HKES’ S.N DENTAL COLLEGE

guided by:-

Dr. Veena A Patil

Contents

• Introduction

• Definition

• Various steps in research process

• Formulating hypothesis

• Types of study design

• Heirarchy of evidence

• Ethical issues in research

• Study settings and eligibility criterias

• Sampling

• Bias

• Contamination

• Outcome measures and endpoints in research

• Representation of data

• Descriptive and inferential statistics

• Writing of a report

Introduction

• “All progress is born of inquiry. Doubt is often better than over-confidence, for it leads to inquiry, and inquiry leads to invention.”

–Hudson Maxim (1853-1927)

• Research in the field of dentistry has witnessed a tremendous

upsurge in the last two decades unveiling newer innovations in

techniques, methodologies, and material science.

• The recent focus in dental research is an evidence-based

approach which offers a bridge from science to clinical

practice.

Definition

• Research can also be defined as a scientific and systematic

search for pertinent information on a specific topic.

• formulating the research problem,

• an extensive literature survey,

• developing the hypothesis,

• preparing the research design,

• sample size estimation,

• collecting the data, execution of the project, data analysis,

• Hypothesis testing, generalizations and interpretation and

• preparation of the report.

Formulating the research problem

• Formulation of a general topic into a specific research

problem.

• 2 types

research hypothesis

question

Research question

• Question that you are trying to answer

• narrowly constructed

• addresses the important factors of the problem.

• Three types of questions are identified in research,

• questions of description;

• questions about relationships between phenomena;

• questions of comparison.

• The PICO question is a gold standard in all studies related to

clinical comparative studies.

• The parts of a well-built research question (PICO question)

• Includes

• Patient/population/problem (P),

• Intervention (I),

• Comparison (C), and

• Outcome (O).

Developing the hypothesis

• Hypothesis is defined as a ‘‘supposition arrived at from an

observation or reflection.

• A hypothesis is a statement that can be proved or disproved.

• If a typically framed research question would be:

• ‘‘Is chlorhexidine (CHX) chip in conjunction with scaling and

root planing (SRP) more effective in periodontal therapy than

SRP alone?’’ then, a hypothesis would state:

• ‘‘The use of SRP and CHX chip is efficacious in the reduction

of probing depth when compared to SRP alone.’’

• 2 types:- a. null hypothesis (Ho)

b. alternative hypothesis (Ha)

• Null hythpothesis:-

• difference seen is purely accidental or

• may arise due to bias in sampling.

• The investigators seek to accept or reject the null hypothesis as

the outcome of research.

• For example,

the adjunctive use of a CHX chip along with SRP does not

have a beneficial effect in the reduction of probing depth

compared to SRP alone.

• Directional hypothesis confers magnitude on the effect of the

independent variable.

Approach to research

1. Quantitative

2. Qualitative

• Quantitative research:-

• based on the measurement of quantity or amount.

• applicable to phenomena that can be expressed in terms of

quantity.

• the results are given in numbers or proportions

• Qualitative research:-

• concerned with subjective assessment of attitudes, opinions,

and behavior.

• results are described in words rather than numbers.

• Evaluating the awareness and perceptions of pregnant women

about proper oral hygiene during pregnancy would be an

example of qualitative research.

Types of study design

1. experimental

observational

2. cross-sectional

longitudinal

3. prospective

retrospective

• Study designs broadly can be classified as

1. observational

2. experimental

Observational:

• are referred to as observational as the investigators merely

observe what is happening rather than attempting to intervene

in anyway.

• The design does not involve a specific intervention other than

normal standard care.

Various observational studies:-

i. Correlational

ii. Case reports & case series

iii. Cross-sectional study

iv. Case-control study

v. Cohort study

vi. Ecological study

vii. Systematic reviews

viii. Metaanalysis

Correlational study:-

• intend to explore a correlation between two variables.

• A correlation would not necessarily mean causation.

• For eg:- on the correlation between coronary heart disease and

chronic periodontitis or obesity and periodontal disease etc.

