, confidence interval; SE,standard error.


The main objective of this longitudinal study was to

determine the cognitive evolution over 2 years of patients

with first-ever hemorrhagic stroke. A remarkable finding

of this study is the evidence of multiple evolutionary

trends in the sample. There were patients with stable,

improving, or worsening cognitive status at every evolu-

tionary time frame and in every cognitive stage. In

agreement with this study, the study of Tham et al. [28]

found a 33% overall rate of change from the cognitive

baseline state after a 1-year follow-up both in improving

and deteriorating cases. Several studies have reported

that cognitive impairment after stroke may improve over

time, although the recovery rates were very diverse

because of the different basal characteristics of the

samples. In this study, six patients (19.4%) improved

during the follow-up and, in agreement with previous

reports [29], patients who had dementia showed a high

improvement rate, (13.9%).

Most of our patients with and without cognitive

impairment (70.1%) had stable cognition during follow-

up. Del Ser et al. [4] also found that most of the dementia

and nondementia cases (78.2%) had stable cognition

during follow-up. A neuropsychologic battery exploring

different cognitive domains is an objective and more

reliable tool and therefore all studies on poststroke

cognitive impairment have used this for diagnosis.

However, there is no standard battery validated for this

purpose and every group has selected a different set of

tests and different cutoff points.

Three months after stroke, 60% of our patients with

stroke were classified as CIND. Previous series have

reported a poststroke CIND frequency that ranges

between 35 and 71% [17,28,29]. These different figures

can be explained by differences in the design of

neuropsychological batteries, cutoff values, inclusion–

exclusion criteria (such as exclusion of cases with

previous stroke), and very importantly, the time points

chosen for poststroke baseline. Because most cognitive

recovery occurs within 3 weeks to 3 months after

stroke [30], a short interval for poststroke baseline can

overestimate cognitive impairment.

We found an increased risk of incident dementia at 2

years in patients with stroke who were cognitively

impaired at baseline. Also, a single stroke was strongly

associated with CIND at the first follow-up. A study

carried out by Ballard et al. [31] confirmed our finding.

This suggests that the impact of a single stroke on

dementia is unlikely to be a delayed phenomenon. It is

possible that a single stroke, because of its early cognitive

effects, may lower the threshold for future clinical

expression of preexistent neurodegenerative disease. We

speculate that CIND in patients with stroke is likely to

represent a mixture of the effects of cerebrovascular

disease and neurodegenerative disease, but this requires

further investigation.

In the next 2 years, patients undergo individual changes

but the overall frequency of CIND remains fairly stable.

Del Ser [4] published data on the stability of cognitive

status 2 years after stroke assessed by changes in the

CDR score.

Actual transitions in diagnostic state have been reported

in two hospital-based studies [4,28]. In a Singapore

sample [28], 31% of patients with CIND at 6 months

were cognitively stable at 1 year. High rates of improve-

ment from CIND (44%) and dementia (19%) were also

found at 2 years after stroke in a Spanish study [4].

However, in this study, there is low rates of improvement

from CIND (19%), while there is no improvement from

dementia. Definitional differences may partly explain the

varying results between these studies and our study. Our

criteria of dementia most likely identified people with an

Alzheimer-type dementia, given the primacy of memory

impairment and the requirement for progression. This

therefore constrains the possibility of recovery from

dementia. Also, the small size of our study sample may

explain these results. In addition, as acknowledged by the

Spanish investigators [32], aphasic individuals may have

been misclassified as cases of dementia; thus, improve-

ments in language may have led to a perception of

recovery from dementia. However, we excluded people

with significant aphasia, thus eliminating the possibility

of a misdiagnosis.

Hajat et al. [33] found differences between the subtypes

of hemorrhagic stroke, with a higher prevalence of

hypertension, DM for primary intracerebral hemorrhage,

and higher rates of smoking for subarachnoid hemorrhage.

In agreement with this study, we found a higher

incidence of hypertension and DM among the stroke

group than the nonstroke group.

We found that first-ever hemorrhagic stroke was asso-

ciated with reduced spatial ability, executive function,

and a decline in the MMSE score between baseline and

the first-year follow-up and baseline and the second-year

follow-up. These results are in agreement with another

study [34], in which they found that a single stroke was

associated with reduced spatial ability, attention, and

mental speed. However, executive function impairment

found in our results could be explained by the fact that

mostly our patients had a hematoma in subcortical

structures (basal ganglia and thalamus) and the frontal

lobe. This is in keeping with recent concepts of the

neurobiology of executive functions, which emphasize

the importance of frontal–subcortical circuits [35]. It has

been postulated that the clinical dysexecutive syndromes

observed with frontal lobe injures may also result from

strategic lesions in subcortical components of specific

frontal–subcortical circuits. However, a recent study [36]

assessed cognitive disability changes after hemorrhagic

stroke in 62 patients, with evaluation after 1, 3, and 6

months. It was found that achieved problem solving and

safety and social behavior recovery were lower than those

who showed attention communication and memory

recovery.

There was no relation between the site of hemorrhage

and cognitive functions and this may be because of the

small number of cases.


ConclusionIn this prospective design with high follow-up rates,

cognitive evolution 2 years after hemorrhagic stroke is

different among patients, but a substantial number of

patients remain stable. Additional population-based

studies are required to reliably identify individuals at risk

of cognitive decline for whom pharmacologic or other

therapeutic interventions would be more suitable and those

who will probably show spontaneous improvement. The

determinants of progression of cognitive impairment are

still poorly known. In our sample, age at stroke onset was

found to be a determinant of progression of cognitive

impairment. It was also found in this study that sex can be

considered as a predicting factor for executive dysfunction.

Further Egyptian studies are essential with a larger sample

size. Classification of stroke by etiology may be more useful

for explaining the excess risk of stroke and the scope for its

prevention.


References1 Lloyd Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G,

et al. Heart disease and stroke statistics – 2010 update: a report from theAmerican Heart Association. Circulation 2010; 121:948–954.

2 Adams HPJ, Del Zoppo G, Alberts MJ, Bhatt DL, Brass L, Furlan A, et al.Guidelines for the early management of adults with ischemic stroke: aguideline from the American Heart Association/American Stroke AssociationStroke Council, Clinical Cardiology Council, Cardiovascular Radiology andIntervention Council and the Atherosclerotic Peripheral Vascular Disease andQuality of Care Outcomes in Research Interdisciplinary Working Groups: theAmerican Academy of Neurology affirms the value of this guideline as aneducational tool for neurologists. Stroke 2007; 38:1655–1711.

3 Goldstein LB, Bushnell CD, Adams RJ, Appel LJ, Braun LT, Chaturvedi S,et al. Guidelines for the primary prevention of stroke. A guideline forhealthcare professionals from the American Heart Association/AmericanStroke Association. Stroke 2011; 42 (Suppl 1):s40–s43.

4 Del Ser T, Barba R, Morin MM, Domingo J, Cemillan C, Pondal M, et al.Evolution of cognitive impairment after stroke and risk factors for delayedprogression. Stroke 2005; 36:2670–2675.

5 Hacke W, Donnan G, Fieschi C, Kaste M, Von Kummer R, Broderick JP, et al.Association of outcome with early stroke treatment: pooled analysis ofATLANTIS, ECASS and NINDS rt-PA stroke trials. Lancet 2004; 363:768–774.

6 Stone J, Townend E, Kwan J, Haga K, Dennis MS, Sharpe M. Personalitychange after stroke: some preliminary observations. J Neurol NeurosurgPsychiatry 2004; 75:1708–1713.

7 Bogousslavsky J. William Feinberg lecture 2002: emotions, mood and be-havior after stroke. Stroke 2003; 34:1046–1050.

8 Ferro JM. Hyperacute cognitive stroke syndromes. J Neurol 2001; 248:841–849.

9 Pohjasvaara T, Mantyla R, Ylikoski R, Kaste M, Erkinjuntti T. Comparison ofdifferent clinical criteria (DSM-III, ADDTC, ICD-10, NINDS-AIREN, DSM-IV)for the diagnosis of vascular dementia. National Institute of NeurologicalDisorders and Stroke-Association Internationale pour la Recherche et l’En-seignement en Neurosciences. Stroke 2000; 31:2952–2957.

10 Roman GC. Facts, myths and controversies in vascular dementia. J NeurolSci 2004; 226:49–52.

11 Bowler JV, Hachinski V. Vascular cognitive impairment: a new approach tovascular dementia. Baillieres Clin Neurol 1995; 4:357–376.

12 Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mildcognitive impairment: clinical characterization and outcome. Arch Neurol1999; 56:303–308.

13 Graham JE, Rockwood K, Beattie BL, Eastwood R, Gauthier S, Tuokko H,et al. Prevalence and severity of cognitive impairment with and withoutdementia in an elderly population. Lancet 1997; 349:1793–1796.

14 Sachdev P. Vascular cognitive disorder. Int J Geriatr Psychiatry1999; 14:402–403.

15 Biernaskie J, Chernenko G, Corbett D. Efficacy of rehabilitative experiencedeclines with time after focal ischemic brain injury. J Neurosci 2004; 24:1245–1254.

16 Paolucci S, Antonucci G, Grasso MG, Morelli D, Troisi E, Coiro P, et al. Earlyversus delayed inpatient stroke rehabilitation: a matched comparisonconducted in Italy. Arch Phys Med Rehabil 2000; 81:695–700.

17 Hochstenbach JB, Den Otter R, Mulder TW. Cognitive recovery after stroke:a 2-year follow-up. Arch Phys Med Rehabil 2003; 84:1499–1504.

18 Rasquin SM, Lodder J, Ponds RW, Winkens I, Jolles J, Verhey FR. Cognitivefunctioning after stroke: a one-year follow-up study. Dement Geriatr CognDisord 2004; 18:138–144.

19 Serrano S, Domingo J, Rodriguez Garcia E, Castro MD, Del Ser T.Frequency of cognitive impairment without dementia in patients withstroke: a two-year follow-up study. Stroke 2007; 38:105–110.

20 American Psychiatric Association. Diagnostic and statistical manual ofmental disorders. 4th ed. Washington, DC: American Psychiatric Publisher;2004.

21 Folstein MF, Folstein SE, McHugh PR.‘Mini-mental state’. A practical methodfor grading the cognitive state of patients for the clinician. J Psychiatr Res1975; 12:189–198.

22 Wechsler D, Stone PC. Manual of Wechsler scale. New York: PsychologicalCorporation; 1995.

23 Reitan RM. Validity of the trail making test as an indicator of organic braindamage. Percept Mot Skills 1958; 8:271–276.

24 Wechsler D. The measurement of intelligence. 3rd ed. The psychologicalcorporation, New York: Williams & Wilkins Company; 1981.

25 Morris JC. The Clinical dementia rating (CDR): current version andscoring rules. Neurology 1993; 43:2412–2414.

26 Hillis AE, Barker PB, Wityk RJ, Aldrich EM, Restrepo L, Breese EL, et al.Variability in subcortical aphasia is due to variable sites of corticalhypoperfusion. Brain Lang 2004; 89:524–530.

27 Van Zandvoort MJ, Van der Grond J, Kappelle LJ, De Haan EH. Cognitivedeficits and changes in neurometabolites after a lacunar infarct. J Neurol2005; 252:183–190.

28 Tham W, Auchus AP, Thong M, Goh ML, Chang HM, Wong MC, et al.Progression of cognitive impairment after stroke: one year results from alongitudinal study of Singaporean stroke patients. J Neurol Sci2002; 203–204:49–52.

29 Desmond DW, Moroney JT, Sano M, Stern Y. Recovery of cognitive functionafter stroke. Stroke 1996; 27:1798–1803.

30 Schmidt R, Mechtler L, Kinkel PR, Fazekas F, Kinkel WR, Freidl W. Cognitiveimpairment after acute supratentorial stroke: a 6-month follow-up clinicaland computed tomographic study. Eur Arch Psychiatry Clin Neurosci1993; 243:11–15.

31 Ballard C, Rowan E, Stephens S, Kalaria R, Kenny RA. Prospective follow-upstudy between 3 and 15 months after stroke: improvements and decline incognitive function among dementia-free stroke survivors 475 years of age.Stroke 2003; 34:2440–2444.

32 Srikanth VK, Thrift AG, Saling MM, Anderson JF, Dewey HM, Macdonell RA,et al. Increased risk of cognitive impairment 3 months after mild to moderatefirst-ever stroke: a community-based prospective study of nonaphasicEnglish-speaking survivors. Stroke 2003; 34:1136–1143.

33 Hajat C, Dundas R, Stewart JA, Lawrence E, Rudd AG, Howard R, et al.Cerebrovascular risk factors and stroke subtypes: differences betweenethnic groups. Stroke 2001; 32:37–42.

34 Srikanth VK, Quinn SJ, Donnan GA, Saling MM, Thrift AG. Long-term cog-nitive transitions, rates of cognitive change and predictors of incidentdementia in a population-based first-ever stroke cohort. Stroke 2006; 37:2479–2483.

35 Tekin S, Cummings JL. Frontal-subcortical neuronal circuits and clinicalneuropsychiatry: an update. J Psychosom Res 2002; 53:647–654.

36 Oh H, Seo W. Changes in the acute functional and cognitive disabilitystates of severe hemorrhagic stroke patients. J Neurosci Nurs 2010; 42:245–254.


Characteristics of substance dependence in adolescents with

and without a history of traumaHosam El-Sawy and Mohamed Abd Elhay

Department of Neuropsychiatry, Faculty of Medicine,Tanta University, Egypt

Correspondence to Hosam El-Sawy, AssistantProfessor of Neuropsychiatry, Faculty of Medicine,Tanta University, EgyptTel: + 20127904167;e-mail: [email protected]

Received 1 January 2011Accepted 13 March 2011


2011, 18:211–216

Background

Numerous studies have documented a strong correlation between trauma exposure

and substance abuse in young people. The link between trauma and substance abuse

is even more striking among adolescents with posttraumatic stress disorder (PTSD).

Aim of the study

The aim of this study was to address the characteristics of substance dependence and

comorbid psychiatric disorders in adolescents with and without a history of trauma

(physical or sexual) and in a subgroup that had posttraumatic stress disorder.

Methodology

A total of 78 adolescents aged between 12 and 17 years who attended the drug

dependence clinic at the Neuropsychiatry center, Tanta University, were classified

according to the Childhood Trauma Questionnaire into 29 without a history of trauma,

15 with PTSD, and 34 with a history of trauma without PTSD. All groups were

assessed as regards onset of drug use, number of substances used, motives for use,

attempts for abstinence, and comorbid psychiatric disorders using The MINI

International Neuropsychiatric Interview.

Results

It was found that adolescents exposed to trauma had early onset of drug abuse and

were more likely to use tramadol, followed by cannabis and benzodiazepines. They

have a tendency to polysubstance abuse compared with others. The primary reasons

for drug abuse in trauma patients were coping with stress and enhancement of

self-esteem, whereas it was social pressure in others and they made less attempts

at abstinence. Anxiety disorders and psychotic disorders were more common in the

PTSD group.

Conclusion

Adolescent substance abuse is common among children with sexual or physical

trauma and needs careful attention to minimize comorbid psychiatric disorders.

Keywords:

adolescents, physical and sexual trauma, substance dependence, posttraumatic stress

disorder


IntroductionNumerous studies have documented a strong correlation

between trauma exposure and substance abuse in young

people. A recent survey of adolescents revealed that

teens who had experienced physical or sexual abuse/

assault were three times more likely to report past or

current substance abuse than those without a history of

trauma [1]. Surveys of adolescents receiving treatment

for substance abuse have shown that more than 70% had

a history of trauma exposure [2,3]. The link between

trauma and substance abuse is even more striking among

adolescents with posttraumatic stress disorder (PTSD).

Studies indicated that up to 59% of young people with

PTSD subsequently develop problems related to sub-

stance abuse [3–6].

Many researchers and providers point to the self-

medication hypothesis to explain the connection between

trauma exposure and substance abuse, suggesting that

youth resort to psychoactive drugs and alcohol in an

attempt to cope with traumatic stress or reminders of loss.

Although there is a lot of evidence to support this pathway,

studies evaluating the frequency of substance abuse after

trauma exposure have reported rates as high as 76% [6–9].

It is also true that substance abuse can increase an

adolescent’s risk of trauma exposure and of experiencing

traumatic stress symptoms.

Successful treatment of adolescents with co-occurring

traumatic stress and substance abuse therefore requires

interventions that address the challenges of both dis-

orders. Failure to provide such comprehensive treatments

may significantly impair these teenagers’ likelihood of

long-term recovery. In the absence of coping strategies to

manage distress associated with trauma, adolescents with

co-occurring disorders are more likely to relapse and

revert to maladaptive coping strategies than are teenagers



with substance abuse alone [10]. There are very few

studies in Egypt that have investigated the characteristics

of substance dependence in adolescents with a history of

trauma [11]. The aim of this study was to address the

characteristics of substance dependence and comorbid

psychiatric disorders in adolescents with and without a

history of trauma (physical or sexual) and in a subgroup

that had PTSD.

MethodologyThe study included all adolescent substance dependants

whose ages ranged between 12 and 17 years and who were

being treated at the Drug dependence Outpatient Clinic

of Psychiatry, Neurology and Neurosurgery Center, Tanta

University, from October 2009 to November 2010. They

were diagnosed according to Diagnostic and StatisticalManual of Mental Disorders Fourth Edition [12] diagnostic

criteria for drug dependence and administered a Child-

hood Trauma Questionnaire (CTQ). The Childhood

Trauma Questionnaire is a 28-item self-report retro-

spective inventory that measures childhood or adolescent

abuse and neglect. It is straightforward and easy to use.

The CTQ can be administered individually or to a group.

The examinee responds to 28 simple questions on a 5-

point scale ranging from Never True to Very Often True.

The central constructs underlying the questionnaire are

emotional, physical neglect and abuse, and sexual abuse.

Other traumatic events that may occur during childhood,

such as the death of a parent or a major illness, are not

assessed. The items are written at a sixth grade reading

level, and reading level and intellectual functioning

should be assessed before administering the scale (by

Wechsler Adult Intelligence Test by Mleka 2000) [13,14].

The measure also includes a three-item Minimization/

Denial scale indicating the potential underreporting of

maltreatment. Participants respond to each item in the

context of ‘when you were growing up’ and answer

according to a 5-point Likert scale ranging from ‘never’ =

1 to ‘very often’ = 5, producing scores of 5–25 for each

trauma subscale. The three items comprising the

Minimization/Denial scale are dichotomized (‘never’ = 0,

all other responses = 1) and summed; a total of one [1] or

greater suggests the possible underreporting of maltreat-

ment (false negatives). Participants were divided into

three groups: group I comprised adolescents with

substance dependence without a history of trauma; group

II comprised adolescents with a history of trauma with

PTSD (current or past); and group III comprised

adolescents with a history of trauma without posttrau-

matic stress disorder. All participants were assessed with

regard to onset of drug use, number of substances used,

motives for use, attempts at abstinence, and comorbid

psychiatric disorders using The MINI International

Neuropsychiatric Interview. This interview was trans-

lated and validated into Arabic by Ghanem et al. [15,16].

Written consent was taken from all patients and controls

after they were informed of all the steps and aims of

the study.

Statistical analysis

The collected data were organized and statistically

analyzed using the 15 Minitabe software [17] statistical

computer package. Mean and standard deviations were

used for presentations of quantitative data. The differ-

ences with regard to psychiatric disorders were analyzed

using a multivariate analysis of variance. The Student

t-test was used for comparison between two means. The

w2 test and the Fischer exact test were used for comparison

between the studied groups. A 5% level of significance

was adopted for interpretations of tests of significance.

ResultsDuring the study period, 78 adolescents with substance

dependence whose ages ranged between 12 and 17 years

were interviewed. Of them, 29 (37%) reported no trauma

(physical or sexual) during childhood and were termed

group I; 49 (63%) reported trauma (physical, sexual, or

both) and were further divided into group II (15 patients,

19%; those who developed PTSD) and group III (34

patients, 44%; those without PTSD). There was no

significant statistical difference among the studied groups

as regards age or sex (P 40.05), although there were

more female patients in trauma groups II and III (33;

32%) than in group I (18%). Early onset of substance

dependence was significantly more in groups II and III

than in group I, but there was no significant difference

between groups II and III. The CTQ showed signifi-

cantly higher scores in the physical trauma subscale in

patients with PTSD (Po0.05), but no significant

differences were found between the two groups on the

sexual trauma subscale (P40.05) (Table 1).

Characteristics of substance used in the studied groups

It was found that all patients had a tendency to

polysubstance abuse. In group I, 41% used more than

two drugs in comparison with 53% in group II and 50% in

group III. The difference was not statistically significant

(P40.05). In addition, 44% in group I, 40% in group II,

and 41% in group III used two drugs. Only a minority

used only one drug in the three groups (15% in group I,

7% in group II, and 9% in group III). The difference was

not significant (P40.05) (Table 2).

Tramadol was the most commonly used drug by groups II

and III (93 and 94%, respectively), followed by cannabis

(93 and79%, respectively), opiates (60 and 47%, respec-

tively), and benzodiazepines (13 and 20%, respectively).

Cannabis was the most commonly used drug by group I

(82%), followed by Tramadol (65%), opiates (41%), and

benzodiazepines (17%). Other substances include antic-

holinergics, inhalants, and barbiturates and were used by

37% of group I, 33% of group II, and 44% of group III.

The difference was not statistically significant (P40.05)

(Table 2). Nicotine was excluded as it was used by all

patients.

Social pressure was the most important motive for

substance use in group I (44%), which was statistically

significant compared with groups II and III (7 and 6%,


respectively). Curiosity also was the motive for 28% in

group I, which was not significant in relation to 20 and

11% in groups II and III, respectively. In contrast, coping

with stress was the most important motive for substance

use in patients with PTSD (93%) and in trauma patients

without PTSD (79%), followed by enhancement of self-

esteem (53% in group II and 30% in group III). The

difference between both groups of trauma patients was

statistically significant (Po0.05) (Table 2).

Patients without trauma (group I) showed more sig-

nificant attempts at abstinence than those who had

undergone trauma (Po0.05) (Table 2).

Anxiety disorders (other than PTSD) comprised the most

common comorbidity among group II (67%) patients in

comparison with group III (41%) and group I (20%)

(Po0.05). Psychotic disorders as comorbid disorders

were found in a small percentage in the three groups

Table 1 Demographic data of the patients

VariableGroup I patients without

trauma N = 29Group II patients with trauma

(with PTSD) N = 15Group III traumatic patients

(without PTSD) N = 34

Age:(Years)Range 12–17 12-17 12–17 F = 0.17

P = 0.846Mean 14.51 14.20 14.38SD ± 1.76 1.74 1.70

SexMales 24 (82%) 10 (67%) 23 (68%) X = 2.204Females 5 (18%) 5 (33%) 11 (32%) P = 0.332

Duration of substance use: (months) F = 8.74P = 0.00a

Range 12–48 12–60 12–59 T1 = – 3.12P = 0.005a

Mean 25.03 38.80 37.32 T2 = – 3.93P = 0.000a

SD ± 11.32 15.02 13.53 T3 = 0.33P = 0.747

CTQ physical scores: T = 4.43P = 0.000aRange 10–17 6–14

Mean 12.67 9.79SD ± 2.16 1.93

CTQ sexual scores:Range 5–16 5–18 T = 1.52

P = 0.140Mean 9.93 11.35SD ± 2.89 3.29

CTQ, Childhood Trauma Questionnaire; PTSD, posttraumatic stress disorder; SD, standard deviation.aSignificant T1 (Group I vs. II). T2 (Group I vs. III). T3 (Group II vs. III).