• It would also include studies investigating relationships

between socio economic status, smoking, various

periodontopathogens, inflammatory markers, and periodontal

disease.

Case reports and case series

• descriptive studies in which the possibility of an association

between an observed effect and a specific environmental

exposure is based on detailed clinical evaluations and histories

of the individual(s).

• E.g.: Periodontal findings in a patient with Mauriac syndrome:

A case report.

• Labial piercing resulting in gingival recession – A case series

Cross sectional study

• provide a snapshot picture of a community at a point in time,

• do not involve following a group of individuals over time,

• e.g. prevalence and risk of gingival overgrowth in patients

treated with diltiazem or verapamil.

Case – control study

• Typically examines multiple exposures in relation to a disease;

• subjects are defined as cases and controls, and exposure

histories are compared.

• A case control study starts with patients who already have the

outcome and looks backwards to possible exposures.

• E.g.: Association between periodontitis and low birth weight

• Limitations of a case control study are

• bias (because of the retrospective nature)

• and the difficulty to establish the correct temporal relationship

between the exposure and disease

Cohort study

• take a large population who are already taking a particular

treatment or have an exposure,

• prospective retrospective

follow them forward overtime where both exposure and out

and then compare them for comes have already occurred

outcomes with a similar group when the study begins.

that has not been affected by the -- later examines only prior

treatment or exposure being outcomes and no future ones

Studied.

Ecological study

• It examines the rates of disease in relation to a factor described

on a population level.

• The units of analysis are populations or groups of people

rather than individuals.

Systematic reviews

• Usually focus on a clinical topic and answer a specific

question.

• An extensive literature search is conducted to identify studies

with sound methodology.

• The studies are reviewed, assessed, and the results

summarized according to the predetermined criteria of the

review question.

• E.g: A systematic review of guided tissue regeneration for

periodontal infrabony defects.

Meta-analysis

• Whenever possible, the results of a systematic review are

statistically pooled together to generate a Meta-analysis.

• It is not necessary that every systematic review should

culminate in a meta-analysis.

Experimental

• where something specific is done in the study – i.e., using a

treatment, strategy, or other intervention, that is recorded and

analyzed.

• Experimental studies are commonly classified by their

objective – that is, by whether they investigate a measure that

prevents disease occurrence or a measure that treats an existing

condition.

• The investigator assigns individuals to two or more groups that

either receive or do not receive the preventive or therapeutic

agent.

Randomized controlled clinical trials

(RCTs)

• carefully planned projects

• introduce a treatment or exposure to study its effect on real

patients.

• They include methodologies that reduce the potential for bias

(randomization and blinding)

• allow for comparison between intervention groups and control

groups (no intervention).

• An experiment that can provide sound evidence of cause and

effect.

• also called random allocation, implies that the subjects are

randomly assigned exposures then followed forwards to

achieve an outcome.

Controls

• Clinical trial– comparative in nature

• A clinical trial which includes a comparative group is called a

controlled clinical trial

• No treatment control

• Minus active (Placebo) control

• Benchmark control

• Positive control

• Historical control

Blinding

• Methodologies to reduce potential for bias that allows for

comparison of groups.

• Also called masking is intended to limit the occurrence of

conscious and unconscious bias in the conduct and

interpretation of a clinical trial.

• double blind single blind open-label trial

Experimental designs

• Parallel group

• Crossover trials

• Split-mouth

• factorial

• Parallel group:- each participant is randomly assigned to a

group, and all the participants in the group receive (or do not

receive) an intervention.

• Crossover trials – the subject acts as his/her own control with

the same subject being allocated for both treatments, receiving

them at different times. The possibility of a ‘‘carryover’’ of the

effect of the intervention provided in the first period into the

second intervention period is an important concern in this

study design.

• Split-mouth – separate parts of the mouth of each

participant (i.e., the left and right) are randomized to receive

(or not receive) an intervention.

• A split mouth study design can be used mostly when two

treatment modalities have to be compared, in the same patient

who acts as his own control.

• Factorial – each participant is randomly assigned to a group

that receives a particular combination of interventions or

non-interventions.

• group 1 receives therapy X and therapy Y,

• group 2 receives therapy X and placebo Y,

• group 3 receives placebo X and therapy Y,

• group 4 receives placebo X and placebo Y).

• E.g: A comparison of the effectiveness of the Charters’, scrub,

and roll methods of toothbrushing in removing plaque.

Single centre Vs. multicentre trials

• A clinical trial conducted according to a single protocol but at

more than one site, and therefore, carried out by more than one

investigator is a multi-center trial.

• Multicenter studies offer the potential for increased

recruitment and generalizability from conduct of the trial in

several regions of the country (or world) and also take the

contributions of multiple investigators with complementary

expertise.

Pilot study

• to be done before the starting of a fully-fledged research

project.

• A pilot study is usually carried out on members of the relevant

population, but not on those who will form part of the final

sample.

• Can reveal deficiencies in the design of a proposed experiment

or procedure and

• then be addressed before time and resources are expended on

large scale studies to check the feasibility or to improve the

design of the research.

The hierarchy of evidence

• Evidence-based dentistry has been defined as “the

conscientious, expedient, and judicious use of current best

evidence in making decisions about the care of individual

patients.”

• The principles and methods of evidence-based dentistry have

established their roots well in the present era, where various

decisions regarding patient care are based on choosing the

‘‘best’’ evidence from the ‘‘available’’ evidence.

• Understanding “strength of evidence” and the idea of a

“research design hierarchy” is at the heart of evidence-based

dentistry.

• Evidence is graded based on its strength into different levels

where systematic reviews and randomized controlled trials

represent the highest levels of evidence, whereas case reports

and expert opinion are the lowest.

• For questions related to diagnosis, prognosis or causation,

other study designs such as cohort studies or case-control

studies will often be more appropriate.

• For these types of studies, it may be more appropriate to view

it not as a hierarchy, but as categories of evidence, where the

strongest design which is possible, practical and ethical should

be used.

Implementation of research

• the various ethical norms and standards in human

experimentation,

• the eligibility criteria for the participants,

• sampling methods and sample size calculation,

• various outcome measures that need to be defined and the

• biases that can be introduced in research.

Ethical issues in research

• History of clinical research----several tragedies-----unwitting

participation ------harmed mercilessly.

• The brutal Nazi experiments on prisoners during the world war

II, where human subjects were forcefully and ruthlessly tested

to justify their suppositions was severely criticized and this

inhuman attitude toward human participants prompted the

evolution of various codes and reports.

• The Nuremberg code which was put forward in 1947 was a ten

point statement which defined the conditions under which

acceptable human experimentation should be carried out.

• The Good Clinical Practice (GCP) guidelines by the US Food

and Drug Administration, 1996 regulates the proper conduct of

trials in the United States.

• “The conduct of research in human subjects does not connote

just to the designing of the study and procuring the signature

of the subject on the informed consent form. It also involves

protecting the rights, interests, and safety of research subjects

throughout the study duration.”

….silverman (2007)

• Subject safety monitoring is the responsibility of several

groups, including

research ethics committees or Institutional Review Boards

(IRBs),

investigators

their research staffs,

sponsors, and

data monitoring committees, also called data and safety

monitoring boards,

• All research involving human participants should be cleared

by an appropriately constituted Institutional Ethics Committee,

also referred to as Institutional Review Board (IRB), to

safeguard the welfare and the rights of the participants.

• The IRB is not necessarily constituted by medical people alone

but also has nonmedical people representing the community,

ethicists, clergy or lawyers.

• Once the research protocol and informed consent forms are

approved, the committee undertakes periodic reviews of the

study with detailed reports, to ensure that the conditions are

met in regard to the safety and wellbeing of participants.

• Informed consent should be obtained from every patient (or

legal guardian, if necessary) and has to be included in the trial

proposal.