Table 2 Characteristics of drug dependence in the studied patients

VariableGroup I patients without

trauma N = 29Group II patients with trauma

(with PTSD) N = 15Group III traumatic patients

(without PTSD) N = 34

Number of drug usedMore than two 12 (41%) 8 (53%) 17 (50%) P = 0.900Only two 13 (44%) 6 (40%) 14 (41%)Only one drug 4 (15%) 1 (7%) 3 (9%)

Type of drugTramadol 19 (65%) 14 (93%) 32 (94%) P = 0.005a

Cannabis 24 (82%) 14 (93%) 27 (79%) P = 0.481Opiates 12 (41%) 9 (60%) 16 (47%) P = 0.502Benzodiazepines 5 (17%) 2 (13%) 7 (20%) P = 0.824Others 11 (37%) 5 (33%) 15 (44%) P = 0.752

Motives for useSocial pressure 13 (44%) 1 (7%) 2 (6%) P = 0.000a

Curiosity 8 (28%) 3 (20%) 4 (11%) P = 0.282Enhancement of self-esteem 2 (7%) 8 (53%) 10 (30%) P = 0.003a

Coping with stress 1 (3%) 14 (93%) 27 (79%) P = 0.000a

Others 5 (18%) 2 (13%) 4 (11%) P = 0.820Attempts at abstinence

Yes 12 (41%) 3 (20%) 5 (14%) P = 0.046a

No 17 (95%) 12 (80%) 29 (86%)Comorbid psychiatric disorders

Depressive disorders 8 (28%) 7 (47%) 15 (44%) P = 0.311Anxiety disorders (other than PTSD0 6 (20%) 10 (67%) 14 (41%) P = 0.011a

Psychotic disorders 2 (7%) 1 (7%) 3 (9%) P = 0.947

PTSD, posttraumatic stress disorder.aSignificant o0.05 calculated by Fischer’s exact test.

Characteristics of substance dependence in adolescents El-Sawy and Abd Elhay 213

(7, 7, and 9%, respectively) but were definitely more but

not significant in the PTSD group (P40.05). No

significant difference was found among the three groups

as regards depressive disorders (P40.05).

DiscussionMuch research has been devoted in identifying the

common risks and protective factors associated with

adolescent substance use. In general, teenagers are less

likely to succumb to external pressure toward drug use if

they have a strong sense of attachment to parents who

clearly communicate their disapproval of substance use

and antisocial behaviors [18–20] and who have a strong

commitment to doing well in school. Conversely,

associating with substance-abusing peers and limited

availability of educational and recreational opportunities

are associated with increased risk of substance

abuse [21,22]. In this study, we tried to identify the

difference between those who were exposed to trauma

and other adolescents without exposure to trauma.

We found that there were more male patients than female

patients in both groups with no difference between them.

Sex is an important factor in the use and effects of alcohol

and other drugs of abuse. Our explanation is that boys

tend to have opportunities for use earlier in life and thus

tend to start at younger ages [23]. However, once girls

have the opportunity to experiment, they are just as likely

as boys to use drugs of abuse [24]. Rates of drug use for

both sexes have been converging over the past decade.

Research indicates that there are few differences in the

type or amount of substances that male and female

adolescents use; however, the effects of substances on

their emotional and physiological health can vary. Others

have indicated that substance abuse stemming from

traumatic events and/or psychological problems is more

common in female patients than in male patients. In

addition, female substance abusers are more vulnerable to

some of the physiological effects and psychological

difficulties that can result from substance use [25].

In this study, it was found that onset of drug abuse is

earlier in patients with trauma than in patients without

trauma. Trauma has been shown to adversely affect many

of the neurobiological systems responsible for cognitive

development and regulation of emotions and behavior. In

adolescents, this can manifest in delays in the develop-

mental processes that would normally enable them to

effectively evaluate the consequences of their behavior,

to make realistic appraisals for danger and safety, to

moderate daily behavior to meet long-term goals, and to

make increased use of abstract thinking for academic

learning and problem solving. Harley et al. [26] found that

childhood trauma leads to very early cannabis use, which

agrees with our results. Trauma at an early age leads to

emotional and cognitive disturbances that may enhance

early substance use in such adolescents.

Although the traumatic group seems to be polysubstance

abusers compared with the nontraumatic group, the

difference was not significant in this study. Patients with

a history of trauma may use more than one substance to

self-medicate themselves and achieve homeostasis [27].

In addition, they were found to use tramadol and

cannabis as the main substances. Harley et al. [26] found

a close association of childhood trauma with early

cannabis use, and they found that such clear association

may help the appearance of psychosis in such patients.

Johnson et al. [28] reported that early onset of marijuana

and heroin use, alcohol dependence, and opiate depen-

dence was associated with exposure to a traumatic event

for male substance abusers, and early onset of alcohol use

and alcohol dependence was associated with exposure to

a traumatic event for female substance users. Tramadol is

one of the analgesics that is abused heavily in Egypt and

many adolescents use it because of its easy availability

and low cost. The abuse of prescription painkillers has

risen markedly. According to emergency department data

USA, in 2005 nearly 50 000 youth between the ages of 12

and 17 years presented to the emergency department

because of nonmedical uses of prescription painkillers. An

estimated 14% of high school seniors have used prescrip-

tion drugs for nonmedical reasons at least once in their

lifetime, making prescription drugs the second most

commonly abused illegal substance by teenagers, after

marijuana [29].

On studying the motives for drug abuse in both groups in

this study, patients with a history of trauma abuse

substances as a method of coping with stress and for

enhancement of self-esteem, whereas others abuse drugs

under social pressure. Understanding the reasons why

youth start using drugs or alcohol – as well as their reasons

for continuing or discontinuing use – is crucial to deve-

loping effective substance abuse interventions. Similar

results found in a recent 30-month study of 923 teenagers

receiving outpatient and residential substance abuse

treatment have provided some insight into the motiva-

tions behind adolescents’ substance abuse and eventual

recovery [30]. In this study, three quarters of the teen-

agers cited social pressure and experimentation as their

reasons for initiating drug or alcohol use. Teenagers may

start using drugs or alcohol because they see ‘every one

else’ doing it and want to blend in, because it is a way of

spending time with friends, of being accepted, of

becoming popular, of enhancing social and other activ-

ities, or because they fear that if they refuse they might

alienate potential friends. Many adolescents reported

that curiosity led to first use, whereas others reported

that they decided to start after witnessing use by a parent

or relative. Of note, only 7% reported initiating use to

‘cope with difficulties’ [30].

Many researchers and providers point to the self-medica-

tion hypothesis to explain the connection between trauma

exposure and substance abuse, suggesting that youth turn

to psychoactive drugs and alcohol in an attempt to cope

with traumatic stress or reminders of loss.

In our study, traumatic patients with and without

PTSD had less tendency for abstinence. It is likely that,

for teenagers experiencing traumatic stress, continued

substance use may serve as a coping strategy to deal with


stress, forget unpleasant experiences, avoid negative

emotions, do away with worries, or feel numb or

indifferent to the challenges of daily life or of reminders

of past trauma [31].

Comorbid psychiatric disorders were investigated in this

study. Anxiety disorders were found to be common

associations in traumatic groups, whereas depression

was the most common in the nontraumatic group.

Patients with PTSD are more prone to psychosis.

Epidemiological studies have consistently reported a high

rate of comorbid mental health problems among adoles-

cents with substance use disorders [32]. In all, 32% of

adolescents with current substance abuse had co-

occurring mood disorders [33]. Increased suicide at-

tempts were also found in adolescents with co-occurring

substance use disorders and mood disorders [34]. Anxiety

disorders, especially panic and social phobia, are common

in adolescent substance abusers associated with a history

of trauma [35]. Adolescents with PTSD are very common

and have higher comorbid mental health and used more

drugs in their life time [36]. A high prevalence of

cannabis use among those patients explains the estab-

lished psychotic disorders observed [36].

Limitation of the study

The Questionnaire for trauma, although commonly used

in many cultures, was not standardized to the Egyptian

culture.

ConclusionEarly physical or sexual trauma has considerable impact

on adolescents’ drug dependence and needs careful

investigation to address their coping abilities and evaluate

effective strategies for their treatment.


References1 Kilpatrick DG, Saunders BE, Smith DW. Youth victimization: prevalence and

implications. Washington, DC: U.S. Department of Justice, Office of JusticePrograms, National Institute of Justice; 2003.

2 Funk RR, McDermeit M, Godley SH, Adams L. Maltreatment issues by levelof adolescent substance abuse treatment: the extent of the problem at intakeand relationship to early outcomes. Child Maltreat 2003; 8:36–45.

3 Deykin EY, Buka SL. Prevalence and risk factors for posttraumatic stressdisorder among chemically dependent adolescents. Am J Psychiatry1997; 154:752–757.

4 Clark DB, Lesnick L, Hegedus AM. Traumas and other adverse life events inadolescents with alcohol abuse and dependence. J Am Acad Child AdolescPsychiatry 1997; 36:1744–1751.

5 Giaconia RM, Reinherz HZ, Hauf AC, Paradis AD, Wasserman MS, Lan-ghammer DM. Comorbidity of substance use and post-traumatic stressdisorders in a community sample of adolescents. Am J Orthopsychiatry2000; 70:253–262.

6 Perkonigg A, Kessler RC, Storz S, Wittchen HU. Traumatic events and post-traumatic stress disorder in the community: prevalence, risk factors andcomorbidity. Acta Psychiatr Scand 2000; 101:46–59.

7 De Bellis MD, Narasimhan A, Thatcher DL, Keshavan MS, Soloff P, Clark DB.Prefrontal cortex, thalamus and cerebellar volumes in adolescents and youngadults with adolescent-onset alcohol use disorders and comorbid mentaldisorders. Alcohol Clin Exp Res 2005; 29:1590–1600.

8 Zeigler DW, Wang CC, Yoast RA, Dickinson BD, McCaffree MA, RobinowitzCB, et al. The neurocognitive effects of alcohol on adolescents and collegestudents. Prev Med 2005; 40:23–32.

9 Diamond G, Panichelli Mindel SM, Shera D, Dennis M, Tims F, Ungemack J.Psychiatric syndromes in adolescents with marijuana abuse and dependencyin outpatient treatment. J Child Adolesc Substance Abuse 2006; 15:37–54.

10 Titus JC, Dennis ML, White WL, Scott CK, Funk RR. Gender differences invictimization severity and outcomes among adolescents treated forsubstance abuse. Child Maltreat 2003; 8:19–35.

11 Okasha A, Khalil A, Fahmy M. Psychological understanding of Egyptianheroin users. Egypt J Psychiatry 1999; 13:37–49.

12 American Psychiatric Association. Diagnostic and statistical manual ofmental disorders. 4th ed. American Psychiatric Pub; 2000.

13 Bernstein DP, Fink L, Handelsman L, Foote J, Lovejoy M, Wenzel K, et al.Initial reliability and validity of a new retrospective measure of child abuseand neglect. Am J Psychiatry 1994; 151:1132–1136.

14 Bernstein DP, Ahluvalia T, Pogge D, Handelsman L. Validity of the childhoodtrauma questionnaire in an adolescent psychiatric population. J Am AcadChild Adolesc Psychiatry 1997; 36:340–348.

15 Ghanem MH, Beheri AA, El-Marghany A, Ebrahim M, Abd-El-Hakam Z,Aly AF, Ebrahim A. Development and validation of the Arabic version of theMini International Neuropsychiatry Interview (MINI). The Annual InternationalConference of the Egyptian Psychiatric Association Cairo, Egypt; 1999.

16 Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al.The Mini-International Neuropsychiatric Interview (M.I.N.I.): The developmentand validation of a structured diagnostic psychiatric interview for DSM-IV andICD-10. J Clin Psychiatry 1998; 59 (Suppl) 2022–33;quiz:34-57.

17 Minitab Inc. Minitab introduces statistical mentoring for quality improvement.Pennsylvania: State College, Pa; 2006.

18 Kostelecky KL. Parental attachment, academic achievement, life events andtheir relationship to alcohol and drug use during adolescence. J Adolesc2005; 28:665–669.

19 Bahr SJ, Hoffmann JP, Yang X. Parental and peer influences on the risk ofadolescent drug use. J Prim Prev 2005; 26:529–551.

20 Herrenkohl TI, Tajima EA, Whitney SD, Huang B. Protection against antisocialbehavior in children exposed to physically abusive discipline. J AdolescHealth 2005; 36:457–465.

21 McIntosh J, MacDonald F, McKeganey N. The reasons why children in theirpre and early teenage years do or do not use illegal drugs. Int J Drug Policy2005; 16:254–261.

22 Deas D. Adolescent substance abuse and psychiatric comorbidities. J ClinPsychiatry 2006; 67 (Suppl) 718–23.

23 Van Etten ML, Neumark YD, Anthony JC. Male-female differences in theearliest stages of drug involvement. Addiction 1999; 94:1413–1419.

24 Van Etten ML, Anthony JC. Male-female differences in transitions from first drugopportunity to first use: Searching for subgroup variation by age, race, regionand urban status. J Womens Health Gend Based Med 2001; 10:797–804.

25 Wallace JM. Jr, Bachman JG, O’Malley PM, Schulenberg JE, Cooper SM,Johnston LD. Gender and ethnic differences in smoking, drinking and illicitdrug use among American 8th, 10th and 12th grade students, 1976–2000.Addiction 2003; 98:225–234.

26 Harley M, Kelleher I, Clarke M, Lynch F, Arseneault L, Connor D, et al.Cannabis use and childhood trauma interact additively to increase therisk of psychotic symptoms in adolescence. Psychol Med 2010; 40:1627–1634.

27 Kuntsche E, Jordan MD. Adolescent alcohol and cannabis use in relation topeer and school factors. Results of multilevel analyses. Drug Alcohol Depend2006; 84:167–174.

28 Johnson SD, Striley C, Cottler LB. The association of substance use dis-orders with trauma exposure and PTSD among African American drug users.Addict Behav 2006; 31:2063–2073.

29 Substance Abuse and Mental Health Services Administration. Results fromthe 2006 National Survey on Drug Use and Health: National findings.Department of Health and Human Services; 2008.

30 Titus JC, Godley SH, White MK. A post-treatment examination of adoles-cents’ reasons for starting, quitting and continuing the use of drugs andalcohol. J Child Adolesc Substance Abuse 2007; 16:31–49.

31 Hovens JG, Cantwell DP, Kiriakos R. Psychiatric comorbidity in hospitalizedadolescent substance abusers. J Am Acad Child Adolesc Psychiatry1994; 33:476–483.

32 Rowe CL, Liddle HA, Greenbaum PE, Henderson CE. Impact of psychiatriccomorbidity on treatment of adolescent drug abusers. J Subst Abuse Treat2004; 26:129–140.

33 Grella CE, Hser YI, Joshi V, Rounds Bryant J. Drug treatment outcomes foradolescents with comorbid mental and substance use disorders. J NervMent Dis 2001; 189:384–392.

34 King RD, Gaines LS, Lambert EW, Summerfelt WT, Bickman L. The co-occurrence of psychiatric and substance use diagnoses in adolescents indifferent service systems: frequency, recognition, cost and outcomes.J Behav Health Serv Res 2000; 27:417–430.

35 Riggs PD, Davies RD. A clinical approach to integrating treatment for ado-lescent depression and substance abuse. J Am Acad Child Adolesc Psy-chiatry.41:; 2002. pp. 1253–1255.

36 Deas D, Thomas SE. An overview of controlled studies of adolescent sub-stance abuse treatment. Am J Addict 2001; 10:178–189.

Characteristics of substance dependence in adolescents El-Sawy and Abd Elhay 215

Duration of untreated psychosis in two Arab samples from

Egypt and Saudi Arabia: Clinical and sociocultural correlatesMohab M. Fawzia, Hany M. El-Aminb and Mounir H. Fawzia

aDepartment of Psychiatry, Faculty of Medicine,Zagazig University, Zagazig, Egypt andbConsultant Psychiatrist, Erfan Psychiatric Hospital,Jeddah, Saudi Arabia

Correspondence to Mohab M. Fawzi, Faculty ofMedicine, Zagazig University, Zagazig, EgyptTel: + 161366617; fax: +20552338972;e-mail: [email protected]

Received 11 April 2011Accepted 6 June 2011


2011, 18:217–225

Background

The duration of untreated psychosis (DUP) varies considerably across different cultures

and settings. However, cross-cultural studies have mostly been either comparisons

between developed and developing countries or comparisons between different ethnic

groups in unicultural investigations. Studies comparing more socioculturally related

countries, such as Arab countries, are required. To the best of our knowledge, no

previous studies have compared DUP between Egypt and Saudi Arabia.

Aims

The aims of the study are to determine DUP in two samples of patients with first-

episode psychosis from Egypt and Saudi Arabia; to explore the sociodemographic,

clinical, and help-seeking characteristics that are associated with DUP in these two

groups; to distinguish which of these sociodemographic, clinical and help-seeking

correlates the DUP are shared by Egyptian and Saudi Arabian patient groups and

which are more culture specific; and to test the hypothesis that severity of illness

predicts the length of DUP.

Methods

A total of 96 (50 from Egypt and 46 from Saudi Arabia) consecutive attendees at two

outpatient clinics with first-episode psychosis were assessed by semistructured

interviews. In addition to the determination of DUP and help-seeking contacts, patients

were assessed by the Positive and Negative Syndrome Scale.

Results

The mean DUP was 3.2 and 3.1 years for the Egyptian and Saudi Arabian patient

groups, respectively. There were no significant differences between the two groups

with regard to most of the variables studied. Variables that significantly correlated with

DUP were entered into multiple regression analyses. The final model, which accounted

for 56.9% of the variance in DUP, included only two variables: ‘first contact’ and ‘mode

of onset’.

Conclusion

In the two countries, patients with first-episode psychosis were found to have long

DUP. First contact with a traditional (faith) healer and insidious mode of onset of

psychosis were the two significant predictors of long DUP. Although severity of

negative symptoms, as indicated by Positive and Negative Syndrome Scale negative

subscale scores, was correlated with DUP, it could not be retained in the final

regression model as a significant predictor. Our hypothesis that severity of illness

predicts long DUP had to be rejected. Factors found to influence DUP should be taken

into account in early intervention initiatives.

Keywords:

duration of untreated psychosis, Egypt, first-episode psychosis, help-seeking, Positive

and Negative Syndrome Scale, Saudi Arabia, traditional (faith) healer


Introduction

The duration of untreated psychosis (DUP), which

represents the delay in initiation of treatment, is a

concept of paramount importance in schizophrenia

research, at least from the point of view of secondary

prevention. Its importance began to be appreciated in the

mid 1980s when the Northwick Park Study of first-

episode schizophrenia found that the most important

determinant of relapse was the duration of illness before

starting antipsychotics [1]. Interest in the topic has

increased even more in recent years, with a growing sense

of optimism derived from the understanding that

attention to the early phases of illness could result in a

substantial reduction in morbidity and lead to a better

quality of life. Moreover, although there is some

controversy about whether long DUP is associated with

poor outcome, the weight of evidence supports an

association that, although not strong, is persistent; for

example, [2–5]. Thus, in a systematic review of literature,



Marshall et al. [6] concluded that there is convincing

evidence of an association, albeit small to moderate,

between DUP and outcome. Similarly, literature review in

low and middleincome countries by Farooq et al. [7]

showed that the lack of treatment for psychotic illness

early in its course is associated with poor outcomes,

irrespective of the income or cultural status of the

setting. Long DUP was frequently reported to be

associated with increased mortality and poor prog-

nosis [8,9]. The relationship between DUP and 1-year

outcome, as demonstrated by two large studies from

UK [10] and Australia [11], is curvilinear, with greater

improvement in outcome if DUP is reduced from 6 to 3

weeks compared with reduction from 6 to 3 months. In

other words, the maximum benefit of early intervention

services will be obtained only by shifting patients to the

shortest part of the DUP range.

However, the mechanism by which long DUP might lead

to poor outcome is still uncertain. It has been postulated

that a long DUP might lead to neurotoxic processes,

manifested as persistent morbidity, treatment resistance,

and symptom worsening [12], and that there is a critical

period, postulated to be up to 5 years from the onset of

psychosis, for intervention before psychosis can be

established [13,14]. Biological mechanisms involving

dopaminergic and glutamatergic processes have also been

suggested to explain how prolonged active psychosis will

result in treatment refractoriness. Recently, neuroimaging

studies have demonstrated reductions in hippocampus

volume [15] and temporal gray matter [16] in patients

with long DUP. These findings could reflect a progressive

pathological process that is active before treatment. In

contrast, these abnormalities could be associated with a

more insidious onset of illness and a later presentation to

services. Thus, possible explanatory mechanisms would

also include psychosocial processes, with prolonged

untreated psychosis increasingly producing psychological

and social dysfunction.

In an attempt to reduce DUP, many countries have

implemented early intervention programs [17–19] as a

target for secondary preventive efforts [20]. The aim of

these programs is not limited to the reduction of DUP to

improve outcome; they also attempt to promote recovery

through the evidence-based use of drug treatments,

cognitive behavioral therapies, and family interventions,

provided in a setting specifically designed to be

accessible and nonstigmatizing. Although some studies

indicate that specialized early psychosis intervention

programs can deliver a higher recovery rate and at a cost

lower than that of standard public mental health

services [21,22], other studies suggest that improvement

in outcome is not as promising as hoped [23]. Addressing

factors that have a strong influence on DUP and that are

also changeable is important. This may be a key for the

success of any program attempting to reduce potentially

deleterious treatment delays [24].

Data on treatment delay in psychosis, however, are still

rather limited, especially from developing countries.

Most available studies indicate that DUP has an average

of approximately 1–2 years [25]. It is noted that DUP

varies considerably across different cultures and set-

tings [25]. Thus, although DUP was found by Oliveira

et al. [26] in Sao Paulo (Brazil) to be shorter than

expected, with a mean of only 4.1 weeks, Nishii et al. [27]

found that the mean of DUP in three cities in Japan

(Tokyo, Toyama, and Kochi) was relatively long (20.3

months), and Haas and Sweeney [28] in New York (USA)

found DUP to have a mean as long as 3 years. Our own

pilot study in Zagazig (Egypt) that we reported in

2005 [29] found a still longer duration with a mean of

3.1 years.

Although the earliest manifestations of psychosis may be

universal, the impact of individual, familial, social, and

health service-related factors on psychiatric help-seeking

behavior might vary according to different cultural

contexts [25], and, although cross-cultural data on

incidence and prevalence, rates of admission, psycho-

pathological aspects, symptoms, course, and outcome are

available [30,31], formal studies on DUP-related factors

in different cultures are hard to find. Cross-cultural

studies on the characteristics of the early course of

psychosis and pathways to psychiatric care have mostly

tended to be either comparisons between developed and

developing countries [32] or unicultural studies that have

examined the differences between different ethnic

groups in one country [33,34]. Thus, data from studies

comparing more socioculturally related countries, for

example, studies between Arab countries, are required.

Although both Egypt and Saudi Arabia represent Arab

countries, there are many differences between them in

terms of religious affiliation, level of secularism, level of

democracy, and economic status [35]. These differences

may have an influence on the factors associated with

delay in treatment seeking. However, no previous studies,

to the best of our knowledge, have compared DUP

between these two countries.

Our aims in this study were to determine the DUP length

in two samples of patients, from Egypt and Saudi Arabia,

with first-episode psychosis, who had received no

previous psychiatric treatment; to explore the socio-

demographic, clinical, and help-seeking characteristics

that are associated with DUP in these two groups;

to distinguish which of these sociodemographic, clinical

and help-seeking correlates of DUP are shared by

Egyptian and Saudi patient groups and which are more

culture specific, and (4) to find out whether severity of

illness would predict the length of DUP at presentation.

The null hypothesis (H0) is that no significant correlation

would exist between severity of illness and length of

DUP. The alternative hypothesis (H1) is that a significant

correlation would exist between severity of illness and

length of DUP.

MethodParticipants

The study population comprised 96 consecutive

first-episode never psychiatrically treated patients (50


Egyptian attendees of the outpatient clinic of a private

psychiatric hospital, Zagazig, Egypt, and 46 Saudi Arabian

attendees of an outpatient clinic of a private psychiatric

hospital, Jeddah, Saudi Arabia) during the first half-year

2009 AD/1430 H.

Eligibility criteria included the following:

(1) First presentation to psychiatric services.

(2) Age range of 15–60 years.

(3) Presence of nonaffective psychosis. Diagnosis was based

on Diagnostic and Statistical Manual, version IV criteria for

schizophreniform disorder, schizophrenia, delusional

disorder, or psychosis not otherwise specified.

(4) Residency in either Sharkiah governorate, Egypt, or

in the western province, Saudi Arabia.

(5) Availability of a reliable informant who had stayed

with the patient most of the period of illness and is

able to recall the details about the patient’s illness.

(6) Patient is willing to participate and gives a written

informed consent.

Exclusion criteria were the following:

(1) Presence of organic conditions or use of substances

that directly contribute to psychosis.

(2) Mental retardation.

(3) Epilepsy.