• This implies that the patient is aware of and understands all the

implications involved in the study which are known to the

researchers, and is willing to accept these as a condition of

his/her involvement in the study.

• It is also important in an epidemiological study that the

research is designed in such a manner that the privacy and the

confidentiality of data are preserved and at the same time the

community health needs are addressed.

Study setting and eligibility (inclusion/exclusion) criteria

• It usually establishes the boundaries of the study with respect

to the sample, sampling area and the time period of the study.

• Prior to the commencement of the study, the study population

should be defined, along with the characteristics of the

subjects that are to be included (inclusion criteria).

• The characteristics of the subjects which are not to be included

in the study (exclusion criteria) need to be established.

Sampling

• A sample (n) is a ‘‘Finite’’ part of a statistical population

whose properties are studied to gain information about the

‘‘WHOLE’’.

• A sampling frame, refers to a list of available population

members, for example a list of patients, or the census data etc.

probability

Non-probability

Class.1

Purposive

Non-purposive

Class.2

• A purposive (non-probability/deliberate) sample is one which

is selected by the researcher subjectively.

• Convenience sampling :- where the population elements are

selected for inclusion in the sample based on the ease of

access.

• Quota sampling

• The population is first segmented into mutually exclusive

sub-groups, just as in stratified sampling. Then judgment is

used to select the subjects or units from each segment based on

a specified proportion, which makes the technique one of

non-probability sampling.

• A non-purposive (probability) sample is one in which every

unit in the population has a chance (greater than zero) of being

selected in the sample, and this probability can be accurately

determined.

• Types of probability sampling:

Simple Random Sampling

Stratified random Sampling

Systematic Random Sampling

Cluster Random sampling

Simple random sampling

• also known as chance sampling

• where each and every subject in the population has an equal

chance of inclusion in the sample and each one of the possible

samples has the same probability of being selected.

• Methods of simple random sampling include coin toss, random

selection of numbers, lottery, and computer generation of

numbers.

Systematic sampling

• a systematic method

• the selection process starts by picking some random points in

the list and then every nth element is selected until the desired

number is secured.

Stratified sampling

• The population is stratified into a number of non-overlapping

subpopulations or strata and sample items are selected from

each stratum.

• If the item selection from each stratum is based on simple

random sampling, then the entire procedure, first stratification

followed by simple random sampling, is known as stratified

random sampling.

• E.g. strata of age groups; gender (male/female) etc.

Cluster sampling and area sampling

• Cluster sampling involves grouping the population and then

selecting the groups or the clusters rather than individual

elements for inclusion in the sample.

• When all the units within a cluster are selected, the technique

is referred to as one-stage cluster sampling.

• If a subset of units is selected randomly from each selected

cluster, it is called two-stage cluster sampling

Multi-stage sampling

• Technique is meant for larger data extending to a considerably

large geographical area like an entire country.

• In multi-stage sampling the first stage may be to select large

primary sampling units such as states, districts, towns, and

finally certain families within towns.

Sample size estimation

• The calculation of the size of the sample to be surveyed in a

research project is pivotal as it would facilitate the researcher

with some information on the timeframe, logistics of the

project and also the future generalizability and relevance of the

results.

• what is the result of other studies which used a similar

intervention?

• Or what is the range of the present level of or rate of

occurrence of the event that we are interested in?

• what is the level of α or β errors that we are willing to accept?

• To what extent our result could be due to chance?

• Conventionally, 5% for type 1 and 20% for type II error is

accepted.

• what is the result we are expecting?

• That is, what is the clinically meaningful difference?

• For field survey

n = 4pq

l2

• For quantitative data

n = 4s2

l2

The observational unit (subject vs. site)

• The unit of observation in an experiment or observational

study is the smallest unit with a unique set of important

characteristics which is independent of other similar units in

that its response cannot be affected by these other units.

• In clinical trials, usually the subject or the mouth is selected as

an observational unit.

• The study should be designed and analyzed in such a way that

the randomization process should randomize the experimental

units (the mouths) rather than sub-units (the teeth) to the

different treatments.