(4) Serious threat of suicide, violence, or other mental

states that would not allow participation (e.g., stupor)

or those who were judged as not having the capacity

to give consent. This capacity was assessed with a

four-item scale, three of which were based on those

reported by Palmer et al. [36] to examine participants’

comprehension of the purpose, risks, and benefits of

the research protocol; the fourth question was to

assess the voluntary nature of participation.

The inclusion and exclusion criteria were ascertained by

careful clinical assessments based on interviews with

patients and their families, physical examinations, and

routine laboratory testing, supplemented with toxicolo-

gical screening and other investigations as indicated.

The study was approved by the Research Ethics Commit-

tee of the Faculty of Medicine, Zagazig University, Zagazig,

Egypt and the Local Research Ethics Committee of the

Psychiatric Hospital, Jeddah, KSA.

Assessments

Patients were assessed by semistructured interviews

attended by at least one close relative to confirm the

information given by the patient. Assessments included

the following:

(1) DUP determination: DUP was defined as the time

between the onset of first psychotic symptoms

(e.g., hallucinations, delusions, thought disorder, or

inappropriate or bizarre behavior) and the time of

receiving first adequate treatment. To determine the

onset date, patients and family members were asked

to state when the patient (or family member) first

experienced (or noticed) behavioral changes that,

in retrospect, appear to be related to the patient

becoming ill. These changes must have lasted

throughout the day for several days or several times

a week and not be limited to a few brief moments.

The patients (or family members) were asked again,

after explaining psychosis in clear language, when they

first experienced (or noticed) psychotic symptoms?

When there were differences between patients and

family members, the date given by the patient was

taken because most of the time the exact onset of

illness had been overlooked by the relatives [37]. The

mode of onset of psychosis was operationally defined

as acute (o1 month) or insidious (41 month).

(2) Help-seeking contacts: Using a semistructured ques-

tionnaire, details were obtained about any contacts,

medical or otherwise, that were made to obtain help

for the patient’s condition before approaching the

psychiatric service. In addition, reasons for delay in

getting psychiatric help were enquired about. Details

about sociodemographic characteristics were also

recorded.

(3) The Positive and Negative Syndrome Scale (PANSS)

[38]: This is a 30-item test. Each item is rated from 1

(no evidence) to 7 (extreme). In addition to the total

score for overall psychopathology (sum of all 30

items), PANSS has subscales that yield data on

positive symptoms of psychosis (7 items), negative

symptoms of psychosis (7 items), and general

psychopathology (16 items). The a coefficients of

reliability reported for the PANSS scale scores are 0.73

for the positive scale, 0.83 for the negative scale, and

0.79 for the general psychopathology scale [38]. All

raters in the two sites were experienced in using

PANSS. They were trained at the same center using

face-to-face interviews with patients and videotaped

cases. The intraclass correlations for total scores and

subscale scores on the PANSS were in the range of

0.85–0.93.


Data were presented as arithmetic mean ± standard

deviation ( ± SD), or as median (range) for continuous

variables, and as absolute values with percentages for

categorical measures. Differences between groups were

analyzed using either the t-tests for independent samples

for normally distributed variables or the nonparametric

Mann–Whitney U-test when distributional assumptions

were not met. Nominal variables were cross-tabulated,

and relationships were assessed using the w2 test.

Spearman’s r was used to calculate correlations. To

address the highly skewed distribution of DUP, we

performed a logarithmic (base 10) transformation of the

variable. Multiple linear regressions were used to explore

the factors associated with DUP. Variables that showed

significant correlation with log DUP were further

analyzed using multiple linear regression, the stepwise

method, with both forward selection and backward

elimination (Po0.05 for entry and P40.10 for removal),

to evaluate their influence (as independent variables)

Duration of untreated psychosis Fawzi et al. 219

on the change of the logarithmically transformed DUP

(as the dependent variable). Dummy variables were used

for nationality (Egyptian = 1; Saudi = 0), sex (male = 1;

female = 0), marital status (married = 1; unmarried = 0),

occupation (yes = 1; no = 0), residence in Egypt (urban =

1; rural = 0), residence in Saudi Arabia (metropolitan = 1;

nonmetropolitan = 0), family history (positive for psychia-

tric illness = 1; negative for psychiatric illness = 0), mode of

onset (insidious = 1; acute = 0), diagnosis (schizophrenia =

1; other nonaffective psychoses = 0), and first help-seeking

contact (traditional/faith-healer = 1; others = 0). A stan-

dardized beta estimate was used to determine which

variable had the strongest effect on DUP. The SPSS

statistical program, version 11.5 [SPSS for Windows, 2001

(SPSS Inc., Chicago, IIIinois, USA)], was used for all

statistical analyses and sample size estimations. A two-

tailed P value of less than 0.05 was considered significant.

ResultsAs shown in Table 1, most of the patients in the Egyptian

and Saudi Arabian samples were unmarried, with the

Egyptian patients significantly more often so than Saudi

Arabian patients (80 versus 60.9%; P = 0.039). There

were no significant differences between the two groups

with regard to all other sociodemographic parameters.

However, the two groups differed in the frequency

distribution of the diagnostic categories (P = 0.049). The

Egyptian patient group had more patients with schizo-

phrenia, whereas the Saudi Arabian patient group had

more patients with other nonaffective psychoses. In

addition, when patients were subclassified by sex, there

were more men (25 patients, 50%) than women (10

patients, 20%) with a diagnosis of schizophrenia among

the 50 Egyptian patients (w2 = 13.909; df = 5; P = 0.016),

but there were no sex differences as regards diagnosis of

Table 1 Sociodemographic, clinical, and help-seeking characteristics of the Egyptian (N = 50) and Saudi Arabian patients (N = 46)

Patients

Characteristic Egyptian Saudi Arabian Analysis

Sociodemographic characteristicsSex

Male 28 25 w2 = 0.026; df = 1; P = 0.871Female 22 21

Age (years)Mean ± SD 26.8 ± 9.42 28.6 ± 11.27 t = 0.837; df = 94; P = 0.405

Marital statusMarried 10 18 w2 = 4.244; df = 1; P = 0.039Unmarrieda 40 28

Education (years)Mean ± SD 9.8 ± 3.72 9.2 ± 3.21 t = 0.905; df = 94; P = 0.368

OccupationYes 27 33 w2 = 3.217; df = 1; P = 0.073No 23 13

ResidenceUrban/Metropolitan 28 30 w2 = 0.851; df = 1; P = 0.356Rural/ nonmetropolitan 22 16

Clinical characteristicsFamily history

Positive 16 13 w2 = 0.159; df = 1; P = 0.690Negative 34 33

Age at onset (years)Mean ± SD 23.6 ± 10.01 25.5 ± 10.9 t = 0.887; df = 94; P = 0.377

Mode of onsetAcute 19 25 w2 = 2.579; df = 1; P = 0.108Insidious 31 21

Diagnosis groupSchizophrenia 35 17 w2 = 11.099; df = 5; P = 0.049Schizophreniform disorder 4 8Schizoaffective disorder 4 10Brief psychotic disorder 2 4Delusional disorder 1 2Psychotic disorder NOS 4 5

PANSSTotal: Mean ± SD 92.0 ± 13.58 88.5 ± 12.16 t = 1.358; df = 94; P = 0.178Positive: Mean ± SD 23.0 ± 4.54 21.6 ± 4.08 t = 1.593; df = 94; P = 0.114Negative: Mean ± SD 22.2 ± 4.04 22.4 ± 3.17 t = 0.315; df = 94; P = 0.753General psychopathology ± SD 46.8 ± 7.88 44.4 ± 8.71 t = 1.423; df = 94; P = 0.158

Help-seeking characteristicsFirst contact

Traditional (faith) healer 39 31 w2 = 1.894; df = 2; P = 0.388General practitioner/other professionals 5 9None before current (psychiatric) contact 6 6

DUP (years)Mean ± SD 3.2 ± 2.16 3.1 ± 2.02 Mann-Whitney U = 1130.5; Z = 0.144; P = 0.885Median (range) 3.0 (0.02–10.5) 3.0 (0.01–10.0)

DUP, duration of untreated psychosis; PANSS, Positive and Negative Syndrome Scale; Psychotic disorder NOS, psychotic disorder not otherwisespecified; SD, standard deviation.aUnmarried, Single/Divorced/Widow.


schizophrenia among the Saudi Arabian patients. There

were no significant differences in family history, age at

onset, mode of onset, or PANSS scores between the

Egyptian and Saudi Arabian patients. In addition, there

were no significant differences in first contact or DUP

between the Egyptian and Saudi Aabian patients. In both

groups, the most common first contact was the traditional

(faith) healer. Egyptian patients who first contacted

traditional (faith) healers had significantly longer mean

DUP (3.6 ± 2.17) compared with those who did not

(1.7 ± 1.33) (Z = 2.770; P = 0.006). Saudi Arabian pa-

tients who first contacted traditional (faith) healers also

tended to have longer mean DUP (3.5 ± 2.20) compared

with those who did not (2.3 ± 1.28); however, this

difference was not statistically significant (Z = 1.753;

P = 0.080). The mean DUP was significantly longer in

patients with a diagnosis of schizophrenia among both

Egyptian and Saudi Arabian patients. Egyptian patients

with a diagnosis of schizophrenia had a significantly

longer mean DUP (3.8 ± 2.12 years) compared with

patients with a nonschizophrenia diagnosis (1.9 ± 1.63

years) (Z = 3.357, P = 0.001), whereas the corresponding

figures for the Saudi Arabian patients were 3.9 ( ± 2.12)

years versus 2.6 ( ± 1.78) years (Z = 2.197, P = 0.028).

With the aim of studying the relationship between DUP

and other variables, Spearman’s rank correlation was used

individually in the Egyptian and Saudi Arabian patient

groups, using DUP as the dependent variable. Results are

shown in Table 2. Variables that were significantly

associated with DUP were entered into multiple regres-

sion analyses. For the Egyptian patient group, these

variables included age at onset, education, residence,

family history, mode of onset, diagnosis, scores on the

negative subscale of PANSS, and first help-seeking

contact. The variables included for the Saudi Arabian

patient group were age at onset, education, residence,

family history, mode of onset, diagnosis, scores on the

negative subscale of PANSS, and first help-seeking

contact. For the overall study population, we included,

in addition to the variables already entered for the two

groups, nationality of the patient (Egyptian/ Saudi) as an

independent variable. As shown in Table 3, the final

models for both the Egyptian and Saudi Arabian patient

groups contained three variables: first help-seeking

contact, mode of psychosis onset, and diagnosis. The

final model for the total sample included two variables:

first contact and mode of onset. That is, only the first

contact and mode of onset remained as significant

predictors for longer DUPs. This final model accounted

for 56.9% of the variance in DUP and was statistically

significant (F = 63.8, P = 0.000).

DiscussionThis may be the first study to compare DUP between

two Arab countries. We found no significant difference

between the mean DUP of patients from Egypt (3.2

years) and that of patients from Saudi Arabia (3.1 years).

The DUP mean of patients from both countries is very

long compared with those reported from other countries,

especially from developed ones [33,39–41], indicating

that prolonged treatment delay is of major clinical

concern in both Arab cultures. Borrowing support from

the currently established association between prolonged

DUP and poor outcome of psychosis [7], the significance

of our finding could be extended to argue against the

presumed wisdom that ‘schizophrenia carries a better

prognosis in developing countries’ [42]. The first long-

term study of the outcome of schizophrenia in an Arab

country was conducted by Okasha et al. [43]. They found

that a 10-year outcome of a sample of Egyptian patients

‘was not better than that reported in developed

countries’, despite the putative protective factors,

including family support. It may be that these factors, if

any, would only have limited protective power during the

long period of illness without treatment.

Table 2 Correlations of duration of untreated psychosis with the

characteristics studied in the Egyptian patients (N = 50) and

Saudi Arabian patients (N = 46)

Egyptian patientsSaudi Arabian

patients

Characteristic Rho P Rho P

Sex 0.234 0.102 0.190 0.206Age (years)

Current – 0.210 0.144 – 0.109 0.472At onset – 0.269 0.059 – 0.249 0.095Marital status – 0.208 0.146 – 0.159 0.290Education – 0.276 0.052 – 0.262 0.078Occupation – 0.200 0.164 – 0.216 0.149Residence 0.383 0.006 0.310 0.036Family history – 0.369 0.008 – 0.335 0.023Mode of onset 0.585 0.000 0.602 0.000Diagnosis 0.447 0.001 0.574 0.000

PANSSTotal 0.266 0.074 0.269 0.059Positive – 0.250 0.094 – 0.251 0.079Negative 0.291 0.040 0.377 0.010General psychopathology 0.275 0.053 0.241 0.107

First contact 0.591 0.000 0.527 0.000

PANSS, Positive and Negative Syndrome Scale.

Table 3 Regression analysis of variables significantly asso-

ciated with the duration of untreated psychosis in the Egyptian

(N = 50), Saudi Arabian (N = 46), and overall study patients

(N = 96): final models

Explanatory variable B SE Beta t P

Egyptian patient samplea

(Constant) 1.126 1.415 0.769 0.430First contact 0.296 0.044 0.622 6.680 0.000Mode of onset 0.991 0.414 0.230 2.395 0.021Diagnosis 0.044 0.019 0.205 2.294 0.026

Saudi Arabian patient sampleb

(Constant) 9.487 1.242 7.638 0.000First contact 0.139 0.012 0.837 11.562 0.000Mode of onset 0.031 0.013 0.165 2.344 0.024Diagnosis 0.194 0.088 0.160 2.208 0.033

Total samplec

(Constant) 6.288 1.038 6.058 0.000First contact 0.112 0.011 0.695 10.230 0.000Mode of onset 0.291 0.086 0.230 3.378 0.001

aAdjusted R2 = 0.641; F = 30.2; P = 0.000.bAdjusted R2 = 0.781; F = 54.6; P = 0.000.cAdjusted R2 = 0.569; F = 63.8; P = 0.000.


In addition to the similarity between Egyptian and Saudi

Arabian patients in having a long DUP, there were a

number of similarities between the two groups in terms

of sociodemographic, clinical, and help-seeking character-

istics. In both groups, there were more men than women,

but this did not reflect in a significant sex difference in

DUP between Egyptian and Saudi Arabian patients. Pre-

vious studies examining this association showed discre-

pant results. Thorup et al. [44], for example, reported that

men had a longer DUP than women. By contrast, K�ster

et al. [45] found that women had longer DUP. However,

Large and Nielssen [46] examined more than 100

published studies of DUP and found that fewer than

one third had mentioned the DUP of men and women

separately. This could suggest that in most studies, in

accordance with our results, sex difference in DUP may

not have been significant [46].

We tried to conduct this study in comparable settings as

far as possible. Patients for the two study groups were

recruited from outpatient clinics of private psychiatric

hospitals. However, the place of residence of the

Egyptian patient group was classified into urban and

rural, whereas it was classified for the Saudi Arabian group

into metropolitan and nonmetropolitan. Nevertheless,

the Egyptian rural residence and the Saudi Arabian

nonmetropolitan residence correlated similarly with long

DUP. This is at variance with the finding of an

‘association between rural place of residence and shorter

DUP’, as reported by Sharifi et al. in Iran [47]. In defense

of their case, Sharifi et al. [47] argued that patients from

rural areas might have been detected better by the active

case finding of their national mental health programs in

rural areas. Nevertheless, the Iranian study did not

disprove the possibility that patients residing in rural

areas might be encountering difficulties in accessing

psychiatric hospitals, so that only those with recent onset

and severe psychosis were brought to hospital, whereas

those with chronic illness might have remained untreated

in the community (and hence escaped inclusion in the

study). Our contrasting finding, however, is in accordance

with our earlier study [29]. We could further argue that

rural families of schizophrenia patients in Egypt, or

nonmetropolitan families in Saudi Arabia, are perhaps

more able to compensate and cope with the dysfunctional

ill member and hence keep him/her untreated for

several years.

We also found that positive family history of psychiatric

illness in both patient groups was equally common and

negatively associated with the length of DUP. Although

our results are in contrast to those of some other

studies, [48] they are in agreement with others [49].

The presence of another family member who has been

receiving psychiatric treatment plays an important role in

the early presentation of psychosis. Conceivably, previous

contact with a psychiatric patient potentiates the

awareness of psychiatric symptoms and their significance.

Chen et al. [49] emphasize that educational efforts

directed at the family should be an essential part of any

strategy for the early detection of psychosis.

In line with recent studies indicating that mode of onset

is a determinant of DUP [50,27] we found in both

Egyptian and Saudi Arabian samples that insidious mode

of onset was associated with long DUP. Understandably,

more abrupt changes in experience and behavior are more

likely to be identified as a product of some pathological

processes and are more likely to trigger help-seeking

behavior compared with insidious changes. Conversely, if

psychosis develops insidiously, the chance is greater for

the occurrence of a gradual adaptation, as a result of which

the patient and his/her family become gradually desensi-

tized to the presence of abnormal behavioral signals

indicative of a psychotic illness and become less motivated

to overcome obstacles to help seeking, such as stigma.

The Egyptian and Saudi Arabian patient groups were

similar in many respects but differed in others. For

example, Egyptian patients were divorced, widowed, or

never married and had a diagnosis of schizophrenia

significantly more often than did Saudi Arabian patients.

These differences, however, were not reflected in a

difference in DUP.

Symptom severity as measured by PANSS was not,

however, different between Egyptian and Saudi Arabian

patients. In both groups, severity of negative symptoms,

but not positive symptoms or general psychopathology,

was associated with DUP. Although this finding contra-

dicts a few studies that failed to find evidence that a

longer period before treatment was associated with more

severe illness [51], it is consistent with the results of

many studies, including the meta-analyses provided by

Marshall et al. [6] and Perkins et al. [52]. Nevertheless,

when multiple regression analysis was performed and the

PANSS negative subscale score was entered as an

independent variable, this variable failed to be retained

in the final regression model, indicating that it is not a

significant predictor of DUP. In contrast, first contact

remained as the most significant predictor for long DUP

in the final model for the Egyptian, Saudi Arabian, and

total samples. It was noted that the traditional (faith)

healer was the most frequent help-seeking first contact in

both groups. In contrast to studies from non-Arabian

countries, which indicate that patients with psychotic

disorders contact the general practitioner practice more

frequently than do other types of patients [53], our

results showed that general practitioners play a minor

role. The major role played by traditional and religious

healers in primary psychiatric care in Egypt was first

noted by Okasha [54]. In one study it was estimated that

60% of outpatients at the university clinic in Cairo serving

low socioeconomic classes have been to traditional healers

before approaching a psychiatrist [55]. Recently, in a large

community survey in upper Egypt, Rakhawy, and Hamdi

[56] concluded that mentally disordered people have

considerable tendency toward faith healing. Interestingly,

our results, not only for the Egyptian patient group but

also for the Saudi Arabian patient group, are in accordance

with this conclusion. They also draw attention to the

failure of other agencies in directing patients to seek

help. Continued public education about psychosis, there-

by improving the knowledge of potential patients, their


relatives, and other people or organizations involved,

would be an important component in an overall strategy

to achieve early detection of psychosis and shorten DUP.

Our study, however, has a number of limitations. First,

patients as described above were taken from different

population areas. Egyptian patients came from urban and

rural areas of one governorate (Sharkia), whereas Saudi

Arabian patients were from the metropolitan area of

Jeddah city and from some of its surrounding nonme-

tropolitan areas. Second, patients recruited were from

those presenting to private psychiatric service only,

making it an false representation of Egyptian or Saudi

Arabian samples. Third, the sample size was modest, and

further study comprising a larger group of patients would

be worthy. Fourth, although a systematic approach with

the use of standardized instruments and a semistructured

interview was adopted, the DUP and pathway data are

based on patients’ descriptions and are subject to recall

bias. To enhance validity, all data were confirmed by at

least one family member who was present during the

interview. Moreover, some patient-related factors such as

lack of insight, poor social adjustment, or other psycho-

pathologies that might contribute to treatment delays

were not controlled for.

ConclusionThe limitations noted above signify that conclusions

should be viewed with some caution.

Patients with first-episode psychosis in both Egypt and

Saudi Arabia have a long DUP, which should be of major

clinical concern. In the two study sites, we found that

first contact with a traditional (faith) healer and insidious

mode of onset of psychosis were the two significant

predictors of long DUP. Although severity of negative

symptoms, as indicated by PANSS negative subscale

scores, was correlated with DUP, it could not be retained

in the final regression model as a significant predictor of

DUP. Therefore, our hypothesis that severity of illness at

presentation would strongly predict long DUP had to be

rejected. Factors found to influence DUP should be taken

into account in early intervention initiatives.


References1 Johnstone EC, Crow TJ, Johnson AL, MacMillan JF. The Northwick park study

of first episodes of schizophrenia. I. Presentation of the illness and problemsrelating to admission. Br J Psychiatry 1986; 148:115–120.

2 Larsen TK, Melle I, Auestad B, Haahr U, Joa I, Johannessen JO, et al. Earlydetection of psychosis: positive effects on 5-year outcome. Psychol Med2011; 41:1461–1469.

3 Malla AK, Bodnar M, Joober R, Lepage M. Duration of untreated psychosis isassociated with orbital-frontal grey matter volume reductions in first episodepsychosis. Schizophr Res 2011; 125:13–20.

4 Melle I, Larsen TK, Haahr U, Friis S, Johannesen JO, Opjordsmoen S, et al.Prevention of negative symptom psychopathologies in first-episode schizo-phrenia: two-year effects of reducing the duration of untreated psychosis.Arch Gen Psychiatry 2008; 65:634–640.

5 Sarotar BN, Pesek MB, Agius M, Pregelj P, Kocmur M. Duration of untreatedpsychosis and it’s effect on the functional outcome in Schizophrenia: Pre-liminary results. Psychiatr Danub 2008; 20:179–183.

6 Marshall M, Lewis S, Lockwood A, Drake R, Jones P, Croudace T. Associationbetween duration of untreated psychosis and outcome in cohorts of first-epi-sode patients: a systematic review. Arch Gen Psychiatry 2005; 62:975–983.

7 Farooq S, Large M, Nielssen O, Waheed W. The relationship between theduration of untreated psychosis and outcome in low-and-middle incomecountries: a systematic review and meta analysis. Schizophr Res 2009;109:15–23.

8 Kurihara T, Kato M, Kashima H, Takebayashi T, Reverger R, Gusti Rai I. Tirta.Excess mortality of schizophrenia in the developing country of Bali. Schi-zophr Res 2006; 83:103–105.

9 Ran MS, Chen EY, Conwell Y, Chan CL, Yip PS, Xiang MZ, et al. Mortality inpeople with schizophrenia in rural China: 10-year cohort study. Br J Psy-chiatry 2007; 190:237–242.

10 Drake RJ, Haley CJ, Akhtar S, Lewis SW. Causes and consequences ofduration of untreated psychosis in schizophrenia. Br J Psychiatry 2000;177:511–515.

11 Harrigan SM, McGorry PD, Krstev H. Does treatment delay in first-episodepsychosis really matter? Psychol Med 2003; 33:97–110.

12 Bottlender R, Moller HJ. The impact of the duration of untreated psychosison short- and long-term outcome in schizophrenia. Curr Opin Psychiatry2003; 16 (Suppl 2S39–S43).

13 Birchwood M, Fiorillo A. The critical period for early intervention. PsychiatrRehabil Skills 2000; 4:182–198.

14 McGorry PD, Killackey E, Yung AR. Early intervention in psychotic disorders:detection and treatment of the first episode and the critical early stages. MedJ Aust 2007; 187 (7 SupplS8–10).

15 Penttila M, Jaaskelainen E, Haapea M, Tanskanen P, Veijola J, Ridler K, et al.Association between duration of untreated psychosis and brain morphologyin schizophrenia within the Northern Finland 1966 Birth Cohort. SchizophrRes 2010; 123:145–152.

16 Takahashi T, Suzuki M, Tanino R, Zhou SY, Hagino H, Niu L, et al. Volumereduction of the left planum temporale gray matter associated with longduration of untreated psychosis in schizophrenia: a preliminary report. Psy-chiatry Res 2007; 154:209–219.

17 Cocchi A, Meneghelli A, Preti A. Programma 2000: celebrating 10 years ofactivity of an Italian pilot programme on early intervention in psychosis. AustN Z J Psychiatry 2008; 42:1003–1012.

18 Goldner Vukov M, Cupina DD, Moore LJ, Baba Milkic N, Milovanovic S. Earlyintervention in first episode psychosis: hope for a better future. Srp ArhCelok Lek 2007; 135:672–678.

19 Sim K, Yiong HC, Siow AC, Siris SG. A 24-month prospective outcome studyof first-episode schizophrenia and schizoaffective disorder within an earlypsychosis intervention program. J Clin Psychiatry 2007; 68:1368–1376.

20 Yung AR, Killackey E, Hetrick SE, Parker AG, Schultze Lutter F, Klos-terkoetter J, et al. The prevention of schizophrenia. Int Rev Psychiatry2007; 19:633–646.

21 McCrone P, Craig TKJ, Power P, Garety PA. Cost-effectiveness of an earlyintervention service for people with psychosis. Br J Psychiatry 2010; 196:377–382.

22 Mihalopoulos C, Harris M, Henry L, Harrigan S, McGorry P. Is early inter-vention in psychosis cost-effective over the long term? Schizophr Bull2009; 35:909–918.

23 Yap HL. Early psychosis intervention. Singapore Med J 2010; 51:689–693.

24 O’Callaghan E, Turner N, Renwick L, Jackson D, Sutton M, Foley SD, et al. Firstepisode psychosis and the trail to secondary care: help-seeking and health-system delays. Soc Psychiatry Psychiatr Epidemiol 2010; 45:381–391.

25 Norman RM, Malla AK, Verdi MB, Hassall LD, Fazekas C. Understandingdelay in treatment for first-episode psychosis. Psychol Med 2004; 34:255–266.

26 Oliveira AM, Menezes PR, Busatto GF, McGuire PK, Murray RM, ScazufcaM. Family context and duration of untreated psychosis (DUP): results fromthe sao paulo study. Schizophr Res 2010; 119:124–130.

27 Nishii H, Yamazawa R, Shimodera S, Suzuki M, Hasegawa T, Mizuno M.Clinical and social determinants of a longer duration of untreated psychosisof schizophrenia in a Japanese population. Early Interv Psychiatry 2010; 4:182–188.

28 Haas GL, Sweeney JA. Premorbid and onset features of first-episode schi-zophrenia. Schizophr Bull 1992; 18:373–386.

29 Fawzi M, Fawzi MJ. Help-seeking contacts of a sample of Egyptian patientswith a first episode psychosis. Cairo, Egypt: XIII WPA Comgress; 2005.

30 Isaac M, Chand P, Murthy P. Schizophrenia outcome measures in the widerinternational community. Br J Psychiatry 2007; 191 (Suppl 50s71–s77).

31 Jablensky A, Sartorius N, Ernberg G, Anker M, Korten A, Cooper JE, et al.Schizophrenia: manifestations, incidence and course in different cultures. AWorld Health Organization ten-country study. Psychol Med Monogr Suppl1992; 20:1–97.

32 Iyer SN, Mangala R, Thara R, Malla AK. Preliminary findings from a study offirst-episode psychosis in Montreal, Canada and Chennai, India: comparisonof outcomes. Schizophr Res 2010; 121:227–233.


33 Archie S, Akhtar Danesh N, Norman R, Malla A, Roy P, Zipursky RB. Ethnicdiversity and pathways to care for a first episode of psychosis in Ontario.Schizophr Bull 2010; 36:688–701.

34 Burns JK, Jhazbhay K, Emsley RA. Causal attributions, pathway to care andclinical features of first-episode psychosis: a South African perspective. Int JSoc Psychiatry 2010[Epub ahead of print].

35 Kwong KK, Levitt CE. The impact of national culture on value based deci-sions: comparison of Saudi Arabian, Egyptian and American healthcareprofessionals. 2009; Available at: http://www.thefreelibrary.com/The +impact + of + national + culture + on + value + based + decisions%3A +comparisony-a0219002332.

36 Palmer BW, Dunn LB, Appelbaum PS, Mudaliar S, Thal L, Henry R, et al.Assessment of capacity to consent to research among older persons withschizophrenia, Alzheimer disease or diabetes mellitus: comparison of a 3-item questionnaire with a comprehensive standardized capacity instrument.Arch Gen Psychiatry 2005; 62:726–733.

37 Perkins DO, Leserman J, Jarskog LF, Graham K, Kazmer J, Lieberman JA.Characterizing and dating the onset of symptoms in psychotic illness: thesymptom onset in schizophrenia (SOS) inventory. Schizophr Res2000; 44:1–10.

38 Kay SR, Fiszbein A, Opler LA. The positive and negative syndrome scale(PANSS) for schizophrenia. Schizophr Bull 1987; 13:261–276.

39 Cougnard A, Kalmi E, Desage A, Misdrahi D, Abalan F, Brun Rousseau H,et al. Pathways to care of first-admitted subjects with psychosis in South-Western France. Psychol Med 2004; 34:267–276.

40 Gupta PR, Chakrabarti S, Kulhara P. Lack of association between duration ofuntreated psychosis and outcome in an Indian cohort. World Psychiatry2010; 9:124–125.

41 Kohn D, Pukrop R, Niedersteberg A, Schultze Lutter F, Ruhrmann S, Bech-dolf A, et al. Pathways to care: help-seeking behavior in first-episode psy-chosis Wege in die behandlung: hilfesuchverhalten schizophrenerersterkrankter. Fortschr Neurol Psychiatr 2004; 72:635–642.

42 Cohen A, Patel V, Thara R, Gureje O. Questioning an axiom: better prognosisfor schizophrenia in the developing world? Schizophr Bull 2008; 34:229–244.

43 Okasha A, Sadek A, Seif Al Dawla A, Okasha T, Sayed M, Youssef A. Out-come of schizophrenia: a ten-year study of a sample of Egyptian patients.Egypt J Psychiatry 2005; 24:21–32.

44 Thorup A, Petersen L, Jeppesen P, Ohlenschlaeger J, Christensen T, KrarupG, et al. Gender differences in young adults with first-episode schizophreniaspectrum disorders at baseline in the Danish OPUS study. J Nerv Ment Dis2007; 195:396–405.

45 K�ster A, Lajer M, Lindhardt A, Rosenbaum B. Gender differences in firstepisode psychosis. Soc Psychiatry Psychiatr Epidemiol 2008; 43:940–946.

46 Large MM, Nielssen O. Gender differences in the duration of untreatedpsychosis. J Nerv Ment Dis 2008; 196:171–172.

47 Sharifi V, Kermani Ranjbar T, Amini H, Alaghband Rad J, Salesian N, SeddighA. Duration of untreated psychosis and pathways to care in patients withfirst-episode psychosis in Iran. Early Interv Psychiatry 2009; 3:131–136.

48 Norman RMG, Malla AK, Manchanda R. Delay in treatment for psychosis: itsrelation to family history. Soc Psychiatry Psychiatr Epidemiol 2007; 42:507–512.

49 Chen EY, Dunn EL, Miao MY, Yeung WS, Wong CK, Chan WF, et al. Theimpact of family experience on the duration of untreated psychosis (DUP) inHong Kong. Soc Psychiatry Psychiatr Epidemiol 2005; 40:350–356.

50 Compton MT, Chien VH, Leiner AS, Goulding SM, Weiss PS. Mode of onsetof psychosis and family involvement in help-seeking as determinants ofduration of untreated psychosis. Soc Psychiatry Psychiatr Epidemiol2008; 43:975–982.

51 Owens DC, Johnstone EC, Miller P, Fiona Macmillan J, Crow TJ. Duration ofuntreated illness and outcome in schizophrenia: test of predictions in relationto relapse risk. Br J Psychiatry 2010; 196:296–301.

52 Perkins DO, Gu H, Boteva K, Lieberman JA. Relationship between durationof untreated psychosis and outcome in first-episode schizophrenia: a criticalreview and meta-analysis. Am J Psychiatry 2005; 162:1785–1804.

53 Oud MJT, Schuling J, Groenier KH, Verhaak PFM, Slooff CJ, Dekker JH, et al.Care provided by general practitioners to patients with psychotic disorders:a cohort study. BMC Fam Pract 2010; 11Art. No. 92. DOI: 10.1186/1471-2296-11-92. .

54 Okasha A. A cultural psychiatric study of El-Zar cult in U.A.R. Br J Psychiatry1966; 112:1217–1221.

55 Okasha A, Kamel M, Hassan AH. Preliminary psychiatric observationsin Egypt. Br J Psychiatry 1968; 114:949–955.

56 Rakhawy MY, Hamdi E. The attitude and use of faith healing by people withmental disorders in upper Egypt: a community survey. Arab J Psychiatry2010; 21:29–49.


Shyness and sociability in a sample of Egyptian patients

with schizophrenia and its relation to resting frontal EEGHoda Abdou Husseina, Heba Fathya, Sherine Mohamed Abdel Mawlaa,Fadia Zyadaa and Reem A. El Hadidyb

Departments of aPsychiatry and bNeurophysiology,Faculty of Medicine, Cairo University, Giza, Egypt

Correspondence to Heba Fathy, Department ofPsychiatry, Faculty of Medicine, Giza, EgyptTel: + 101404826;e-mail: [email protected]

Received 22 February 2011Accepted 1 March 2011


2011, 18:226–230

Introduction

One of the most disabling features and consequences of schizophrenia is the marked

impairment of social skills.

Aim of the study

The aim of this study is to determine the relationship between premorbid shyness

and negative symptoms and resting frontal quantitative EEG alpha activity in patients

with schizophrenia.

Methodology

Forty patients with schizophrenia were selected successively in a cross-sectional

study. The patients were assessed using The Structured Clinical Interview for

Diagnostic and Statistical Manual of Mental Disease Axis of Disorders, Positive and

Negative Syndrome Scale, The Revised Cheek and Buss Shyness, and Sociability

Scale. Quantitative EEG was carried out and assessed for frontal alpha asymmetry.

Results

Ninety-seven percent of the patients showed asymmetrical frontal alpha EEG activity

and 85% showed right resting frontal alpha EEG asymmetry. Patients with right frontal

asymmetry showed higher PANSS-negative and shyness scores than those with

left asymmetry.

Conclusion

The negative symptoms of schizophrenia and premorbid shyness could be related to

right frontal resting alpha EEG asymmetry.

Keywords:

negative symptoms, QEEG alpha asymmetry, schizophrenia, shyness


IntroductionOne of the most disabling features and consequences

of schizophrenia is the marked impairment of social

skills [1]. Negative symptoms of schizophrenia such as

decreased spontaneous movements, poor eye contact, and

social withdrawal are especially detrimental to normal

social interactions and are inversely correlated with social

skills’ performance [2]. These behavioral deficits are also

associated with a poor prognosis, cognitive impairments,

and reduced functioning [3].

Behavioral deficits in social functioning such as poor eye

contact and social withdrawal are also characteristics of

temperamental shyness [4], although there is research

suggesting that stable individual differences in person-

ality do exist among individuals with schizophrenia [5]

and can possibly influence the severity and symptoms of

the pathology [6].

It has been reported that hospitalized patients with

schizophrenia experience greater shyness than con-

trols [7]. More recently, another study found a higher

degree of early shyness and sociability troubles in patients

than controls [8] and greater relative right resting frontal

EEG activity (a trait marker of stress) in patients with

schizophrenia who were shy [9]. These findings have

important implications in light of research suggesting that

early biological and behavioral antecedents of shyness and

social withdrawal are identifiable in infants and young

children, are linked to sensitivity of forebrain limbic and

frontal cortical areas, and produce dysfunction in one’s

ability to regulate social stress [4].

Healthy adults and children who exhibit right frontal

EEG asymmetry at rest are easily distressed, fearful, and

shy, whereas those who exhibit left frontal EEG asymmetry

at rest are socially outgoing and extroverted [10,11].

Because the pattern of frontal EEG asymmetry at rest is

stable across time and its appearance early in life is

predictive of later personality, some have argued that this

metric may be ‘trait-like’ [11,12].

Some studies found that adults with schizophrenia scored

significantly higher on measures of premorbid behavioral

inhibition and trait measures of shyness compared with

healthy adults [8], and that measures of trait shyness

were immutable to change following weekly social skills’

training over a 7-month period [13]. Another study

revealed that high trait shyness was related to greater

226 Original article

2090-5408 & 2011 Okasha Institute of Psychiatry, Ain Shams University DOI: 10.1097/01.XME.0000403817.06941.1f

relative resting right frontal EEG activity, whereas high

trait sociability was related to greater relative resting left

frontal EEG activity [13].

Aim of the studyTo study the relationship between premorbid shyness,

negative symptoms, and resting frontal alpha EEG

activity in patients with schizophrenia.

Patients and methodsAfter receiving approval from Research Ethical Commit-

tee Review in Kasr El Aini hospital, 40 patients with

schizophrenia diagnosed by Lecturer of Psychiatry

according to Diagnostic and Statistical Manual of Mental

Disease, 4th edition [14] criteria were recruited from the

psychiatric outpatient clinic of Kasr El Aini hospital. This

is a cross-sectional study. All patients gave consent to

participate in the study after a full explanation of

procedures was provided. Both sexes were included and

the age range was 20–50 years. We excluded patients with

other psychiatric disorders, mental retardation, organic

brain disorders, especially epilepsy, and substance-in-

duced psychiatric disorders. Forty control cases (healthy

volunteers among the medical and paramedical personnel

staff of Kasr El Aini university hospital) were chosen from

an alphabetical computer list of employees of the

hospital. All the scales showed absence of psychopathol-

ogy in the control group. They were matched in terms of

age and sex.

Psychometric tools

Semistructural interview

A specially designed semistructural interview derived

from the Kasr El Aini psychiatric sheet was used to collect

demographic data, personal data, past history, and family

history.

The structured clinical interview for the Diagnostic and

Statistical Manual of Mental Disease Axis of Disorders

(severe combined immunodeficiency-I) [15]

The structured clinical interview for Diagnostic and

Statistical Manual of Mental Disease, 4th edition axis I

disorders, severe combined immunodeficiency-I, provides

a broad coverage of axis I psychiatric diagnosis according

to Diagnostic and Statistical Manual of Mental Disease,

4th edition.

Positive and Negative Syndrome Scale [16]

Each scale comprises seven symptoms that are rated on a

1 (absent) to 7 (extreme) metric.

The Revised Cheek and Buss Shyness and Sociability

Scale [17]

The scale was translated and back translated to the

Arabic language. These two scales comprised a 20-item

self-report questionnaire. Sample items from the shyness

scale include ‘I don’t find it hard to talk to strangers’

(scored in reverse direction). Sample items from the

sociability scale include ‘I like to be with people’, and are

scored on a 0–4 metric, with high scores showing shyness

and sociability for the two scales.

EEG mapping was carried out as an outpatient procedure

during the daytime with a recording time of 30 min:

15 min with the eyes open and 15 min with the eyes

closed. We used a 14-channel digitalized Schwarzer

BrainLab 4 GmbH (Germany), medical diagnostic

equipment. The EEG surface electrodes were positioned

according to the 10/20 system of the International

Federation, with an electrode impedance below 10 Kohm,

and ear lobe electrodes served as a reference [18]. The

EEG was recorded from the left and right anterior and

posterior regions of the scalp (i.e. mid-frontal, F3 and F4,

and parietal, P3 and P4).

The EEG activity was collected in the parietal region in

order to examine whether asymmetry differences were

specific to the frontal region.

EEG data reduction and quantification

The EEG data were visually scanned for artifacts because

of movement (e.g. eye blinks and body movements). If an

artifact was present in one channel, then data in all

channels were excluded. All artifact-free EEG data were

analyzed using a discrete Fourier transform. Regional

EEG power was derived in the alpha (8–13 Hz) frequency

band separately for the EO and EC conditions. Because

the EEG power in the EO and EC conditions was highly

related for each of the sites, a composite measure of

resting EEG alpha power was computed separately for

each EEG site by averaging power in the EO and EC

conditions. This aggregate measure is known to produce a

more reliable estimate of EEG power and asymmetry

than separate EO and EC conditions [12]. A separate

EEG asymmetry measure was then computed for the

frontal (i.e. F4 alpha power minus F3 alpha power) and

parietal (i.e. P4 alpha power minus P3 alpha power)

regions. Because EEG power is inversely related to

activation, negative values on the frontal asymmetry

metric reflect greater relative right EEG activation [19].

After calculating the difference between F3, F4 and P3,

P4 for each participant, whether case or control, we

calculated the average difference for the control cases.

Then we took this average as the cut-off limit of

asymmetry among the cases. So any patient above average

of control was considered as asymmetry.

The statistical methods

Data were statistically described in terms of range,

mean ± standard deviation, and median when appropri-

ate. Comparison between right-side and left-side asym-

metry results was carried out using the Mann–Whitney

U-test for independent samples. The correlation between

various variables was assessed using the Spearman rank

correlation equation for a nonnormal relation. A prob-

ability value (P-value) less than 0.05 was considered

statistically significant. All statistical calculations were

carried out using computer programs Microsoft Excel

Shyness in schizophrenia Hussein et al. 227

2007 (Microsoft Corporation, New York, USA) and SPSS

(Statistical Package for the Social Science; SPSS Inc.,

Chicago, Illinois, USA) version 15 for Microsoft Windows.

ResultsSociodemographic data

There were no statistically significant differences regard-

ing age, sex, marital status, education, and occupation

between the patients and the control (Tables 1–4).

Discussion

Schizophrenia is one of the most debilitating psychiatric

disorders, affecting approximately 1% of the population [14].

The clinical manifestations of schizophrenia vary widely in

both symptomology and severity, and recent research

suggests that individual differences in personality traits

or coping styles may account for part of this variance [6,8].

Also, certain maladaptive personality traits may predate

illness onset [20]. Individual differences in personality do

exist among people with schizophrenia [5] and can possibly

influence the severity and symptoms [6].

It was found that healthy adults and children who exhibit

right frontal EEG asymmetry at rest are easily distressed,

fearful, and shy, whereas those who exhibit left frontal

EEG asymmetry at rest are socially outgoing and

extroverted [10,11]. Because the pattern of frontal EEG

asymmetry at rest is stable across time and context [21]

and its appearance early in life is predictive of later

personality [11], some have argued that this represents a

‘trait-like’ marker of dispositional affective style [22].

We conducted this study to examine the relationship

between frontal EEG asymmetry at rest and trait

measures of shyness and sociability in a sample of

Egyptian patients with schizophrenia. It was found that

positive and negative symptoms are related more to right

frontal asymmetry, which was statistically significant only

with negative symptoms; this is consistent with Gruze-

lier [23] and Sutton and Davidson [24], who observed

right hemisphere asymmetries in patients experiencing

negative symptoms but not consistent with their findings

that left hemisphere asymmetries noted in patients

experiencing positive symptoms. This could be because

of patient selection or drug effects.

Our results agreed with those of Schmidt [10], who found

left frontal asymmetry in shy individuals who never-

theless scored high on measures of sociability.

Our findings are also not consistent with those of Jetha

et al. [13], who found a left hemispheric bias in patients

experiencing positive symptoms.

We also found that patients with left frontal asymmetry

show premorbid high sociability, whereas patients with

right frontal asymmetry show premorbid high shyness,

with a statistically significant difference. Our results are

consistent with some studies showing that adults with

schizophrenia scored significantly higher on measures

of premorbid behavioral inhibition and trait measures of

shyness compared with healthy adults [8,25] and that

measures of trait shyness were immutable to change

following weekly social skills’ training over a 7-month

period [13]. Jetha et al. [13] revealed that high trait

shyness was related to greater relative resting right frontal

EEG activity, whereas high trait sociability was related to

greater relative resting left frontal EEG activity.

However, in this study, it was found that PANSS-positive

and PANSS-negative schizophrenic patients have right

parietal asymmetry more than left parietal asymmetry.

Sociability and shyness associated with right parietal

asymmetry showed no statistically significant differences.

This is in concordance with the study carried out by

Schmidt and Fox, who examined differences in brain

electrical activity (EEG), heart rate (EKG), heart rate

variability, and behavior among 40 young women who

Table 1 Comparison between frontal and parietal asymmetry

(above average control)

Frontal Parietal

Frequency % Frequency %

No asymmetry 1 2.5 18 45Asymmetry 39 97.5 22 55

Table 2 Right and left asymmetry in frontal and parietal

(above average control)

Frontal asymmetry Parietal asymmetry

Frequency % Frequency %

Right 34 85 15 37.5Left 5 12.5 7 17.5

Table 3 Comparison between clinical variables in right and left

frontal asymmetry

Mean ± SD

Right frontal asymmetry Left frontal asymmetry P

PANSS positive 22.7 ± 8.9 20.4 ± 9.5 0.6PANSSnegative

28.2 ± 9.6 18.6 ± 5.5 0.02

Sociability 22.3 ± 6.4 30 ± 4.3 0.01Shyness 35.7 ± 7.3 27 ± 8.4 0.03

PANSS, Positive and Negative Syndrome Scale; SD, standarddeviation.

Table 4 Comparison between clinical variables in right and left

parietal asymmetry

Mean ± SD

Right parietal asymmetry Left parietal asymmetry P

PANSSpositive

23.3 ± 9.2 21.7 ± 5.5 0.6

PANSSNegative

27.7 ± 10.5 26.5 ± 9.5 1

Sociability 22.9 ± 6.3 22 ± 6.4 0.7Shyness 35.2 ± 7.9 34.7 ± 8.4 0.8

PANSS, Positive and Negative Syndrome Scale; SD, standarddeviation.


were selected for high and low self-ratings of shyness and

sociability. They found that LOSHY/HISOCIABLE parti-

cipants displayed greater relative right parietal activation

and LOSHY/LOSOCIABLE participants displayed great-

er relative left parietal activation [26]. Also, the results

of Jetha et al. [13] disagree with our results; they did not

find a relation between parietal asymmetry and the

negative symptoms scale.

Limitations

(1) The relatively small sample size limits generaliza-

tions to a broader population of individuals with

schizophrenia. Future studies should attempt to

replicate the present findings with a larger sample

of adults with schizophrenia.

(2) The second limitation concerns the reliance on self-

report measures in general for patients with schizo-

phrenia, which may have potential for distortion

depending on the degree of psychotic symptoms.

However, we confirmed this information from the

participants.

(3) In addition, Beaton et al. [27] highlight the importance

of considering concurrent emotional states of partici-

pants when examining psychophysiological correlates of

personality. But in this study we did not measure the

emotional state of the participants.

(4) Although The Revised Shyness and Sociability Scale

was translated and back translated by two different

blind researchers, the methodological standardization

of the applied test is still ongoing.


References1 Morrison RL, Bellack AS. Social functioning of schizophrenic patients:

clinical and research issues. Schizophr Bull 1987; 13:715–725.

2 Jackson HJ, Minas IH, Burgess PM, Joshua SD, Charisiou J, Campbell IM. Issocial skills performance a correlate of schizophrenia subtypes? SchizophrRes 1989; 2:301–309.

3 Davidson L, McGlashan TH. The varied outcomes of schizophrenia.Can J Psychiatry 1997; 42:34–43.

4 Schmidt LA, Polak CP, Spooner AL. Biological and environmental contribu-tions to childhood shyness: a diathesis-stress model. In: Crozier WR, AldenLE, editors. The essential handbook of social anxiety for clinicians. WestSussex, UK: John Wiley & Sons; 2005. pp. 33–55.

5 Kentros M, Smith TE, Hull J, McKee M, Terkelsen K, Capalbo C. Stabilityof personality traits in schizophrenia and schizoaffective disorder: a pilotproject. J Nerv Ment Dis 1997; 185:549–555.

6 Guillem F, Bicu M, Semkovska M, Debruille JB. The dimensional symptomstructure of schizophrenia and its association with temperament andcharacter. Schizophr Res 2002; 56:137–147.

7 Flanagan R. Shyness, egocentricity and psychopathology: their relationshipsamong nonhospitalized individuals and mental hospital patients. Psychol Rep1992; 70 (3 Pt 1):995–1004.

8 Goldberg JO, Schmidt LA. Shyness, sociability and social dysfunction inschizophrenia. Schizophr Res 2001; 48:343–349.

9 Jetha MK, Schmidt LA, Goldberg JO. Stability of shyness, sociability andsocial dysfunction in schizophrenia: a preliminary investigation of the influ-ence of social skills training in a community-based stable outpatient sample.Eur J Psychiatry 2007; 21:189–198.