Examiner training and standardization/calibration

• The clinical examiners who are assessing patients are

well-trained and calibrated in order to achieve good

reproducibility of data with minimal error and bias.

• Hefti and Preshaw introduced the term ‘‘Examiner alignment

and assessment’’ as a more descriptive term for the process of

training examiners who will participate in a clinical trial.

Bias and confounding

• ‘‘opinion or feeling that favors one side in an argument or one

item in a group or series.’’

• In an epidemiological perspective, bias is present when the

results from the study are systematically distorted and so are

consistently above (or below) what they should be.

• Sackett in 1979 identified 24 biases.

Selection Bias

• When the study participants are not representative of the

population of interest.

• This bias usually happens during the selection of subjects for

control and test groups where the investigator assigns subjects

such that they differ with respect to extraneous factors.

Observer or measurment bias

• When an examiner consistently over/under reports a variable

(a characteristic).

• This must be resolved in training and calibration sessions.

• Recall bias :-

• An information bias in which the subjects with disease (cases)

tend to recall past exposures better than controls.

• Attrition bias :-

• when subjects quit the study before its completion.

• These drop outs in the clinical trial cause bias in the results

due to the decreased sample size in one group or may be both,

and also the decreased follow up time period.

• Migration bias

• Another kind occurs either when individuals drop out of

study or move from one group to another.

• Publication bias

• Studies which show significant results are more likely to

be published in journals than those with insignificant or

negative results.

• Allocation bias

• When treatment groups in an experimental study are not

comparable with respect to the variables influencing the

response of interest.

Confounding

• Confounding is a mixing of the effect of an exposure with the

effect of another variable that is associated with the exposure

and is an independent risk factor for the disease.

• Confounding factors are variables, which compete with the

hypothesized risk factor as explanations for the observed

response.

Contamination

• It occurs when an intervention administered to an intervention

group of an experimental study percolates into the control

group.

• This is usually seen in a split mouth study or in a crossover

study where the intervention from one site filters into the

control treatment.

• It could also be seen with respect to information which is

given from one group by word of mouth to the members in the

other group.

Hawthrone effect

• Roethlisberger and Dickson in 1939.

• Individual behaviour may be altered when participant knows

he is being observed.

• Subjects who are singled out to participate in a mouthwash

trial consciously tend to improve their oral hygiene and may

show lower plaque scores.

Rosenthal effect (experimenter effect)

• The expectations and biases of an experimenter can be

communicated to experimental subjects in unintentional ways

and these clues may significantly affect the outcome of the

experiment.

• Experimenter effects can be avoided by using double blinded

studies where the experimenters’ expectations and biases are

not communicated to the study subjects.

Evaluation of diagnostic & screening tests

• Reliability

• Validity

• Sensitivity

• Specificity

• Reliability is the extent to which an experiment, test, or any

measuring procedure yields the same result on repeated trials.

• Validity refers to whether a study is able to scientifically

answer the questions, it is intended to answer.

• Sensitivity is the probability (usually expressed as a

percentage) that a subject with the disease will have a positive

test result.

• Specificity is the probability that a subject who is free of the

disease will have a negative test result.

• The best tests are the ones that are good at detecting most of

the people with the condition (high sensitivity) and at

excluding people who do not have the condition (high

specificity).

Outcome measure and endpoints in research

Lab measures

• Biological tests on cell cultures

•Mechanical tests on clinical materials

Clinical measures

•Various indices

Pt-based measures

• Patient perceptions

• questionnaire

Primary question that the study is designed to answer

Trial is powered to answer such a question

Primary

Other outcome of intrest

Often includes unintended and unanticipated effects of the intervention

Secondary

• End points :- An endpoint is any measurement that is thought

to be related to the disease process and that is used to assess

treatment efficacy.

• Researchers are usually faced with the challenge of selecting

an endpoint that provides clear, unequivocal evidence of a

benefit to the patient.