10 Schmidt LA. Frontal brain electrical activity in shyness and sociability.Psychol Sci 1999; 10:316–320.

11 Fox NA, Henderson HA, Rubin KH, Calkins SD, Schmidt LA. Continuity anddiscontinuity of behavioral inhibition and exuberance: psychophysiologicaland behavioral influences across the first four years of life. Child Dev2001; 72:1–21.

12 Tomarken AJ, Davidson RJ, Wheeler RE, Kinney L. Psychometric propertiesof resting anterior EEG asymmetry: temporal stability and internalconsistency. Psychophysiology 1992; 29:576–592.

13 Jetha MK, Schmidt LA, Goldberg JO. Resting frontal EEG asymmetry andshyness and sociability in schizophrenia: a pilot study of community-basedoutpatients. Int J Neurosci 2009; 119:847–856.

14 American Psychiatric Association. Diagnostic and statistical manualof mental disorders. 4th ed. Washington, DC: American Psychiatric Asso-ciation. American Psychiatric Pub; 2000.

15 First MB, Gibbon M, Spitzer RL, Williams JBW, Benjamin LS. Structuredclinical interview for DSM-IV axis II personality disorders, (SCID-II).Washington, DC: American Psychiatric Press Inc.; 1997.

16 Kay SR, Fiszbein A, Opler LA. The positive and negative syndrome scale(PANSS) for schizophrenia. Schizophr Bull 1987; 13:261–276.

17 Cheek JM, Buss AH. Shyness and sociability. J Pers Soc Psychol1981; 41:330–339.

18 Jasper HH. The ten-twenty electrode system of the international federation.Electroenceph Clin Neurophysiol 1958; 10:371–375.

19 Davidson RJ, Tomarken AJ. Laterality and emotion: an electrophysiologicalapproach. In: Boller F, Grafman J, editors. Handbook of neuropsychology.Amsterdam: Elsevier; 1989. pp. 419–441.

20 Cuesta MJ, Peralta V, Caro F. Premorbid personality in psychoses. SchizophrBull 1999; 25:801–811.

21 Schmidt LA, Cote KA, Santesso DL, Milner CE. Frontal electro-encephalogram alpha asymmetry during sleep: stability and its relation toaffective style. Emotion 2003; 3:401–407.

22 Davidson RJ, Goldsmith HH, Scherer K. Handbook of affective science.New York: Oxford University Press; 2003.

23 Gruzelier JH. Functional neuropsychophysiological asymmetry in schizo-phrenia: a review and reorientation. Schizophr Bull 1999; 25:91–120.

24 Sutton SK, Davidson RJ. Prefrontal brain asymmetry: a biological substrateof the behavioral approach and inhibition systems. Psychol Sci1997; 8:204–210.

25 Coan JA, Allen JJ. Frontal EEG asymmetry and the behavioral activation andinhibition systems. Psychophysiology 2003; 40:106–114.

26 Schmidt LA, Fox NA. Patterns of cortical electrophysiology and autonomicactivity in adults’ shyness and sociability. Biol Psychol 1994; 38:183–198.

27 Beaton EA, Schmidt LA, Ashbaugh AR, Santesso DL, Antony MM,McCabe RE. Resting and reactive frontal brain electrical activity (EEG)among a non-clinical sample of socially anxious adults: does concurrentdepressive mood matter? Neuropsychiatr Dis Treat 2008; 187–192.

Shyness in schizophrenia Hussein et al. 229

Prevalence and risk factors of unexplained somatic symptoms

in school-aged children of Sharkia GovernorateNagy M. Fawzya, Haitham M. Hashima and Hadeel M.A. Rahmanb

aDepartments of Psychiatry andbPediatrics, Faculty of Medicine, Zagazig University,Zagazig, Egypt

Correspondence to Nagy M. Fawzy, AssistantProfessor of psychiatry, Department of Psychiatry,Faculty of Medicine, Zagazig University, Zagazig, EgyptTel: +0106895396;e-mail: [email protected]

Received 16 March 2011Accepted 19 May 2011


2011, 18:231–236

Background

Somatization in children consists of the persistent experience and complaints of

somatic distress that cannot be fully explained by a medical diagnosis. The aim of

this study was to determine the prevalence and risk factors of unexplained somatic

symptoms and their relation to emotional symptoms in school-aged children.


The sample included 294 children recruited from four primary schools of Sharkia

Governorate. All the children were between 6 and 12 years of age, were from both

sexes, and had no social limitation. All participants were subjected to psychiatric

assessment for somatic symptoms by the Children’s Somatization Inventory. They were

also assessed for depression by the Child Depression Inventory and for anxiety by the

Revised Children’s Manifest Anxiety Scale.

Results

The prevalence rate of somatic symptoms was 13%, that of depression was 9%,

and that of anxiety was 21%. Somatic symptoms were correlated with emotional

symptoms.

Conclusion

This study concluded that there was a high rate of somatic and emotional symptoms

in school children that were interrelated with sociodemographic characteristics.

Keywords:

children, emotional symptoms, pain, unexplained somatic symptoms


IntroductionPhysical symptoms or painful complaints of unknown

etiology are fairly common among children [1,2]. In the

general population, 2–10% of children have been

documented as having recurrent pains or gastrointestinal

(GI) symptoms, or have been described as sick [3,4].

Somatization in children consists of the persistent

experience and complaints of somatic distress that cannot

be fully explained by a medical diagnosis. The somatic

symptoms in children with somatization disorder become

the main focus of their attention and often interfere with

school, home life, and peer relationships [5]. Symptoms

are often medically unexplained and linked to psycholo-

gical problems [1,3]. Complaints of limb pain, aching

muscles, fatigue, and neurological symptoms, especially

pseudoseizures, appear to increase with age [6]. Accord-

ing to the latest edition of the Diagnostic and StatisticalManual of Mental Disorders, Fourth Edition-Text Revision

(DSM-IV-TR; American Psychiatric Association) [7], so-

matic complaints as seen in somatization disorder can be

allocated into four domains: (a) pain symptoms (e.g.

headache, stomachache, back pain), (b) GI symptoms

(e.g. nausea, vomiting, diarrhea), (c) sexual symptoms

(e.g. sexual indifference, erectile dysfunction, irregular

menses), and (d) pseudoneurological symptoms (e.g.

conversion symptoms such as impaired coordination,

paralysis, loss of touch sensation). Eight criteria were

required for a diagnosis (four different pain sites, two GI

symptoms, one sexual symptom, and one pseudoneur-

ological symptom). Somatization often occurs in response

to psychosocial stress and generally persists even after the

acute stressor has resolved, resulting in the belief by the

child and family that the correct medical diagnosis has

not yet been found [8]. Psychological stress may result in

numerous physical effects, including the following: stress

affects immune responses through the hypothalamus–

pituitary–adrenal axis and the sympathetic nervous

system, and neurotransmitters are released, triggering

various GI responses such as gut dysmotility and

recurrent abdominal pain. Nonspecific inflammatory

changes can be found on biopsy specimens at all levels

of the GI tract, suggesting that immunomodulation plays

a role in the pathogenesis of the symptom[6]. Emotional

distress can cause muscular pains and headaches through

increased muscular tension. Psychologically induced

changes in behavior, such as compulsive activity or

prolonged bed rest, lead to secondary physiologic changes

and attendant symptoms [6]. Thus, patients and families

may continue to seek repeated medical treatment after


2090-5408 & 2011 Okasha Institute of Psychiatry, Ain Shams University DOI: 10.1097/01.XME.0000405086.70462.8e

being informed that no acute medical illness has been

found and that the symptoms cannot be fully explained

by a medical diagnosis. It is generally well accepted that

stress and worry can take a physical toll and can be the

hidden source of chest pain, headache, stomachache, and

backache [9]. Somatic complaints can be the presenting

and/or comorbid symptoms of childhood depression and

anxiety disorders [10,11]. Conscious and unconscious

worries can lead to somatic symptoms with a spectrum of

degrees of severity in almost every organ system [8].

Even though symptoms are often medically unexplained,

they can lead to considerable impairment in the child’s

life, affecting development, school, and social adjust-

ment [12]. Associations with psychological symptoms are

especially marked in children with multiple somatic

complaints [13.] Many prepubertal children may experi-

ence psychological distress in the form of somatization

symptoms. Headache and recurrent abdominal pain are

frequently reported painful somatic symptoms in children

younger than 13 years of age, [14] with 10–30% of school-

aged children and adolescents reporting symptoms as

often as weekly [15,16]. The morbidity associated with

unexplained pediatric somatic complaints can be sig-

nificant. These children are more likely to be considered

sick or health-impaired by parents, to be absent from

school, and to perform poorly in academics. Somatoform

disorders have been associated with impairment in

functioning and with suffering for the child and family.

They also lead to costly and dangerous medical investiga-

tions and treatments [8]. Hence, the aim of this study

was to determine the prevalence and risk factors of un-

explained somatic symptoms and their relation to emo-

tional symptoms in a sample from school-aged children of

Sharkia Governorate, Egypt.

Participants and methodsThis study was conducted from 1 April 2010 to 1

December 2010. The study sample included 294 children

recruited from three general schools and one private

primary school in Sharkia Governorate. Children included

in the study were between 6 and 12 years of age, were

from both sexes, with no social and educational limita-

tions, and lived with their parents. Children with a past

history of psychotic or physical disorder or any chronic

disease were excluded from the study. An informed

written permission was obtained from the Ministry of

Education of Sharkia Governorate, and a written consent

was received from the parents or legal guardians of

participating children. Oral permission was also obtained

from the children.

Complete physical examination and relevant investiga-

tions were conducted as indicated to exclude any organic

disease. Those patients with explainable organic causes

for the symptoms were excluded from the evaluation.

Pubertal stage was assessed using the Tanner criteria [17].

Of the children, 209 (71%) were prepubertal (Tanner

stage 1) and 85 (29%) were early pubertal (Tanner stages

2 and 3).

The mental state of the participants was examined

according to the DSM-IV-TR criteria. A specially

designed semistructured interview, derived from the

Psychiatric Department sheet of Zagazig University

(Egypt), to obtain clinical data, to confirm diagnosis,

and to know family history of psychiatric disorders was

conducted.

The children’s somatic symptoms were detected using

the Children’s Somatization Inventory (CSI), which

covers a range of somatic complaints and produces four

scales such as (a) pseudoneurological, (b) cardiovascular,

(c) GI, and (d) pain/weakness problems. The CSI [18] is

a self-report questionnaire comprising 35 items requiring

individuals to report the extent to which they experi-

enced each symptom in the previous 2 weeks (0 = not at

all, 1 = a little, 2 = somewhat, 3 = a lot, 4 = a whole

lot) [19–21]. Two scores are derived as follows: (a) the

CSI total score (maximum = 140), which is the sum of all

items reflecting both the range and intensity of

experienced symptoms; and (b) the somatization score

(maximum = 26) is the sum of ‘a lot’ or a ‘whole lot’

responses to the 26 items in the DSM-IV somatization

disorder. The CSI has been shown previously to have ade-

quate good internal reliability with coefficient a values in

excess of 0.90 and adequate construct validity through

moderate correlations (0.20–0.43) [20,21].

Depression in children was detected using the Child

Depression Inventory, which is a standardized self-report

questionnaire of depression [22]. It has been developed

for children and young people of 6–17 years of age. The

Child Depression Inventory includes 27 items, each

scored on a 0–2 scale (from ‘not a problem’ to ‘severe’),

comprising symptoms observed for the previous 2 weeks.

The total score ranges between 0 and 54, and a score of

19 has been found to indicate the likelihood of a

depressive disorder [23].

Anxiety was determined using the Revised Children’s

Manifest Anxiety Scale, which is a standardized 37-item

self-report questionnaire for children of 6–19 years of

age [24]. It measures the presence or absence of anxiety-

related symptoms (‘yes/no’ answers) in 28 items related

to anxiety and in nine items pertaining to lies. A cutoff

total score of 18 has been found to predict the presence

of anxiety disorder in an Arab population [25].

Statistical analyses

The w2 analysis was used to compare the sociodemo-

graphic characteristics of the groups.

a ¼X ðO�EÞ

E

2

whereX¼summation;

O ¼observed value;

E ¼expected value

Somatic symptoms, depression, and anxiety were corre-

lated according to Pearson’s correlation and analyzed

using a personal computer using a statistical software


program Statistical Package for Social Studies(SPSS,

version 13.0, SAS Institute, Cary, NC, USA, 2002) [26].

ResultsThe prevalence rate of somatic symptoms was 13%, that

of depression was 9%, and that of anxiety was 21% in our

children. Table 1 represents the sociodemographic

characteristics of the study group. The mean age of the

study group was 8.7 ± 1.2 years (range = 6–12 years).The

female-to-male ratio was 1 : 3. The majority of the

children were from urban areas (70%), belonged to a

good home atmosphere (83%), went to public schools

(92%), had good teacher communication (56%), em-

ployed parents (75%), and good family cohesion (51%).

Abdominal pain (70%) and headache (67%) were the

dominant presenting symptoms among somatoform dis-

orders, followed by low energy (59%), nausea (50%), sore

muscle (47%), weakness (41%), chest pain (40%), and

lower back pain (38%). The mean total score of CSI was

22.1 ± 15.5. Somatic symptoms were significantly higher

in girls, in children with unemployed parents, and in

children who studied in private schools (Pr0.0001 for

each), but no significant difference in somatic symptom

frequency was observed on the basis of residence, home

atmosphere, teacher communication, and family cohesion

(Table 2). However, depression was significantly higher

in children who lived in urban areas (P = 0.03) with no

effect of other demographic data (Table 3). Anxiety was

significantly higher in girls, in children with unemployed

parents, and in children who lived in urban areas

(P = 0.0001, P = 0.0001, P = 0.007, respectively) but no

significant difference was seen in somatic symptom

frequency according to type of school, home atmosphere,

teacher communication, and family cohesion (Table 4).

Correlation was significantly positive between somatic

symptoms, depression scores, and anxiety scores and

between depression and anxiety scores (Table 5).

DiscussionResearch on somatization or functional disorders, char-

acterized by the subjective study of physical symptoms

in the absence of clear physical pathology, is limited in

young children [6].

This study found that the prevalence rate of somatic

symptoms was13%, that of depression was 9%, and that of

Table 1 Sociodemographic data of the study group

Variable N [294 (100%)]

SexMale 228 78%Female 66 22%

ResidenceRural 88 (30)Urban 206 (70)

Home atmosphereGood 245 (83)Bad 49 (17)

School statePublic school 270 (92)Private school 24 (8)

Teacher communicationGood 164 (56)Bad 130 (44)

Parents’ occupationEmployed 222 (75)Unemployed 72 (25)

Family cohesionGood 154 (51)Bad 140 (49)

Pubertal stagePrepubertal 209 (71)Early pubertal 85 (29)

Age (mean ± standard deviation) 8.7 ± 1.2 (range: 6–12)

Table 2 Comparison between children’s somatic symptom

percentage according to sociodemographic data

Variable

Somatic symptomgroup

[n = 38 (13%)]

Normal group[n = 256(87%)] w

Pvalue

SexMale 20 (9) 208 (91) 15.5 0.000*Female 18 (27) 48 73%

ResidenceRural 8 (9) 80 (91) 1.46 0.200Urban 30 (14) 176 (86)

Home atmosphereGood 34 (14) 211 (86) 1.18 0.276Bad 4 (8) 45 (92)

School typePublic

school29 (11) 241 (89) 14.02 0.000*

Privateschool

9 (37) 15 (63)

Teacher communicationBad 17 (13) 113 (87) 0.000 0.944Good 21 (13) 143 (87)

Parents’ occupationEmployed 16 (7) 206 (93) 26.33 0.000*Unemployed 22 (30) 50 (70)

Family cohesionGood 19 (12) 135 (88) 0.10 0.752Bad 19 (15) 121 (85)

*Po0.001 (highly significant).

Table 3 Comparison between children’s depression percentage

according to sociodemographic data

Variable

Depressed[n = 26(9%)]

Normal[n = 268(91%)] w

Pvalue

SexMale 20 (9) 208 (91) 0.01 0.935Female 6 (9) 60 91%

ResidenceRural 3 (3) 85 (97) 4.600 0.031*Urban 23 (11) 183 (89)


School typePublic school 24 (11) 246 (99) 0.010 0.926Private school 2 (9) 22 (91)


Parents’ occupationEmployed 20 (10) 202 (90) 0.030 0.861Unemployed 6 (9) 66 (91)


*Po0.05 (significant).

Prevalence and risk factors Fawzy et al. 233

anxiety was 21% in studied children. Similarly, Garber

et al. [19] found that more than half of the school-aged

children reported experiencing at least one serious

somatic symptom, with 15.2% endorsing four or more

serious complaints. These rates were somewhat lower

than those found in another study by Rask et al. [27], who

found that the prevalence of somatic symptoms was

23.2% in a study on children of 5–7 years of age in

Copenhagen. This difference may be due to the smaller

sample size, older children, higher sympathy, and social

support in eastern countries than in western countries.

The possibility of false results in the Arabic community is

higher because of the stigma that parents attach to

reporting that their children suffer from a psychiatric

disorder. The increased reporting of somatic symptoms in

younger children may be due to an inability to verbalize

emotional distress [28]. This study observed significantly

higher somatic symptoms in girls, in children with

unemployed parents, and in children studying in private

schools. Before puberty there was no difference in the

prevalence of somatic symptoms between boys and

girls [8]. However, adolescent girls tended to report

nearly twice as many functional somatic symptoms

compared with adolescent boys [29]. In this study, 29%

of studied children were in early pubertal stage. The

physiological and neurobiological changes associated with

puberty may play a role in these sex and age differences.

In fact, experts on adolescent development have long

considered puberty as a precursor of mood and behavioral

changes [30]. Studies have found that advanced pubertal

status in girls is associated with the frequency of somatic

symptoms [31]. With regard to unemployed parents and

type of school, we found that children who study in

private schools had higher somatic symptoms. Long-

itudinal data suggest that daily examination stressors in

private schools and family contexts produce greater

somatic distress in children with low social competence,

and that social rewards maintain somatic symptoms,

especially when children have low self-esteem. Social

disadvantage may compound these effects, particularly in

children older than 7 yearsof age [32]. In addition, we did

not find significant difference in the frequency of somatic

symptoms on the basis of residence, home atmosphere,

teacher communication, and family cohesion. This is in

contrast to the study by Brown et al. [33], who suggested

that patients with somatization disorder tended to have

been raised in emotionally cold and unsupportive families

that were characterized by chronic emotional and physical

abuses. The results of this study show that anxiety was

significantly higher in girls, in children with unemployed

parents, and in children who lived in urban areas. Our

results were consistent with some previous studies

[19,28]. Our study found significant positive correlations

between somatic and emotional symptoms, indicating

adequate construct validity of the CSI. This in agreement

with the result of Muris et al. [34] and Toft et al. [35], who

reported that anxiety was significantly positively asso-

ciated with somatic symptoms. These results indicate

that there might be common vulnerability factors in

childhood anxiety and somatization symptoms. However,

Karvonen [36] found that anxiety was independently

associated with somatization symptoms, whereas mood

disorders were not. However, Egger et al. [37] found that a

quarter of respondents recognized a link between somatic

symptoms and stress. These groups had higher somatic

and emotional symptom scores, which is in line with the

notion of increased stress reactivity in children with

functional somatic symptoms [38,39]. In addition,

research suggests that girls with anxiety disorders were

five times more likely to report somatic complaints and

had three times the prevalence of headaches compared

with girls not diagnosed with an anxiety disorder [37].

Furthermore, children with comorbid disorders (i.e.

anxiety, depression) reported more frequent somatic

complaints compared with children without comorbid-

ity [40]. The findings of this study indicate that children

with comorbid anxiety and depression report more

somatic symptoms. Hence, asking about the effect of

stress on somatic complaints is a helpful screening tool for

young people at high risk for somatization. Children’s

limbic hypothalamic–pituitary–adrenocortical and auto-

nomic nervous systems have demonstrated hyperrespon-

sivity to physically aversive events and psychologically

stressful situations [41]. Heightened physiological reac-

tivity is associated with internalizing behaviors in early

and middle childhood [42]. In the clinical setting,

children with somatic symptoms tend to be described

Table 4 Comparison between anxiety percentage according to

sociodemographic data

VariableAnxiety [n =62 (21%)]

Normal [n =232 (79%)] w P value

SexMale 37 (16) 191 (84) 13.73 0.000*Female 25 (37) 41 (63)

ResidenceRural 10 (11) 78 (89) 7.14 0.007*Urban 52 (25) 154 (75)


School typePublic school 58 (21) 212 (79) 0.31 0.579Private school 4 (17) 20 (83)


Parents’ occupationEmployed 36 (16) 186 (84) 12.93 0.000*Unemployed 26 (36) 46 (64)


*Po0.001 (highly significant).

Table 5 Correlation between scores of somatic symptoms,

depression, and anxiety

Variable Somatic symptoms Depression Anxiety

Somatic symptoms 1 0.545a 0.654a

0.028 0.011Anxiety 0.654a 0.721a 1

0.011 0.019Depression 0.545a 1 0.721a

0.028 0.019

aStatistically significant according to r value.


as conscientious or obsessive (perfectionistic), sensitive,

insecure, and anxious [2]. Children with these tempera-

mental vulnerabilities are hypothesized to be at risk for

developing anxiety disorders and are more likely to

generate distress responses to potentially threatening or

uncertain stimuli [43].

ConclusionThis study concludes that there are high rates of somatic

symptoms and emotional disorders among Egyptian

school children and these are strongly interrelated with

sociodemographic characteristics.

Recommendation

Future research should develop and establish a new

construct of child somatization that is easily quantifiable

and based upon information drawn from a wide variety of

independent sources such as parents’ interview and self-

report, child interview, and several child medical mea-

sures. Somatization can be considered as an important

clinical and socioeconomic problem. Thus, early diagnosis

and treatment by primary healthcare physicians, rather

than psychiatrists, will lead to improved clinical outcomes

and physical functioning and reduce healthcare costs.


References1 Campo JV, Fritsch SL. Somatization in children and adolescents. J Am Acad

Child Adolesc Psychiatry 1994; 33:1223–1235.

2 Garralda ME. Somatisation in children. J Child Psychol Psychiatry1996; 37:13–33.

3 Apley J. The child with abdominal pains. 2nd ed. Oxford: Blackwell ScientificPublications; 1975.

4 Goodman JE, McGrath PJ. The epidemiology of pain in children and ado-lescents: a review. Pain 1991; 46:247–264.

5 Garralda ME. Practitioner review: assessment and management of somati-sation in childhood and adolescence: a practical perspective. J Child Psy-chol Psychiatry 1999; 40:1159–1167.

6 Walker LS, Greene JW. Negative life events and symptom resolution in pe-diatric abdominal pain patients. J Pediatr Psychol 1991; 16:341–360.

7 American Psychiatric Association. Diagnostic and Statistical Manual ofMental Disorders. 4th ed. Washington: American Psychiatric Publication;2000.

8 Campo JV, Jansen McWilliams L, Comer DM, Kelleher KJ. Somatization inpediatric primary care: association with psychopathology, functional impair-ment and use of services. J Am Acad Child Adolesc Psychiatry 1999;38:1093–1101.

9 Livingston R, Taylor JL, Crawford SL. A study of somatic complaints andpsychiatric diagnosis in children. J Am Acad Child Adolesc Psychiatry 1988;27:185–187.

10 Wilens TE. Depression in the medically ill child. In: Jellinek MS, Herzog DB,editors. Massachusetts general hospital psychiatric aspects of generalhospital pediatrics. Littleton, Mass: Yearbook Medical Publishers; 1990.pp. 263–271.

11 Sadeh A, Hayden RM, McGuire JP, Sachs H, Civita R. Somatic, cognitiveand emotional characteristics of abused children in a psychiatric hospital.Child Psychiatry Hum Dev 1994; 24:191–200.

12 Roth Isigkeit A, Thyen U, Stoven H, Schwarzenberger J, Schmucker P. Painamong children and adolescents: restrictions in daily living and triggeringfactors. Pediatrics 2005; 115:e152–e162.

13 Escobar JI, Burnam MA, Karno M, Forsythe A, Golding JM. Somatization inthe community. Arch Gen Psychiatry 1987; 44:713–718.

14 Garber J, Zeman J, Walker LS. Recurrent abdominal pain in children: psy-chiatric diagnoses and parental psychopathology. J Am Acad Child AdolescPsychiatry 1990; 29:648–656.

15 Larsson BS. Somatic complaints and their relationship to depressivesymptoms in Swedish adolescents. J Child Psychol Psychiatry 1991;32:821–832.

16 Tamminen TM, Bredenberg P, Escartin T, Kaukonen P, Puura K, Rutanen M,et al. Psychosomatic symptoms in preadolescent children. PsychotherPsychosom 1991; 56:70–77.

17 Tanner JM, Whitehouse RH. Clinical longitudinal standards for height,weight, height velocity, weight velocity and stages of puberty. Arch Dis Child1976; 51:170–179.

18 Walker LS, Greene JW. Children with recurrent abdominal pain and theirparents: more somatic complaints, anxiety and depression than other patientfamilies? J Pediatr Psychol 1989; 14:231–243.

19 Garber J, Walker LS, Zeman J. Somatization symptoms in a communitysample of children and adolescents: further validation of the children’s so-matization inventory. Psychol Assess 1991; 3:588–595.

20 Litcher L, Bromet E, Carlson G, Gilbert T, Panina N, Golovakha E, et al.Ukrainian application of the children’s somatization inventory: psychometricproperties and associations with internalizing symptoms. J Abnorm ChildPsychol 2001; 29:165–175.

21 Meesters C, Muris P, Ghys A, Reumerman T, Rooijmans M. The children’ssomatization inventory: further evidence for its reliability and validity in apediatric and a community sample of Dutch children and adolescents.J Pediatr Psychol 2003; 28:413–422.

22 Kovacs M. The children’s depression, inventory (CDI). Psychopharmacol Bull1985; 21:995–998.

23 Gharib A. Arabic version of CDI. Cairo: El Nahda El Masrya; 1985.

24 Reynolds CR. Concurrent validity of ‘‘what i think and feel:’’the revisedchildren’s manifest anxiety scale. J Consult Clin Psychol 1980; 48:774–775.

25 Thabet AA, Vostanis P. Social adversities and anxiety disorders in theGaza Strip. Arch Dis Child 1998; 78:439–442.

26 SPSS. Statistical package for social studies. Version 13.0. SAS Institute:2002; Cary, NC, USA.

27 Rask CU, Olasen EM, Elberling H, Christensen MF, Ornbol E, Fink P.Functional somatic symptoms and associated impairment in 5–7-year-oldchildren: the copenhagen child cohort 2000. Eur J Epidemiol 2009;24:625–634.

28 Shapiro CM. Alexithymia-a useful concept for all psychiatrists? J PsychosomRes 1996; 41:503–504.

29 Achenbach TM, Conners CK, Quay HC, Verhulst FC, Howell CT. Replicationof empirically derived syndromes as a basis for taxonomy of child/adolescentpsychopathology. J Abnorm Child Psychol 1989; 17:299–323.

30 Susman EJ, Reiter EO, Ford C, Dorn LD. Work group I: developing modelsof healthy adolescent physical development. J Adolesc Health 2002;31 (6 Suppl171–174.

31 Rhee H. Relationships between physical symptoms and pubertal develop-ment. J Pediatr Health Care 2005; 19:95–103.

32 Fearon P, Hotopf M. Relation between headache in childhood and physicaland psychiatric symptoms in adulthood: National Birth Cohort study. BMJ2001; 322:1145.

33 Brown RJ, Schrag A, Trimble MR. Dissociation, childhood interpersonaltrauma and family functioning in patients with somatization disorder. Am JPsychiatry 2005; 162:899–905.

34 Muris P, Meesters C. Children’s somatization symptoms: correlations withtrait anxiety, anxiety sensitivity and learning experiences. Psychol Reports2004; 94:1269–1275.

35 Toft T, Fink P, Oernboel E, Christensen K, Frostholm L, Olesen F. Mentaldisorders in primary care: prevalence and co-morbidity among disorders:results from the Functional Illness in Primary Care (FIP) study. Psychol Med2005; 35:1175–1184.

36 Karvonen JT. Somatization in young adults. The Northern Finland 1966 BirthCohort Study. Acta Univ Oul 2007.

37 Egger HL, Costello EJ, Erkanli A, Angold A. Somatic complaints andpsychopathology in children and adolescents: stomach aches, muscu-loskeletal pains, and headaches. J Am Acad Child Adolesc Psychiatry 1999;38:852–860.

38 Beck JE. A developmental perspective on functional somatic symptoms.J Pediatr Psychol 2008; 33:547–562.

39 Vila M, Kramer T, Hickey N, Dattani M, Jefferis H, Singh M. Assessment ofsomatic symptoms in British secondary school children using the children’ssomatization inventory (CSI). J Pediatr Psychol 2009; 34:989–998.

40 McCauley E, Carlson GA, Calderon R. The role of somatic complaints in thediagnosis of depression in children and adolescents. J Am Acad ChildAdolesc Psychiatry 1991; 30:631–635.

41 Gunnar MR, Bruce J, Hickman SE. Salivary cortisol response to stress inchildren. Adv Psychosom Med 2001; 22:52–60.

42 Bauer AM, Quas JA, Boyce WT. Associations between physiological re-activity and children’s behavior: advantages of a multisystem approach.J Dev Behav Pediatr 2002; 23:102–113.

43 Dorn LD, Campo JC, Thato S, Dahl RE, Lewin D, Chandra R, et al. Psy-chological comorbidity and stress reactivity in children and adolescents withrecurrent abdominal pain and anxiety disorders. J Am Acad Child AdolescPsychiatry 2003; 42:66–75.

Prevalence and risk factors Fawzy et al. 235

Psychological manifestations in adolescents with thalassemiaHani Hameda, Osama Ezzatb and Tamer Hifnawyc

Departments of aPsychiatry, bPediatrics andcPublic Health and Community, Beni-Sueif University,Beni-Sueif, Egypt

Correspondence to Hani Hamed, Departments ofPsychiatry, Beni-Sueif, EgyptTel: + 20106071194;e-mail: [email protected]

Received 2 April 2011Accepted 21 May 2011


2011, 18:237–244

Objective

Beta-thalassemia major and its complications have a significant psychological impact,

causing emotional burden, hopelessness, and difficulty with social integration.

Patients and methods

This study was an observational analytical case–control study that included

30 adolescents with a diagnosis of thalassemia, ‘Cases’, and another group of

30 adolescents from the gastrointestinal outpatient clinic, ‘Controls’. All participants

were subjected to a semistructured interview, the Patient Health Questionnaire,

the Hospital Anxiety Depression Scale, the Middlesex Hospital Questionnaire, and

the McGill Quality of Life Questionnaire.

Results

Thalassemic adolescents showed statistically significant higher depressive symptoms

(Po0.001) and higher anxiety symptoms (Po0.001) compared with adolescents from

the gastrointestinal outpatient clinic. There was a highly significant difference in the

results of the Middlesex Hospital Questionnaire (Po0.001). Thalassemic adolescents

showed significantly higher levels of anxiety, phobia, obsession, somatization,

depression, and hysteria. Thalassemic adolescents showed significantly lower levels

in different aspects of quality of life, total, general, physical, and emotional, with regard

to the McGill Quality of Life Questionnaire (Po0.001).

Conclusion

Depressive and anxiety symptoms were more prevalent among adolescents with

thalassemia. In addition, in the same group, there was a higher degree of free floating

anxiety, phobic anxiety, obsessive symptoms, somatic symptoms, depressive

symptoms, and hysteria. Quality of life was highly affected among adolescents

with thalassemia.

Keywords:

adolescents, depression, thalassemia


IntroductionThalassemia was first described by Cooley and Lee in 1952

in several Italian children as a severe anemia with spleen and

liver enlargement, skin discoloration, and bony changes.

Great strides in management and intervention have not

been matched by progress in psychosocial rehabilitation [1].

Thalassemia is one of the most common genetic disorders

worldwide [2].

Beta-thalassemia major is a disorder characterized by the

defective production of hemoglobin and excessive de-

struction of red blood cells. Hemoglobin comprises four

protein subunits, that is, two a and two b. Genetic

mutations in the gene encoding for the b subunits of the

protein result in reduced or totally absent synthesis of the

globin b-chains, leading to the formation of abnormal

hemoglobin or even to the absence of b hemoglobin. This

defect causes an abnormal development of red blood cells

and ultimately anemia, which is the characteristic

symptom of thalassemia. The disease is prevalent among

Mediterranean individuals, the highest frequency is found

in the Greek islands, Italy (lower Po valley, Sicily, and

Sardinia), and Asia, whereas the highest concentration of

individuals carrying the genetic mutations underlying

thalassemia is found in the Maldives [3].

Rapid physical changes are accompanied by significant

psychological changes relating particularly to the way in

which the adolescent perceives himself or herself, this

can be a turbulent time. Parents and others, especially

sports coaches and teachers, who work with adolescents

must be very sensitive to both the physical and the

psychological changes taking place during this period [4].

For an adolescent with an infirmity or chronic illness, and for

his family, there exist specific problems in addition to those

encountered by a healthy adolescent. The painful awareness

of social, professional, and relational barriers is reactivated.

The feeling of failure and helplessness, low selfesteem, and

anger at being a victim represent a supplementary affective

burden for the adolescent and his family [5].

Thalassemia is one of the inherited hemoglobinopathies

responsible for a large number of chronic illnesses

throughout the world. The clinical picture of thalassemia



presents a wide range of problems. The treatment involves

periodic red blood cell transfusion, daily iron chelation, and

sometimes spleenectomy. It poses a very severe burden for

patients with thalassemia and their families [6].

Beta-thalassemia is a chronic illness that poses excessive

psychological burden to children and their families as

clinical manifestations usually develop early in life and

invasive procedures cause considerable suffering [7].

Especially in children, b-thalassemia major and its

complications have a significant psychological impact,

causing emotional burden, hopelessness, and difficulty

with social integration [8].

Patients with thalassemia feel different from their peers

and develop negative thoughts about their life, a sense of

guilt, increased anxiety, and low selfesteem; their behavior-

al profile is similar to normal individuals, but many of them

may develop severe psychosocial problems because of

difficulties in complying with the painful chelation; male

patients, in particular, show oppositional defiant disorder.

Within the family, concerns for the future of a thalassemic

child may contribute to worsening of relationships among

members, and to increase marginalization and isolation [9].

In addition, quality of life (QoL), which is defined as an

individual’s perception of their position in life in the

context of the culture and value systems in which they

live, and in relation to their goals, and expectations, is

often limited by the chronic illness [10].

Many neurotic symptomatologies have been found in

children with thalassemia major in different surveys.

Depressive moods and anxiety were diagnosed in children

with thalassemia major [5].

Screening for anxiety and depression in patients with

thalassemia is essential. Thus, appropriate treatment of

these conditions may improve patients’ health-related

QoL [11].

The impact of thalassemia major and intermedia and their

associated complications of QoL are largely known [12].

Psychological support therefore seems to help reduce the

emotional burden of children with b-thalassemia major

and their families [13].

Psychosocial support aimed at reducing emotional dis-

tress, improving compliance to chelation therapy, and

strengthening the coping strategies for better integration

into daily life is therefore necessary. Aydinok et al. [13]

found that the frequency of psychopathology is higher in

patients with thalassemia compared with the normal

population, this supports the need for lifelong psycholo-

gical support to prevent mental health issues among

patients with thalassemia and their parents.

The recognition and management of the psychological

problems that accompany chronic physical illnesses

including thalassemia would optimize treatment out-

comes and QoL [14].

In Egypt, thalassemia is considered the most common

genetically determined hemolytic disease. Its high

prevalence causes a significant burden on health re-

sources. A few studies of children with thalassemia have

shown a heightened risk of developmental and behavioral

problems. However, the results vary from mild behavioral

problems to obvious psychiatric disorders.

The objectives of this study were as follows: (a) to study

in depth the psychological effect of thalassemia; (b) to

evaluate the presence of psychiatric symptoms (including

depressive symptoms, anxiety, phobic anxiety, obsessive

symptoms, somatic symptoms, and hysteria) among

adolescents with thalassemia; and (c) to analyze QoL of

adolescents with thalassemia.

Patients and methodsPatients

This is an observational analytical case–control study,

which includes 30 adolescents with a diagnosis of

thalassemia, ‘Cases’, (patients regularly undergoing trans-

fusion every 3 weeks and receiving regular oral chelation

treatment) and another group of 30 adolescents from a

gastrointestinal outpatient pediatric clinic who com-

plained of acute gastroenteritis, ‘Controls’. Patients in

this study were selected from the outpatient pediatric

clinic one day per week in the period from January to May

2010. Clearance from the research ethics committee was

obtained and all enrolled children provided consent to

participate in addition to legal guardian written consent.

Inclusion criteria

The inclusion criteria in this study were as follows:

(1) Both sexes;

(2) Age between 12 and 19 years;

(3) Agreeing to participate in this study, by obtaining an

informed consent from the legal guardian and the

child’s consent to participate.

Exclusion criteria

The exclusion criteria in this study were as follows:

(1) Legal guardian or child Refusal to participate in

this study;

(2) Current psychiatric disorder and other chronic

medical conditions.

Hemoglobin fetal was determined in all participants

included and cases were defined as being hemoglobin

fetal positive, and controls were confirmed as being

hemoglobin fetal negative.

Methods

Participants of this study were subjected to the following:

Semistructured interview

Patients and controls were interviewed using a psychiatric

history-taking sheet designed at the Department of

Psychiatry, Cairo University (Egypt). It includes detailed


developmental, family, educational, and past history. It

also includes a mental state examination.

Patient Health Questionnaire [15]

The Patient Health Questionnaire (PHQ) is a self-

administrative version of the PRIME-MD diagnostic

instrument for common mental disorders. The PHQ-9

is the depression module, which scores each of the

Diagnostic and Statistical Manual of Mental Disorders? -

IV criteria as 0 (not at all) to 3 (nearly every day). It has

been validated for use in Primary Care. It is a highly valid

tool. Validity has been assessed against an independent

structured mental health professional interview; a PHQ-9

score greater than 10 has a sensitivity of 88% and a

specificity of 88% for major depression.

Hospital Anxiety and Depression Scale [16]

The Hospital Anxiety and Depression Scale (HADS) is a

14-item selfreport measure to assess anxiety and depres-

sive symptoms in a simple way. Statements 2, 4, 6, 8, 11,

12, and 14 are for anxiety symptoms and statements 1, 3,

5, 7, 9, 10, and 13 are for depressive symptoms. Each

statement scores from 3 (yes definitely) to 0 (not at all)

(the score is reversed for statements 7 and 10), with

higher scores reflecting a higher occurrence of symptoms

of anxiety and depression.

Middlesex Hospital Questionnaire [17]

The Middlesex Hospital Questionnaire comprises 48

items grouped into six subscales covering the following

psychiatric symptoms: free floating anxiety, phobic

anxiety, obsessive symptoms, somatic symptoms, depres-

sive symptoms, and hysteria. The items are answered

as Yes, No, Sometimes, Never, and Little. The response

to each item is scored as 2, 1, or 0. A total score of 9

or more in any subscale is considered sufficient to

indicate that the patient has clinically significant

psychiatric symptoms. It was translated into Arabic by

Al Rakhawi et al. [18].

McGill Quality of Life Questionnaire [19]

The McGill Quality of Life Questionnaire comprises two

multiitem scales. These include three subscales: general,

physical, and emotional. It includes 17 questions. Each

question in this questionnaire begins with a statement,

followed by two opposite answers. Numbers extend from

one extreme answer to its opposite. Higher scores

indicate a higher (better) level of QoL. Thus, a high

score for the general and emotional subscales and a high

score for the physical subscale represent a high level of

symptomatology/problem.

All scales were applied in the Arabic language; first, all

scales were translated into Arabic and then back

translated into English and revised by the study team.

Tools were applied on 10 patients in a pilot study by two

senior medical doctorate (MD) staff separately.


Data were collected, coded, and analyzed using SPSS

software (Statistical Package for the Social Sciences;

SPSS Inc., Chicago, Illinois, USA)(version 16) under

Windows XP. The w2-test was used for the analysis of

categorical data. The Pearson product–moment correla-

tion coefficients ‘r’ were calculated for the different

parameters investigated [20]. The level of significance

was set at Po0.05.

ResultsSociodemographic and clinical data

Age

The age distribution in both the groups is shown

in Table 1.

Sex

The sex distribution in both groups is shown in Table 2.

Education

Education distribution in both groups is shown in Table 3.

Family history of psychiatric illness

The family history of psychiatric illness distribution in

both groups is shown in Table 4.

Table 3 Education distribution in both groups

Patients Controls PEducation Number (%) Number (%)

Illiterate 6 (20) 2 (6.7) 0.047Primary students 8 (26.7) 18 (60)Preparatory students 16 (53.3) 10 (33.3)Total 30 (100) 30 (100)

Table 2 Sex distribution in both groups

Patients Controls

Sex Number (%) Number (%) P

Female 14 (46.7) 19 (63.3) 0.194Male 16 (53.3) 11 (36.7)Total 30 (100) 30 (100)

Table 1 Age distribution in both groups

Age (years) Minimum Maximum Mean Standard deviation P

Patients 12.00 15.00 13.03 1.13 1.18Controls 12.00 15.00 12.67 0.96

Table 4 Family history of psychiatric illness distribution in

both groups

Patients Controls

Psychiatric illness Number (%) Number (%) P

Negative family history 27 (90) 28 (93.4) 0.503Family history of mood disorder 2 (6.7) 1 (3.3)Family history of psychotic disorder 0 (0.0) 1 (3.3)Family history of mental retardation 1 (3.3) 0 (0.0)Total 30 (100) 30 (100)

Psychological manifestations in adolescents Hamed et al. 239

Psychometric data

Patient Health Questionnaire-9

The PHQ-9 distribution in both groups is shown

in Table 5

Hospital Anxiety Depression Scale

The HADS distribution in both groups is shown

in Table 6.

Middlesex Hospital Questionnaire

The Middlesex Hospital Questionnaire distribution in


McGill Quality of Life Questionnaire

The McGill Quality of Life Questionnaire distribution in


Correlation studies

The correlation between the HADS and the Middlesex

Hospital Questionnaire is shown in Table 9.

The correlation between the Middlesex Hospital Ques-

tionnaire (depression) and the McGill Quality of Life

Questionnaire, general and physical subscale is shown

in Table 10.

DiscussionThere was no statistically significant difference between

the two groups with regard to age (P = 1.18) (Table 1).

Participants from both groups were selected from the

Pediatrics Outpatient Clinic.

There was no statistically significant difference between

the two groups with regard to sex (P = 0.194) (Table 2).

The majority of the patient group were men (53.3%).

This was consistent with the results of Sabry and

Salama [21], who found that 54% of patients with

thalassemia in their study in Egypt were men.

There was a statistically significant difference between

the two groups with regard to the educational level

(P = 0.047). Twenty percent of the individuals in the

patient group were illiterate, whereas only 6.7% of

adolescents in the control group were illiterate (Table 3).

This was in line with the study of Sabry and Salama [21];

a statistically significant difference was found in the

levels of education between the patient group and the

control group: 55% of cases did not attend school

compared with 12% of the control group. This could be

explained by the physical weakness caused by their

chronic illness, and frequent blood transfusion. Another

explanation for the lack of school attendance could be an

overprotective parenting style among Egyptian families

which is prevalent during the illness of their children.

Ratip et al. [22] found that, in the United Kingdom,

among 27 patients with thalassemia, 90% had to take time

off from school because of their medical condition. In

addition, thalassemia affected the scholastic performance

of 70% of Indian adolescents adversely [22].


both groups with regard to a family history of psychiatric

illness (P = 0.503). The majority of adolescents in both the

groups had a negative family history of psychiatric illness

(90% of the patient group, 93.4% of the control group)

(Table 4). This was similar to the study of Mazzone et al. [3],

who found a statistically significant difference between

a group of adolescents with thalassemia (28 patients) and

Table 5 Patient Health Questionnaire-9 distribution in

both groups

Patients Controls

PHQ-9 Number (%) Number (%) P

No depression 0 (0.0) 28 (93.3) o0.001Mild depression 4 (13.3) 2 (6.7)Moderate depression 16 (53.4) 0 (0.0)Moderate-to-severe depression 9 (33.3) 0 (0.0)Severe depression 0 (0.0) 0 (0.0)Total 30 (100) 30 (100)

PHQ-9, Patient Health Questionnaire-9.

Table 6 Hospital Anxiety Depression Scale distribution in

both groups

Patients Controls

Mean ± SD Mean ± SD P

HADS total 18.70 ± 3.41 0.30 ± 1.15 o0.001HADS anxiety 8.63 ± 1.65 0.30 ± 0.183 o0.001HADS depression 10.07 ± 2.12 0.28 ± 1.03 o0.001

HADS, Hospital Anxiety Depression Scale; SD, standard deviation.

Table 7 Middlesex Hospital Questionnaire distribution in

both groups

Patients Controls


Middlesex anxiety 9.23 ± 0.57 0.27 ± 0.83 o0.001Middlesex phobia 5.60 ± 1.89 0.00 ± 0.00 o0.001Middlesex obsession 3.57 ± 1.91 0.00 ± 0.00 o0.001Middlesex somatization 7.80 ± 1.90 0.17 ± 0.913 o0.001Middlesex depression 9.60 ± 1.48 0.63 ± 1.47 o0.001Middlesex hysteria 4.87 ± 1.83 0.00 ± 0.00 o0.001


Table 8 McGill Quality of Life Questionnaire distribution in both groups

Patients Controls


McGill Quality of Life Questionnaire total 83.57 ± 11.60 128.7 ± 1.93 o0.001McGill Quality of Life Questionnaire general 3.70 ± 0.92 9.90 ± 0.31 o0.001McGill Quality of Life Questionnaire physical 31.60 ± 2.75 3.33 ± 3.33 o0.001McGill Quality of Life Questionnaire emotional 48.60 ± 13.05 115.5 ± 3.99 o0.001



the control group (28 normal participantss) with regard to a

family history of psychological illness.


the two groups with regard to PHQ-9 (Po0.001). All

adolescents in the patients group were depressed (13.3%

had mild depression, 53.4% had moderate depression, and

33.3% had moderate-to-severe depression). In contrast,

only 6.7% of the participants in the control group had

mild depression (Table 5). This was in line with the study

of Sabry and Salama [21], who found that patients with

thalassemia have three times higher likelihood of having

depression. No patient with thalassemia was found to be

free of depressive symptoms compared with 70% of the

controls. Dysphoric moods and low selfesteem were

reported by the majority of children with thalassemia [23].

Woo et al. [24] reported that two-third of the patients

were worried about pain, death, and the unknown in a

sample of 22 children with thalassemia. This conclusion

was also supported by Khurana et al. [23], who reported

that chronic illnesses such as thalassemia give rise to

feelings of being different and inferior, with a consequent

loss of selfesteem and increased dependence. Facial

characteristics in thalassemia occur as a consequence of

the expansion of bones, particularly the skull and the jaw

bones. Anemia and iron overload in these patients often

lead to short stature and delayed puberty. Delayed

puberty is associated with other endocrine disturbances,

which can cause depression. They are likely to have

reduced self-esteem, feelings of difference, poor self-

image, being dependent, and anxiety over issues such as

pain and death. Huurre and Aro [25] observed that

patients with chronic illness limiting their daily life

experience more depression than those with illnesses that

do not limit daily life.


the two groups with regard to the HADS (Po0.001).

Adolescents with thalassemia showed significantly higher

levels of anxiety and depression than the control group

(mean = 8.63 ± 1.65, 10.07 ± 2.12 and mean = 0.30 ±

0.183, 0.28 ± 1.03, respectively) (Table 6). Depression

has been listed as a major cause of morbidity in

thalassemia. The rate of depression in patients with

thalassemia is higher than that in the controls [26]. In

addition, Saravi et al. [27] claimed that frequent blood

samplings for laboratory tests, multiple transfusions, and

frequent subcutaneous injections of iron chelator drugs,

which altogether can be considered severe stresses, are

likely to make patients susceptible to psychological

burdens namely depression and anxiety. They found that

the rate of depression among patients with thalassemia

was 14% in comparison with 5.5% in the control group

(Po0.001). Aydin et al. [28] concluded that Hopelessness

and Trait-Anxiety Scores were found to be significantly

higher in adolescents with thalassemia than in control

cases (Po0.01 and o0.05, respectively).


both groups with regard to the Middlesex Hospital

Questionnaire (Po0.001). Adolescents with thalassemia

showed significantly higher levels of anxiety, phobia,

obsession, somatization, depression, and hysteria (mean =

9.23 ± 0.57, 5.60 ± 1.89, 3.57 ± 1.91, 7.80 ± 1.90, 9.60 ±

1.48, and 4.87 ± 1.83, respectively) (Table 7). Moorjani

and Issac [5] reported higher total neuroticism, anxiety,

phobia, somatic anxiety, obsession, and depression in

patients with thalassemia than in the controls. Interviews

with parents of adolescents with thalassemia indicated

various behavioral problems in these adolescents. Adoles-

cents with thalassemiahad higher scores in neuroticism.