True

How a patient feels, functions or survives

Pain, bleeding on brushing, and oral health

related quality of life

Surrogate

Intermediate endpoints, biological markers,

Probing depth, measures of inflammation, microbiological measures and

immunologic measures

Representation of data

• All the data are entered manually on paper or directly entered

into a spread sheet or database or directly into a computer.

• Analysis of data :-

establishment of categories,

the application of these categories to raw data through coding,

tabulation and

then drawing statistical inferences.

• Data file can take the form of a spreadsheet with

• individual people the rows and

• the variables columns.

• A variable is something that can be changed, such as a

characteristic or value.

• two types of variables – dependent and independent.

• The variable(s) we measure as the outcome of interest is the

dependent variable (Y variable), or response/effect. The

independent or the X variable causes an effect that is seen

on the dependent variable.

1. quantitative

• Data can

2. qualitative

• (i) Quantitative data which measure either how much or how

many of something, i.e., a set of observations where any single

observation is a number that represents an amount or a count.

• (ii) Qualitative data which provide the quality of observations,

i.e., it describes something.

• Qualitative data:-

i. Nominal/categorical data:- variables with no inherent order

or ranking sequence.

Dichotomous/binary data

ii. Ordinal/rank data:- variables with an ordered series.

iii. Interval :- do not have a true zero but has an arbitary zero.

iv. Ratio scale:- has a definite “0” as the starting point true zero

point.

• Quantitative data:-

i. Discrete/discontinuous:- in the form of integers and has no

intermediate points.

ii. Continuous:- can be divided into fractions of whole numbers

like height, weight.. etc.

• Paired versus unpaired data:-

• Unpaired (independent or unmatched) data are obtained from

two groups that are unrelated to each other.

• Paired or matched data are where the measurements are taken

on the same individual or matched groups as in a split mouth

or same group before and after or cross over designs.

Statistical analysis

• In research, usually both descriptive and inferential statistics

are used to analyze the results and draw conclusions.

Descriptive statistics

• include the numbers, tables, charts, and graphs used to

describe, organize, summarize, and present raw data.

measures of central tendency

• They include

measures of dispersion

• Variability, in a statistical sense, is a quantitative measure of

how close together or spread out the distribution of scores is.

• The two measures which quantify variability are

• the standard deviation (SD):- individual observations in a

study sample,

• the standard error (SE):- the SE quantifies the variability of

observed sample means if the study were repeated many times.

Inferential statistics

• To draw conclusions and predictions based on analysis of

numeric data.

• Inferential statistics are frequently used to answer cause and

effect questions.

• To investigate differences between and among groups.

• Two approaches to quantify this uncertainty are

(i) Hypothesis testing, which is associated with P values, and

(ii) Estimation, which is associated with confidence intervals

(CIs).

• Hypothesis testing:- For any study to make any inference

about any relationship between the proposed

intervention/treatment and the outcome, hypothesis testing is a

fundamental requisite.

• Statistical inference is achieved usually by means of

hypothesis testing using P value (Probability value).

• P-value refers to the probability of detecting a statistically

significant difference that is not the result of the treatment but

the result of chance.

• The most commonly used criteria are probabilities of 0.05

(5%, 1 in 20), 0.01 (1%, 1 in 100), and 0.001 (0.1%, 1 in

1000).

Estimation

• While the P value is based on a single value or point estimate

derived from the data, a second form of statistical inference,

interval estimation.

• In estimation,

the sample study provides an estimate of the effect of the

intervention in the population and

consideration of sampling error yields an interval, known as a

confidence interval, which is reasonably certain to contain the

(unknown) true population effect.

• The confidence interval (CI) is used to estimate the upper and

lower limits of the variability in the sample data.

Odds ratio and relative risk

• Risk ratio is ratio of probabilities of 2 events.

Or,

incidence of disease in exposed group

incidence in non-exposed.

• Odd’s ratio:- probability of event occurring

probability of event not occurring

Inference of statistical test

• To draw inferences – statistical tests are used.

• 2 types:- 1. parametric tests

2. non-parametric tests

• Parametric tests:-A statistical test which concerns population parameters and requires assumptions about these parameters.