Some behavioral problems were also found, along with

neurotic manifestations. Adolescents with thalassemia had

several physical problems, which led to stress. A recent

study suggests that anxiety disorders may be more

strongly related to early stress exposure, Manevich

et al. [29]. Moussa et al. [30] found that children are

anxious about the treatment modalities, effectiveness of

iron chelation, and complications related to the iron

chelation. Adolescence itself is a time that demands more

adjustment skills. An illness, in addition to the existing

problems, may cause an emotional outburst, which needs

to be handled properly. If not, the overlooked needs may

manifest as anxiety disorders. Thalassemia, being a

chronic disease, can cause the same kind of anxiety and

worry as other chronic illnesses such as type 1 diabetes

and cancer. Hayward et al. [31] stated that because of the

overgrowth of bones and disfigurement that occurs in the

long run, a thalassemic child may confine him/herself

within the home, which can manifested as a social phobia.

These kinds of phobias have been documented earlier. A

study carried out by Moorjani and Issac [5] revealed a

marked difference in adolescents with thalassemia and

adolescents without thalassemia in terms of phobia. Most

of the population with thalassemia reported fear related to

blood transfusions. Some of these children had a fear of

death. Parents reported fear of new people and places in

33.3% of these children. Many adolescents with thalasse-

mia may experience fear related to intravenous line

insertion and subcutaneous infusion pumps. However, it

is impossible for a child with thalassemia to remain

symptom-free most of the time, which predisposes him or

her to a certain degree of anxiety phobic reactions. Bush

et al. [32] found that a marked difference in obsession

Table 9 Correlation between the Hospital Anxiety Depression

Scale and the Middlesex Hospital Questionnaire

Middlesex obsession

HADS total R 0.393P 0.032N 30

HADS, Hospital Anxiety Depression Scale; n, number; P, P value;r, statistical parameter.

Table 10 Correlation between the Middlesex Hospital

Questionnaire (depression) and the McGill Quality of Life

Questionnaire (general and physical)

McGill Quality of LifeQuestionnaire (general)

McGill Quality of LifeQuestionnaire (physical)

Mid. 6depression

R – 0.500 – 0.503P 0.005 0.005N 30 30

Mid., Middlesex.


between adolescents with thalassemia and adolescents

without thalassemia in which adolescents with thalasse-

mia inclined more towards the negative side. Adolescents

with thalassemia have frequent intrusive thoughts of

death and parting from loved ones. This should be

addressed because at a later stage these obsessions may

result in blurring of the boundaries between internal

(cognitive) and external events. Moorjani and Issac [5]

claimed that adolescents with thalassemia revealed an

increased level of somatic anxiety when compared with

normal controls. The somatic anxiety is marked by a

history of diverse physical complaints that may be

psychological in origin.


the two groups with regard to the McGill Quality of Life

Questionnaire (Po0.001). Adolescents with thalassemia

showed significantly lower scores in different aspects of

QoL: total, general, physical, and emotional (mean =

83.57 ± 11.60, 3.70 ± 0.92, 31.60 ± 2.75, and 48. 60 ±

13.05, respectively) (Table 8). Triantis et al. [33] stated

that thalassemia can be challenging to an individual at the

physical, emotional, and cognitive levels and disrupts

QoL. Its frequent and complex treatment might also lead

to financial burden for the individual and his/her family,

which may further result in reduced adaptive and coping

ability of affected children. Sachdeva et al. [34] stated that

the overall QoL was affected in 88% of patients with

thalassemia in multiple domains, including physical,

psychological, social, and cognitive.

There was a significant positive correlation between the

HADS and the Middlesex Hospital Questionnaire,

obsession subscale (P = 0.032) (Table 9). This means

that anxiety and depression are highly associated with the

occurrence of obsessive symptoms. Messina et al. [35]

concluded that patients with thalassemia showed a

personality characterized by somatization, depression,

and obsessive–compulsive traits. Ahmad et al. [36] found

that the most common psychiatric disorders among

adolescents with thalassemia were major depressive

disorder and separation anxiety disorder. In addition,

they found that more than 43% of the adolescents had

recurrent thoughts of death.

There was a significant negative correlation between the

Middlesex Hospital Questionnaire, depression subscale,

and the McGill Quality of Life Questionnaire, general

and physical (P = 0.005) (Table 10). This means that a

higher degree of depression is associated with lower QoL

among adolescents with thalassemia. Pakbaz et al. [12]

found that all patients with thalassemia reported severe

impairments in the QoL assessment. Feelings such as

anxiety, depression, and concern with regard to one’s

overall health status, which had marked effects on

different aspects of QoL, were the most commonly

reported. In addition, Azarkeivan et al. [37] claimed that

depression is associated with both poor physical and

mental HRQoL among patients with major/intermedia

b-thalassemia. Kullowatz et al. [38] found that the

negative impact of anxiety and depression on HRQoL

in patients with thalassemia is consistent with previous

studies of other chronic conditions that demonstrated

that individuals with comorbid medical illness and

depression and anxiety show significantly greater impair-

ment with Health related quality of life (HRQoL). In

addition, Ahmad et al. [36] reported that psychological

problems, including depression and anxiety, were sig-

nificant predictors of impaired QoL.

ConclusionDepressive and anxiety symptoms are more prevalent

among adolescents with thalassemia. In addition, in the

same group, there were higher degrees of free floating

anxiety, phobic anxiety, obsessive symptoms, somatic

symptoms, depressive symptoms, and hysteria. QoL was

highly affected among adolescents with thalassemia. A

higher degree of depression is associated with lower levels

of QoL among adolescents with thalassemia.

Limitations

The small-sized sample in this study can be considered as

one of the limitations of this study. A large-sized sample

may be needed to assess other possible psychological

profiles of adolescents with thalassemia. In addition,

follow-up studies may be valuable in the assessment of

the course and prognosis of depression and anxiety among

adolescents with thalassemia.


References1 Kuo HT, Peng CT, Tsai MY. Pilot study on parental stress and behavioral

adjustment to the thalassemia major disease process in children undergoingiron-chelation in western Taiwan. Hemoglobin 2006; 30:301–309.

2 Jarman F, Oberklaid F. Children with chronic illness: factors affectingpsychosocial adjustment. Curr Opin Pediatr 1990; 2:868–872.

3 Mazzone L, Battaglia L, Andreozzi F, Romeo MA, Mazzone D. Emotionalimpact in beta-thalassaemia major children following cognitive-behaviouralfamily therapy and quality of life of caregiving mothers. Clin Pract EpidemiolMent Health 2009; 5:5.

4 Parker JS, Benson MJ. Parent-adolescent relations and adolescentfunctioning: self-esteem, substance abuse and delinquency. Adolescence2004; 39:519–530.

5 Moorjani JD, Issac C. Neurotic manifestations in adolescents withthalassemia major. Indian J Pediatr 2006; 73:603–607.

6 Guasco G, La Mantia A, Cuniolo A. Psychological problems of thalassemicsubjects. Pediatr Med Chir 1987; 9:269–279.

7 Klein N, Sen A, Rusby J, Ratip S, Modell B, Olivieri NF. The psychosocialburden of Cooley’s anemia in affected children and their parents. Ann N YAcad Sci 1998; 850:512–513.

8 Economou M, Zafeiriou DI, Kontopoulos E, Gompakis N, Koussi A, PerifanisV, et al. Neurophysiologic and intellectual evaluation of beta-thalassemiapatients. Brain Dev 2006; 28:14–18.

9 Saini A, Chandra J, Goswami U, Singh V, Dutta AK. Case control study ofpsychosocial morbidity in beta thalassemia major. J Pediatr 2007; 150:516–520.

10 Telfer P, Constantinidou G, Andreou P, Christou S, Modell B, AngastiniotisM. Quality of life in thalassemia. Ann N Y Acad Sci 2005; 1054:273–282.

11 Hajibeigi B, Azarkeyvan A, Alavian SM, Lankarani MM, Assari S. Anxiety anddepression affects life and sleep quality in adults with beta-thalassemia.Indian J Hematol Blood Transf 2009; 25:59–65.

12 Pakbaz Z, Treadwell M, Yamashita R, Quirolo K, Foote D, Quill L, et al.Quality of life in patients with thalassemia intermedia compared tothalassemia major. Ann N Y Acad Sci 2005; 1054:457–461.


13 Aydinok Y, Erermis S, Bukusoglu N, Yilmaz D, Solak U. Psychosocialimplications of thalassemia major. Pediatr Int 2005; 47:84–89.

14 Shaligram D, Girimaji SC, Chaturvedi SK. Psychological problems and qualityof life in children with thalassemia. Indian J Pediatr 2007; 74:727–730.

15 Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depressionseverity measure. J Gen Intern Med 2001; 16:606–613.

16 Zigmond AS, Snaith RP. The hospital anxiety and depression scale. ActaPsychiatr Scand 1983; 67:361–370.

17 Crown S, Crisp AH. Manual of the Middlesex Hospital Questionnaire(MHQ). Barnstaple, Devon: Psychological Test Publications; 1970.

18 Al Rakhawi Y, Girgis W, Abdel Jawad MS. Arabic translation of MiddlesexQuestionnaire. Egypt: Department of Psychiatry Cairo University; 1978.

19 Cohen SR, Mount BM, Bruera E, Provost M, Rowe J, Tong K. validity of themcgill quality of life questionnaire in the palliative care setting: a multi-centreCanadian study demonstrating the importance of the existential domain.Palliat Med 1997; 11:3–20.

20 Altman DG. Practical statistics for medical research. London: Chapman &Hall/CRC; 1991.

21 Sabry N, Salama KH. Cognitive abilities, mood changes and adaptive func-tioning in children with b thalassaemia. Curr Psychiatry 2009; 16:244–254.

22 Ratip S, Skuse D, Porter J, Wonke B, Yardumian A, Modell B. Psychosocialand clinical burden of thalassaemia intermedia and its implications forprenatal diagnosis. Arch Dis Child 1995; 72:408–412.

23 Khurana A, Katyal S, Marwaha RK. Psychosocial burden in thalassemia.Indian J Pediatr 2006; 73:877–880.

24 Woo R, Giardina P, Hilgartner M. Psychosocial needs with beta-thalassae-mia. Archiv Dis Child 1982; 57:860–863.

25 Huurre TM, Aro HM. Long-term psychosocial effects of persistent chronicillness: a follow-up study of Finnish adolescents aged 16 to 32 years.Eur Child Adolesc Psychiatry 2002; 11:85–91.

26 Borras L, Constant EL. Depression and beta-thalassemia: a genetic link?Acta Neuropsychiatrica 2007; 19:134.

27 Saravi VG, Zarghami M, Tirgari A, Ebrahimi E. Relationship betweenthalassemia and depression. Res J Biol Sci 2007; 2:280–284.

28 Aydin B, Yaprak I, Akarsu D, Okten N, Ulgen M. Psychosocial aspects andpsychiatric disorders in children with thalassemia major. Acta Paediatr Jpn1997; 39:354–357.

29 Manevich TM, Sokolova ED, Iakhno NN, Rogovina EG. Specifics ofpersonality and mental status in children and adolescence with chronictension-type headache. Zh Nevrol Psikhiatr Im S S Korsakova 2004; 104:11–15.

30 Moussa MA, Alsaeid M, Abdella N, Refai TM, Al Sheikh N, Gomez JE. Socialand psychological characteristics of Kuwaiti children and adolescents withtype 1 diabetes. Soc Sci Med 2005; 60:1835–1844.

31 Hayward C, Wilson KA, Lagle K, Killen JD, Taylor CB. Parent-reportedpredictors of adolescent panic attacks. J Am Acad Child Adolesc Psychiatry2004; 43:613–620.

32 Bush S, Mandel FS, Giardina PJ. Future orientation and life expectations ofadolescents and young adults with thalassemia major. Ann N Y Acad Sci1998; 850:361–369.

33 Triantis J, Xypolita-Tsantili D, Papadakou- Lagoyianni S. Understandingof illness: A study of cognitive and emotional Family reactions and theirmanagement in a parents group factors. Ann N Y Acad of Sci1985; 445:327–336.

34 Sachdeva A, Yadav SP, Berry AM, Kaul D, Raina A, Khanna VK. Assessmentof quality of life in thalassemia major. Int J Haematol 2002; 76 (SI):4.

35 Messina G, Colombo E, Cassinerio E, Ferri F, Curti R, Altamura C, et al.Psychosocial aspects and psychiatric disorders in young adult withthalassemia major. Intern Emerg Med 2008; 3:339–343.

36 Ahmad G, Sirin K, Hamid A. Prevalence of Psychiatric Disorders, Depres-sion, and Suicidal Behavior in Child and Adolescent With Thalassemia Major.J Pediatr Hematol/Oncol 2006; 28:781–784.

37 Azarkeivan A, Hajibeigi B, Alavian SM, Lankarani MM, Assari S. Associatesof poor physical and mental health-related quality of life in beta thalassemia-major/intermedia. J Res Med Sci 2009; 14:349–355.

38 Kullowatz A, Kanniess F, Dahme B, Magnussen H, Ritz T. Association ofdepression and anxiety with health care use and quality of life in asthmapatients. Respir Med 2007; 101:638–644.


Central auditory processing in attention deficit hyperactivity

disorder: an Egyptian StudySaffeya Effata, Somaya Tawfikb, Hanan Husseina, Hanan Azzama

and Safaa El Erakyc

aDepartments of Psychiatry,bAudiology Department, Faculty of Medicine,Ain Shams University, Cairo andcHospital of Mental Health, Abbasseya, Egypt

Correspondence to Hanan Hussein, AssistantProfessor of Psychiatry, Department of Psychiatry,Faculty of Medicine, Ain Shams University, Cairo, EgyptFax: + 20122193402;e-mail: [email protected]

Received 27 February 2011Accepted 4 March 2011


2011, 18:245–252

Introduction

Attention deficit hyperactivity disorder (ADHD) and central auditory processing disorder

(C)APD are two neurodevelopmental disorders that usually result in poor scholastic

performance. Both disorders share common symptoms such as poor attention

particularly in noisy situations. Several studies suggested that they are the same disorder.

Aim

This study aimed to explore the relationship between ADHD and (C)APD.


A group of 20 children with ADHD were assessed psychologically using Wechsler

Intelligence Scale for Children and Conner’s Parent Rating Scale. Then, central

auditory function was assessed subjectively using the Scale of Auditory Behavior

(SAB) and objectively using the central auditory processing test battery.

Results

It was found that 55% (n = 11) of children showed abnormality in one or more of the

(C)APD test results. SAB scores and Conner’s scores did not vary significantly

between both the groups. In contrast, Intelligence Quotient Scores were significantly

lower in patients with ADHD than in patients with (C)APD. The results showed that

pitch pattern sequences, pitch pattern discrimination (PPD), and gap in noise were

significantly abnormal in patients with ADHD with affected (C)APD, indicating that the

most affected central ability in (C)APD ADHD is auditory temporal processing, namely,

‘temporal ordering and sequencing as well as temporal resolution’. In addition,

inattention and cognitive problems in Conner’s Parent Rating Scale-Long version

were statistically significantly associated with (C)APD.

Conclusion

It was concluded that high comorbidity exists between (C)APD and ADHD, with the

most affected ability being temporal auditory processing. Inattention and cognitive

problems were the only clinical variables correlated to the presence of (C)APD.

Keywords:

attention deficit, hyperactivity, neurodevelopmental disorder, Conner’s,

reading disability, central auditory processing


IntroductionAttention deficit hyperactivity disorder (ADHD) is a

neurodevelopmental disorder characterized by age-inap-

propriate poor attention span as well as features of

hyperactivity and impulsivity or both [1]. It is the most

common neurobehavioral disorder presenting for treatment

in childhood. ADHD is often chronic, with prominent

symptoms, and impairment spanning into adulthood. It is

often associated with cooccurring anxiety, mood, and

disruptive disorders, as well as substance abuse [2].

A pathophysiological explanation for ADHD symptoma-

tology relates to deficits in prefrontal cortex-mediated

executive brain function, also known as response inhibi-

tion [3]. Neuroimaging is allowing researchers to further

study the ways in which medications affect neurophysiol-

ogy, providing more precise insights into ADHD and its

etiology, diagnosis, and treatment [4]. Neuropsychologi-

cal studies have implicated the frontal cortical regions

of the brain and the circuits linking them to the basal

ganglia as critical to executive function, attention, and

the ability to exercise inhibition [5].

There may be a greater likelihood for the causal pathway to

be from hyperactivity-inattention symptoms to scholastic

deficits. This is consistent with findings showing that

inattention symptoms contribute to later reading difficul-

ties [6]. It was found that the severity of ADHD affects

academic performance in school, with psychiatric morbid-

ity [7]. Children with ADHD are up to five times more

likely to require special needs education than children

without ADHD [8,9]

Central auditory processing disorder [(C)APD] is defined

as a hearing disorder resulting from impaired brain


2090-5408 & 2011 Okasha Institute of Psychiatry, Ain Shams University DOI: 10.1097/01.XME.0000405285.63178.ef

function and characterized by poor discrimination,

separation, grouping, localization, or ordering of sounds.

It is a common cause of poor scholastic performance as it

is reported to contribute significantly to academic and

behavioral dysfunctions among school-aged children [10].

In USA, (C)APD is included in the ‘specific learning

disability’ category under the Individuals with Disabil-

ities Education Act. It is defined under Individuals with

Disabilities Education Act as a disability that causes

problems in comprehending the social and interpersonal

content of language [11].

Since the introduction of (C)APD, there has been a debate

about its relation to ADHD. Although the comorbidity of

(C)APD with ADHD has been well documented [12],

some researchers argued that (C)APD and ADHD may be

overlapping but independent disorders [13], whereas other

investigators argued that there are similarities between

both disorders. There is a similarity between ADHD and

(C)APD in symptomatology as well as in psychoeduca-

tional and behavioral sequelae [14]. Research findings

concluded that a diagnosis of ADHD places the child at

risk (50–80%) for (C)APD [15]. Chermak and Museik

suggested that understanding the relationship between

the attention deficits of ADHD and (C)APD hinges on the

interaction between perception and higher-level cognitive

processing [16]. Although several studies were conducted

to evaluate (C)APD in ADHD, debate still exists on the

relation of both disorders [14,17,18]. Accordingly, this

study was conducted to explore the relationship between

ADHD and (C)APD.

HypothesisADHD and (C)APD are different but overlapping

disorders with high comorbidity. The comorbid cases

show particular clinical and electrophysiological profi-

les.The aims of this study were (a) to detect the profile

of central auditory processing among ADHD patients and

(b) to study the behavioral and psychophysical correlates

of comorbid ADHD and (C)APD.

Participants and methodsA convenient sample of 20 children aged 6–12 years

fulfilling the diagnosis of ADHD according to the Diagnosticand Statistical Manual of Mental Disorders-Fourth Edition

(DSM-IV) criteria [19] who were not under medication

were recruited from the outpatient clinic of the Institute

of Psychiatry, Ain Shams University (Cairo, Egypt). The

inclusion criterion was Intelligence Quotient of 85 or more

on the Wechsler Intelligence Test for Children, Arabic

version [20]; written consent was obtained from one

parent to involve his or her child in the study. Children

with any other neurological problems, sensory deficit, or

receiving psychotropic drugs or auditory training were

excluded. Each child was evaluated in two sessions.

During the first session, a proper case history and

examination using the child psychiatry clinical sheet of

the Institute of Psychiatry, Ain Shams University, was

applied to diagnose ADHD and exclude patients on

treatment or with comorbidity. Confirmation of the

diagnosis according to the criteria was carried out using

the DSM-IV [19]. Comorbidity was excluded using the

Mini International Neuropsychiatric Interview for chil-

dren, Kid-Arabic version [21], which is a short structured

diagnostic interview based on DSM-IV criteria. General

intelligence was assessed by a professional clinical

psychologist using the Wechsler Intelligence Scale for

Children-Arabic version [20]. The severity of ADHD was

assessed using Conner’s Parent Rating Scale-revised-

Long version (CPRS-L) [22]. It scores the parents’ report

of their child’s behavior during the past month on a 4-

point response scoring. It has an excellent specificity for

ADHD dimensions (Short-Band Questionnaire).

During the second session, an audiological assessment

was made. It included a case history and otological

examination, followed by a basic audiologic evalua-

tion that included pure-tone audiometry (air conduc-

tion testing) and speech audiometry that consisted of

speech reception threshold using Arabic bisyllabic

words [23], and a speech discrimination test using Arabic

Phonetically Balanced Kindergarten words [23]. Immit-

tanemetry was carried out to assess middle ear function.

Patients with abnormal test results were excluded.

Patients were then screened for (C)APD using the Arabic

version of the SAB Questionnaire [24]. It is a 12-item

questionnaire with an average time of administration of

5 min. It scores the parents’ report of their child’s

auditory behavior on a 5-point response. It is used for

the screening of (C)APD. The scale was translated from

the English form developed by Schow et al. [24].

A series of psychophysical central auditory tests were

then carried out for the selected patients including the

following:

(1) Arabic low-pass-filtered (LPF) test [25]: Assessing

auditory closure ability;

(2) Arabic speech intelligibility-in-noise (SPIN) test

[25]: Assessing selective auditory attention;

(3) Arabic dichotic digit test [26]: Assessing binaural

integration;

(4) Arabic-gap in noise (GIN) test [27]: Assessing

temporal resolution;

(5) Pitch pattern sequences (PPS)(PPD) test [28]:

Assessing temporal ordering and sequencing;

(6) All tests were scored as percent correct for ears, except

the GIN test, which was scored by measuring the Gin

threshold in milliseconds (the shortest gap duration

for which at least four of six responses are correct [29].

Statistical methodsThe data collected were statistically analyzed using

Statistical Package for Social Sciences program software

version 17.0. (Chicago, Illinois, USA). Descriptive

statistics were obtained for numerical parametric data as

means, standard deviation, minimum and maximum of the


range, and 95% confidence interval, whereas for categorical

data, it was expressed as number and percentage.

Inferential analyses were carried out for quantitative

variables using an independent t-test in case of two

independent groups with parametric data. Qualitative data

were obtained using Fisher’s exact test. Correlations were

assessed using the Pearson’s correlation for numerical

parametric data. The level of significance was set at a

P value of less than 0.05, and nonsignificant otherwise.

ResultsDescriptive statistics

Twenty children with ADHD were included in this study,

six children (30%) had ADHD-I (inattentive type) and

14 children (70%) had ADHD-C (combined type). There

were six (30%) females and 14 (70%) males. Their mean

age was 8.65 years [standard deviation (SD) = ± 1.18)],

ranging from 7 to 11 years. The mean verbal intelligence

quotient was 101.0 (SD = + 11.4), the mean performance

intelligence quotient was 102.9 (SD = + 10.9), and the

mean total intelligence quotient was 101.5 (SD = + 10.4).

The mean scores on (CPRS-L) are presented in Fig. 1.

The mean score on the SAB is 31.8 (SD = ± 5.2), ranging

from 23 to 41, and 95% confidence interval was 29.3–34.2.

The diagnosis of (C)APD among patients with ADHD

was made on the basis of abnormal scores even in one test

according to age-specific norms. Among the entire study

sample of ADHD patients, 45% (n = 9) showed normal

(C)APD test scores, whereas 55% (n = 11) showed

abnormality in one or more of the (C)APD test results.

Among inattentive-type ADHD, two cases (33.3%) were

non-(C)APD and four cases (66.6%) were (C)APD,

whereas among combined-type ADHD, seven cases

(50%) were non-(C)APD and seven cases (50%) were

(C)APD, w2 = 0.6, P = 0.5.

The (C)APD pattern was as follows: 55% showed abnormal

scores on PPS, 30% on PPD, 15% on DD, and 40% on GIN

tests. None of the patients with ADHD showed abnorm-

ality in LPF and SPIN. The results are shown in Fig. 2.

Relation between patients with ADHD with (C)APD and

patients with ADHD without (C)APD

Demographic variables

Patients with ADHD with (C)APD did not differ

significantly from patients with ADHD without

(C)APD in terms of age [ADHD with (C)APD, mean

age: 8.5 years, SD = ± 1.4 vs. ADHD without (C)APD,

mean age: 8.9 years, SD = ± 0.9, t = 0.81, P = 0.42].

Similarly, sex was not statistically associated with either

diagnosis. In the ADHD with (C)APD group, three

(27%) were females and eight (72.7%) were males; in the

ADHD without (C)APD group, three (33.3%) were

females and six (66.6%) were males.

Behavioral variables

Patients with ADHD with (C)APD did not differ

significantly from patients with ADHD without

(C)APD with regard to their auditory behavior using

(SAB) [ADHD with (C)APD mean SAB score: 30 ± 5.1

SD vs. ADHD without (C)APD mean age: 34 ± 4.8 SD,

t = 1.8, P = 0.089). Similarly, there was no statistically

significant difference between patient scores on CPRS

among patients with ADHD with or without (C)APD,

except for the cognitive problem subscale, which was

significantly lower in patients with (C)APD [ADHD

without C(APD) mean cognitive probability score:

74.4 ± 5.6 SD vs. ADHD with C(APD) mean cognitive

score: 81.6 ± 8.2 SD, t = 2.216, P = 0.4]. In addition, the

inattention subscale scores tended to be significantly

lower in patients without (C)APD [ADHD without

(C)APD inattention score: 75 ± 6.7 SD vs. ADHD with

(C)APD mean inattentive score: 81.4 ± 7.7 SD, t = 1.94,

P = 0.06]. The results are shown in Fig. 3.

Psychometric variables

However, VIQ and TIQ were statistically significantly higher

in patients without (C)APD ADHD compared with patients

with (C)APD ADHD . The results are shown in Table 1.

Audiometric variables

Different CAP subsets were tested for a statistically

significant association with the presence or absence of

Fig. 1.

Mean scores of Conner’s Parent Rating Scale.

Fig. 2.

Percentage of patients with attention deficit hyperactivity disordershowing normal or abnormal central auditory processing disorder testresults. DD, dichotic digit; GIN, gap in noise; LPF, low-pass-filtered;PPS, pitch pattern sequences; PPD, pitch pattern discrimination; SPIN,speech intelligibility-in-noise.

Central auditory processing in attention deficit hyperactivity disorder Effat et al. 247

(C)APD among patients with ADHD in an attempt to

find a specific marker among them for the presence of

(C)APD or to at least detect the specific differentiating

pattern of CAP between ADHD and (C)APD.

The results showed that PPS, PPD, and GIN were

significantly atypical in patients with ADHD with

(C)APD, indicating that the most affected central ability

in (C)APD ADHD is auditory temporal processing

namely ‘temporal ordering and sequencing as well as

temporal resolution’, which are not affected in ADHD

alone (Table 2).

Both groups were then compared in terms of their

(C)APD test battery results using an independent-

sample t test and a highly statistically significant

difference was found between them with regard to two

of the six tests conducted, namely, temporal ordering and

sequencing, being lower in the (C)APD group. Moreover,

a statistically significant difference was found on the

dichotic test and the GIN test, reflecting poor perfor-

mance in the (C)APD group on these two tests as shown

in Table 3.

DiscussionThis study was carried out to determine the rate of

comorbidity between ADHD and (C)APD among

patients in a clinical setting in our community, which

was found to be 55%. No statistically significant

association existed between the clinical subtype of

ADHD and the occurrence of (C)APD. The (C)APD

pattern was as follows: 55% showed abnormal scores on

PPS, 30% on PPD, 15% on DD, and 40% on GIN tests.

None of the patients with ADHD showed abnormalities

in LPF and SPIN. The results are shown in Fig. 2. This is

consistent with the result obtained by Tillery et al. [15],

who found that a diagnosis of ADHD places the child at

risk (50–80%) for (C)APD. In addition, Riccio et al. [30]

found that in 30 children diagnosed with (C)APD, 50%

would also fulfill the criteria of ADHD on the basis of a

formal diagnosis.

In terms of the sociodemographic characteristics of cases

with overlap between ADHD and (C)APD, there is no

statistically significant difference between patients with

(C)APD and patients without (C)APD as regards age.

This might be explained by the fact that both ADHD and

(C)APD are neurodevelopmental disorders. Hence, they

will go hand in hand with regard to age of presentation.

Furthermore, patients are selected according to a limited

age range (6–12 years). Similarly, there was no statistically

significant difference between both groups with regard to

sex. This could be attributed to the higher number of

males (high male-to-female ratio) in this study, which

might implicate the findings. This result should be

interpreted with caution as the sample studied was too

small to detect a difference.

The aim of this study was to detect symptom patterns in

ADHD both with and without (C)APD. On comparing

patients without (C)APD and patients with (C)APD

ADHD with regard to the four subscales of (CPRS-L)

(Fig. 3), we found that the Cognitive Problem Subscale

Score was significantly higher in patients with (C)APD.

Fig. 3.

Comparison between noncentral auditory processing disorder[(C)APD] and (C)APD attention deficit hyperactivity disorder cases inConner’s scores.

Table 1 Comparison between non-(C)APD and (C)APD ADHD

cases in terms of IQ

Non-(C)APD (C)APD

Mean (SD) 95% CI Mean (SD) 95% CI t P

VIQ 106.9 (12.4) 97.3–116.4 96.1 (8.1) 90.7–101.5 2.347 0.031*PIQ 107.9 (10.4) 99.9–115.9 98.8 (10) 92.1–105.5 1.984 0.63TIQ 106.7 (10.7) 98.4–114.9 97.3 (8.4) 91.6–102.9 2.198 0.041*

ADHD, attention deficit hyperactivity disorder; (C)APD, central auditoryprocessing disorder; CI, confidence interval; IQ, Intelligence Quotient;SD, standard deviation.*P value is Sf statistically significant.

Table 2 Association between (C)APD tests and the presence of

(C)APD in ADHD cases

Non-(C)APD ADHD (%) (C)APD ADHD (%) P

LPFAbnormal 0 (0) 0 (0) CCNormal 9 (100) 11 (100)

SPINAbnormal 0 (0) 0 (0) CCNormal 9 (100) 11 (100)

PPSAbnormal 0 (0) 11 (100) o0.001***Normal 9 (100) 0 (0)

PPDAbnormal 0 (0) 6 (54.5) 0.014*Normal 9 (100) 5 (45.5)

DDAbnormal 0 (0) 3 (27.3) 0.218Normal 9 (100) 8 (72.7)

GINAbnormal 0 (0) 8 (72.7) o.001***Normal 9 (100) 3 (27.3)

ADHD, attention deficit hyperactivity disorder; (C)APD, central auditoryprocessing disorder; CC, could not be calculated; DD, binauralintegration; GIN, temporal resolution; LPF, auditory closure; PPD,temporal discrimination; PPS, temporal ordering; SPIN, selectiveauditory attention.*Po0.05 (significant).**Po0.01 (highly significant).***Po0.001 (very highly significant).


Furthermore, the inattention subscale scores tended to be

significantly higher (P value = 0.068) in patients with

(C)APD compared with patients without (C)APD . Thus,

a statistically significant association between the presence

of (C)APD comorbidity and severity of cognitive and

attentional problems was found in these patients. This is

an indication of an area of overlap detected in our study

between ADHD and (C)APD symptoms. There are many

studies indicating that both disorders overlap clini-

cally [31–37]. Riccio et al. [30] postulated that both

attention and auditory processing are necessary to perform

central auditory processing tasks. Furthermore, Chermak

and Musiek [16], Chermak et al. [34], and Musiek

et al. [38] reported that all auditory tasks, from pure tone

detection to spoken language processing, are influenced

by higher-order, nonmodality-specific factors such as

attention, memory, and motivation. Finally, Cacace and

McFarland [39] concluded that attention is a major source

of contamination in (C)APD testing. Our findings were not

consistent with those of Riccio et al. [13], who found no

significant correlations between measures of attention (i.e.

continuous performance test and rating scales for attention

problems and hyperactivity and measures of central

auditory processing [i.e. the staggered spondaic word and

screening test for auditory processing disorders (SCAN)].

This can be explained by the fact that only 72% of their

study sample had ADHD, but in this study, the entire

sample had ADHD. In addition, their study was retro-

spective in nature. Thus, it is highly likely that children

were medicated; in this study, they were not under

medication. Furthermore, not all children of the other

study sample were subjected to the same combination of

neuropsychological or auditory tests. Finally, they are

correlating results of behavioral tests of (C)APD to

laboratory measures (the test of variables of attention,

which is a computer-administered continuous performance

test) and behavioral rating scales of attention. In this study,

however, only rating scales were used, which might result

in a higher degree of bias.


the scores of the SAB questionnaire in both patients

without (C)APD and patients with (C)APD ADHD. This

indicates an overlap between both groups on evaluation

by subjective measures.

In terms of the overlap between ADHD and (C)APD

on the investigative level, the most affected ability in

patients with ADHD is temporal auditory processing.

This finding was supported by the American Speech

Hearing and Language Association technical report of

coexistence of auditory temporal processing dis-

order with ADHD [40]. Toplak et al. [41] added that

children with ADHD have problems in several aspects

of temporal information processing, including duration

discrimination.

Several studies have applied P300 and mismatch

negativity to assess auditory sequential processing speed

and temporal information processing [42–46]. Du

et al. [47] demonstrated a reduction of the voluntary

component P300 as well as a reduction of the automatic

response component MMN in ADHD cases, which also

indicates abnormality of auditory temporal processing.

This study showed no difference between patients

without (C)APD and patients with (C)APD ADHD in

selective auditory attention as measured by the SPIN test

as all the study sample scores were normal according to

age-specific norms. This agrees with Dalebout and

Fox [48] and Hooks et al. [49], who reported that there

were no differences between an ADHD and a control

group on a selective attention task, and Landau et al. [50],

who reported that children with ADHD focus less on

television in the presence of distraction, but their recall

of events is not significantly different from that of

children without ADHD.

However, our finding is not consistent with that of

Satterfield et al. [51], who reported different results on a

recall task under conditions of auditory and visual

distraction.

Fernandez et al. [52], McAlonan et al. [53], and Shaw and

Rabin [54] reported a delay in cortical maturation in

Table 3 Comparison between non-(C)APD and (C)APD ADHD patients with regard to scores of the CAP test battery

Non-(C)APD (C)APD

Test Side Mean (SD) 95% CI Mean (SD) 95% CI t P

LPF Right 97.9 (4.3) 94.6–101.2 100 (0) 100–100 – 1.488 0.175Left 98.7 (2.8) 96.5–100.8 100 (0) 100–100 – 1.414 0.195

SPIN Right 97.2 (4.4) 93.8–100.6 94.1 (5.8) 90.2–98.0 1.365 0.189Left 97.8 (3.6) 95.0–100.6 95.3 (5.9) 91.3–99.2 1.164 0.261

PPS Right 91.1 (8.9) 84.2–98.0 44.8 (11) 37.4–52.3 10.084 o.001***Left 90.6 (9.8) 83–98.1 47.2 (10) 40.5–54 9.656 o.001***

PPD Right 85.6 (8.8) 78.8–92.3 65.1 (12) 57.0–73.2 4.251 o.001***Left 90 (7) 84.5–95.4 61.3 (14.8) 51.4–71.3 5.66 o.001***

DD Right 96.7 (4.3) 93.3–100.0 95.5 (4.7) 92.3–98.6 0.593 0.561Left 95.6 (4.6) 92.0–99.1 85.9 (12) 77.8–94.0 2.267 0.036*

GIN Right 5.6 (0.5) 5.2–6.0 8.0 (1.9) 6.7–9.3 – 3.985 0.002*Left 5.6 (0.5) 5.2–6.0 8.4 (2.1) 6.9–9.8 – 4.254 o0.001***

ADHD, attention deficit hyperactivity disorder; (C)APD, central auditory processing disorder; CI, confidence interval; DD, binaural integration; GIN,temporal resolution; LPD, auditory closure; PDD, temporal discrimination; PDS, temporal ordering; SD, standard deviation; SPIN, selective auditoryattention.*Po0.05 (significant).**Po0.01 (highly significant).***Po0.001 (very highly significant).


ADHD and that different clinical outcomes may by

associated with different developmental trajectories in

adolescence and beyond. In this study, a significantly

reduced dichotic digit score in the left ear than the right

ear was found in patients with (C)APD compared with

patients without (C)APD ADHD. This finding reflects

an atypically large right ear advantage (i.e. left ear

deficit), indicating possible developmental delay in the

maturation of the central auditory nervous system [46].

This finding is supported by Mackie et al., who reported

that more comorbid presentations of ADHD are associated

with a more pronounced delay in brain maturation [55].

Conclusion and recommendationsHigh comorbidity exists between (C)APD and ADHD,

with the most affected ability being temporal auditory

processing. The presence of right ear advantage as

evidenced by a dichotic digit test confirms maturational

delay in patients with ADHD. High inattention and

cognitive problem scores on CPRS-L were the only

clinical variables correlated to the presence of (C)APD. It

is thus recommended to suspect the presence of (C)APD

in those patients and subject them to further assessment.

Further research is recommended to study temporal

processing on a large sample of ADHD children using

both psychophysical and electrophysiological measures.

Furthermore, neuroimaging is recommended as another

investigative tool to delineate the differences between

ADHD and (C)APD.


References1 Mc Cracken JT. Attention deficit disorder. In: Sadock BJ, Sadock VA, Ruiz P,

editors. Comprehensive textbook of psychiatry. 9th edition. LippincottWilliams & Wilkins; 2002.

2 Wilens TE, Biederman J, Spencer TJ. Attention deficit/hyperactivity disorderacross the lifespan. Annu Rev Med 2002; 53:113–131.

3 Dopheide JA, Theesen KA. Childhood disorders. In: DiPiro JT, Talbert RL,Yee GC, et al. Pharmacotherapy: a pathophysiologic approach. 5th edition.New York, NY: McGraw-Hill; 2002, pp. 1145–1154.

4 Raz A. Brain imaging data of ADHD. Psychiatric Times 2004; 21:(9)S.

5 Arnsten AF. Toward a new understanding of attention-deficit hyperactivitydisorder pathophysiology: an important role for prefrontal cortex dysfunction.CNS Drugs 2009; 23 (Suppl 1):33–41.

6 Rodriguez A, Jarvelin MR, Obel C, Taanila A, Miettunen J, Moilanen I, et al.Do inattention and hyperactivity symptoms equal scholastic impairment?Evidence from three European cohorts. BMC Public Health 2007; 7:327.

7 El Missiry MA, Bishry Z, Gadallah MA, Ramy HA, El Sheikh MM. Attentiondeficit hyperactivity disorder in a sample of preparatory school students.Cairo, Egypt: Ain Shams University; 2009.

8 LeFever GB, Villers MS, Morrow AL, Vaughn ES. III. Parental perceptions ofadverse educational outcomes among children diagnosed and treated forADHD: a call for improved school/provider collaboration. Psychol Schools2002; 39:63–71.

9 Jensen PS, Eaton Hoagwood K, Roper M, Arnold LE, Odbert C, Crowe M,et al. The services for children and adolescents-parent interview: develop-ment and performance characteristics. J Am Acad Child Adolesc Psychiatry2004; 43:1334–1344.

10 Katz J, Wilde L. Auditory processing disorders. In: Katz J, editor. Handbook ofclinical audiology. 4th edition. Williams & Wilkins; 1994. pp. 490–502.

11 Palfery TD, Duff D. Central auditory processing disorders: review andcase study. Axone 2007; 28:20–23.

12 Bishop DV. Developmental cognitive genetics: how psychology can informgenetics and vice versa. Q J Exp Psychol (Colchester) 2006; 59:1153–1168.

13 Riccio CA, Cohen MJ, Garrison T, Smith B. Auditory processing measures:correlation with neuropsychological measures of attention, memory andbehavior. Child Neuropsychol 2005; 11:363–372.

14 Cook JR, Mausbach T, Burd L, Gascon GG, Slotnick HB, Patterson B, et al.A preliminary study of the relationship between central auditory processingdisorder and attention deficit disorder. J Psychiatry Neurosci 1993; 18:130–137.

15 Tillery KL, Katz J, Keller WD. Effects of methylphenidate (Ritalin) on auditoryperformance in children with attention and auditory processing disorders.J Speech Lang Hear Res 2000; 43:893–901.

16 Chermak GD, Musiek FE, Craig CH. Central auditory processing disorders:new perspectives. San Diego: Singular Publishing Group Inc; 2007.

17 Gascon GG, Johnson R, Burd L. Central auditory processing and attentiondeficit disorders. J Child Neurol 1986; 1:27–33.

18 Burd L, Fisher W. Central auditory processing disorder or attention deficitdisorder? J Dev Behav Pediatr 1986; 7:215.

19 American Psychiatric Association (APA). Diagnostic and statistical manual ofmental disorders DSM-IV-TR. 4th edition. Amer Psychiatric Pub; 1994.

20 Ismail ME, Melika LK. Wechsler intelligence scale for children: ArabicManual. 6th edition. Cairo: El-Nahda Press; 1999.

21 Ibrahim M, Bishry Z, Ghanem M. Comparison of the mini internationalneuropsychiatric interview for children (mini-kid) with the schedule foraffective disorders and schizophrenia for school aged children present andlife time version (K-sads-pI). Cairo, Egypt: Ain Shams University; 2002.

22 Conners CK. Conners Rating Scales - Revised Conners Rating Scales -Revised. North Tonawanda: Multi-Health Systems NY; 2001.

23 Soliman SandEl Mahalawy T. Simple speech test as a predictor for speechreception threshconventional (SRT) in preschool children. Cairo, Egypt: AinShams University; 1984.

24 Schow R, Chermak G, Seikel J, Brockett J, Whitaker M. Multiple auditoryprocessing assessments. St. Louis, MO: Auditec; 2006.

25 Soliman S, Tawfik S, Shalaby A. Development and standardization Arabiccentral test battery for children. Proceeding of XXIII world congress of in-ternational association of logopedics and phoniatrics. 1995; 416–419.

26 Tawfik S, Abd El Maksoud A, Weiheba H. Standardization of two dichotictest. Cairo, Egypt: Ain Shams University; 2008.

27 Shinn JB, Chermak GD, Musiek FE. GIN (Gaps-In-Noise) performance in thepediatric population. J Am Acad Audiol 2009; 20:229–238.

28 Pinheiro and Ptacek, eds. Assessment of central auditory dysfunction:Foundation and clinical correlate.1971, 219–338. Pinheiro, Ptacek.

29 American Speech Language Hearing Association. Technical report. 2008,Central auditory processing disorders.

30 Riccio CA, Hynd GW, Cohen MJ, Hall J, Molt L. Comorbidity of centralauditory processing disorder and attention-deficit hyperactivity disorder.J Am Acad Child Adolesc Psychiatry 1994; 33:849–857.

31 Keller WD. Auditory processing disorder or attention-deficit disorders? In:Katz J, Stecker NA, Henderson D, editors. Central auditory processing:a transdisciplinary view. Mosby; 1992. pp. 107–114.

32 Moss WL, Sheiffele WA. Can we differentially diagnose an attention deficitdisorder without hyperactivity from a central auditory processing problem?Child Psychiatry Hum Dev 1994; 25:85–96.

33 Keller W. The relationship between attention deficit hyperactivitydisorders, central auditory processing disorder and specific learningdisorders. In: Masters G, Stecker N, editors. Central auditory processingdisorders: mostly management. 1st edition. Boston: Allyn & Bacon; 1998.pp. 33–48.

34 Chermak GD, Hall JW. 3rd, Musiek FE. Differential diagnosis and manage-ment of central auditory processing disorder and attention deficit hyper-activity disorder. J Am Acad Audiol 1999; 10:289–303.

35 Chermak GD, Tucker E, Seikel JA. Behavioral characteristics of auditoryprocessing disorder and attention-deficit hyperactivity disorder:predominantly inattentive type. J Am Acad Audiol 2002; 13:332–338.

36 McFarland DJ, Cacace AT. Potential problems in the differential diagnosisof (central) auditory processing disorder (CAPD or APD) and attention-deficit hyperactivity disorder (ADHD). J Am Acad Audiol 2003; 14:278–280;author reply 280.

37 Ptok M, Buller N, Schwemmle C, Bergmann C, Luerssen K. Auditoryprocessing disorder versus attention deficit/hyperactivity disorder: a dys-function complex or different entities? HNO 2006; 54:405–408, 410–414.

38 Musiek FE, Bellis TJ, Chermak GD. Nonmodularity of the CANS:implications for (central) auditory processing disorder. Am J Audiol 2005;14:128–138.

39 Cacace AT, McFarland DJ. The importance of modality specificity in diag-nosing central auditory processing disorder. Am J Audiol 2005; 14:112–123.

40 American Speech Language Hearing Association. Technical report. 2005Central auditory processing disorders.

41 Toplak ME, Dockstader C, Tannock R. Temporal information processingin ADHD: findings to date and new methods. J Neurosci Methods2006; 151:15–29.


42 Ritter W, Simson R, Vaughan HGJ. Event-related potential correlates oftwo stages of information processing in physical and semanticdiscrimination tasks. Psychophysiology 1983; 20:168–179.

43 Novick B, Lovrich D, Vaughan HG Jr. Event-related potentials associated withthe discrimination of acoustic and semantic aspects of speech. Neu-ropsychologia 1985; 23:87–101.

44 Meador KJ, Hammond EJ, Loring DW, Feldman DS, Bowers D, Heilman KM.Auditory P3 correlates of phonemic and semantic processing. Int J Neurosci1987; 35 (3–4):175–179.

45 Huber M, Telser S, Falk M, Bohm A, Hackenberg B, Schwitzer J, et al.Information transmission defect identified and localized in languagelearning impaired children by means of electrophysiology. Cortex 2005; 41:464–470.

46 Chermak GD, Musiek FE. Auditory training: principles and approaches forremediating and managing auditory processing disorders. Semin Hear2002; 23:297–308.

47 Du J, Li J, Wang Y, Jiang Q, Livesley WJ, Jang KL, et al. Event-relatedpotentials in adolescents with combined ADHD and CD disorder: asingle stimulus paradigm. Brain Cogn 2006; 60:70–75.

48 Dalebout SD, Fox LG. Reliability of the mismatch negativity in the responsesof individual listeners. J Am Acad Audiol 2001; 12:245–253.

49 Hooks K, Milich R, Larch E. Sustained and selective attention in boyswith attention deficit hyperactivity disorder. J Clin Child Psychol 1994;23:69–77.

50 Landau S, Lorch EP, Milich R. Visual attention to and comprehension oftelevision in attention-deficit hyperactivity disordered and normal boys. ChildDev 1992; 63:928–937.

51 Satterfield JH, Schell AM, Nicholas TW, Satterfield BT, Freese TE. Ontogenyof selective attention effects on event-related potentials in attention-deficithyperactivity disorder and normal boys. Biol Psychiatry 1990; 28:879–903.

52 Fernandez A, Quintero J, Hornero R, Zuluaga P, Navas M, Gomez C, et al.Complexity analysis of spontaneous brain activity in attention-deficit/hyper-activity disorder: diagnostic implications. Biol Psychiatry 2009; 65:571–577.

53 McAlonan GM, Cheung V, Chua SE, Oosterlaan J, Hung SF, Tang CP, et al.Age-related grey matter volume correlates of response inhibition and shiftingin attention-deficit hyperactivity disorder. Br J Psychiatry 2009; 194:123–129.

54 Shaw P, Rabin C. New insights into attention-deficit/hyperactivity dis-order using structural neuroimaging. Curr Psychiatry Rep 2009; 11:393–398.

55 Mackie S, Shaw P, Lenroot R, Pierson R, Greenstein DK, Nugent TF, et al.Neuro-anatomic evidence for the maturational delay hypothesis of ADHD-PNAS. Am J Psychiatry 2007; 164:647–655.


middle east current psychiatrypsychiatry-research-eg.com/texts/current-psychiatry-v18n... ·...

Documents