• Parametric data have an underlying normal (Gaussian) distribution which allows for more conclusions to be drawn as the shape can be mathematically described.

• T-test, correlation, regression, analysis of variance (Anova).

Non-parametric tests

• These tests rely more on the differences in medians rather than

on the estimation of parameters (such as the mean or the

standard deviation) and hence also referred to as

distribution-free methods.

Intention to treat analyses (ITI)

• avoid the biases that would be otherwise introduced by the

alternatives of either omitting the results or analyzing the

results according to the treatments that these patients actually

received.

• It is most suitable for pragmatic trials of effectiveness rather

than for explanatory investigations of efficacy.

• including all patients, regardless of whether they actually

satisfied the entry criteria, the treatment actually received, and

subsequent withdrawal or deviation from the protocol

• Intermediate or interim analyses:-

• Sometimes the investigators in a clinical trial may wish to

perform significance tests at intermediate stages to evaluate

treatment effects and if one treatment is found to be superior,

the trial can be stopped early and all the patients will go on to

receive the most effective treatment.

Clinical vs. statistical significance

• To be clinically important requires a substantial change in an

outcome that matters.

• While statistical significance answers the question, “Is this a

real effect?”,

• clinical significance answers the question, “Is this an important

effect?”.

• One cannot be inferred from the other.

• The results of a study may show statistical significance but

may be clinically insignificant.

Writing of a report

• The report should be structured and should have the following

contents.

• Title

• Abstract

• Introduction

• Materials and methods

• Results

• Discussions

• Conclusion

• Bibliography or references

• Title:- should reflect the content and emphasis of the project

described in the report.

• Abstract:- A primary objective of an abstract is to

communicate to the reader the essence of the paper. The

abstract should concisely describe the topic, the scope, the

principal findings, and the conclusions.

• Introduction :- objective of the research

methodology adopted

background information of the problem

scope of study with various limitations.

• Materials and methods:- the experimental details,

computation procedures

theoretical analysis

• Results:- Relevant data, observations, and findings of the study

are summarized.

• Discussion:- the analysis and interpretation of the results.

What do the results mean?

How do they relate to the objectives of the project?

To what extent have they resolved the problem?

How do they differ from other reports

and what could be the possible reasons?

• Conclusion:-

the final summing up of the most significant results/ findings

where the researcher should again put down the results of his

research clearly and precisely at the end of the document.

Directions for future work can also be included in this section.

• Bibliography or references:- contain a complete list of all the

sources (books, journal articles, websites, etc.) that are cited

directly in a document.

• Each reference entry has four parts: the name of the author, the

year of publication, the title, and further publication

information.

• Tables and figures:- Representation of data in the form of

tables and graphs makes it very easy for the reader to interpret

the results of a study in a comprehensive manner.

• Plagiarism:-

To use someone else’s exact words without quotation marks

and appropriate credit, or to use the unique ideas of someone

else without acknowledgment, is known as plagiarism.

• Paraphrasing:-

When a written passage is paraphrased, you rewrite it to state

the essential ideas in your own words. The paraphrased

material must be properly referenced because the ideas are

taken from someone else whether or not the words are

identical.

• CONSORT:- (Consolidated standards of reporting trials)

• STARD (standard for reporting diagnostic accuracy)

• PRISMA (Preferred Reporting Items for Systematic Reviews and

Meta-Analyses) formerly QUOROM (Quality of Reporting of

Meta-analyses),

• MOOSE (Meta-analysis Of Observational Studies in Epidemiology),

• QUADAS(Quality Assessment of studies of Diagnostic Accuracy included

in Systematic reviews)

• STROBE:- Strengthening the Reporting of Observational studies in

Epidemiology.

Conclusion

• Research in dentistry continues apace.

• In order to conduct clinically relevant research, we need to ask

the important research questions of the day.

• So that we may undertake research that generates the highest

quality of data so that our findings can be translated into

everyday clinical practice.

Thank you