Research Made EasyAssoc. Prof. Dr. Jamalludin Ab Rahman MD MPHDepartment of Community MedicineKulliyyah (Faculty) of Medicine

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Effective strategies to produce good research.

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Good research isnot just producing new information but it should contribute new knowledge.

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Start with end in mind(Bijaksana)

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Idea

Justify Explore Strategize

Collect

Analyse Report Publish

Initiation

Planning & strategize (proposal)

Data collection

Reporting & sharing

Study designSampling planSample size determinationPlan for data collectionPlan for statistical analysis

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The 4 easy steps1. Clear conceptual framework2. SMART objectives3. Detail data dictionary4. Expected dummy table

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Clear conceptual frameworkPreparing the blue print of your research

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What is conceptual framework? Visual representation of your problem

statement and research gap End product of literature review and your

assumptions No specific format But I propose using ‘causality’ approach

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Constructing objectiveSpecific, Measurable, Attainable, Relevant & Timely

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Criteria Explanation

Specific Who is the target population? What is actually done?

Measurable State the measurement done

Attainable Realistic in term of time & expertise

Relevant Relevant to the whole study (title)

Timely Defined time

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Example To find prevalence of hypertension among school

children

To measure prevalence of high blood pressure among secondary school children in Pahang from January to June 2016

SpecificMeasurable Specific

TimelySpecific

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Approach1. General – Specific

Specific objectives are subsets of the general objective Specific objectives determine the order of the

analysis/report2. Primary – Secondary

Primary & secondary are independent objectives Primary = main outcome, not necessary to be

analysed/reported first

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Example 10 D

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Specific objective is the backbone of your study

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It determines:1. What variables to collect2. The sequence for reporting

results3. How you discuss the study

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Detail data dictionaryNothing hidden

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Data dictionar

y

Definition used

Protocol for measureme

nt

CodebookStatistics

operational definition &

code

Linkage to source of

data

e.g.• anthropometric

measurements (weight, height etc.)

• clinical examination

• laboratory investigation (e.g. blood glucose, HbA1c)

• QOL (SF36, HRQOL etc)• DASS

questionnaireFor categorical data e.g.• Sex, 1=Male,

2=Female• Pregnancy, 1=Yes,

0=No, 99=Not applicable (for male respondent)

Operational definition for statistics purpose e.g.• Asthma Yes if, Q1=1

and Q2=1 and Q3=2 or Q4=1 (based on the questionnaire form)

Source of data for certain variables e.g.• BMI is calculated from

variable Weight (in kg) and Height (in cm) defined elsewhere

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What’s the info for? Standardisation of data collection Proper declaration of instruments &

measurement used For statistical analysis

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Describe clearly all the variables used Definition Operation definition Instrument used to measure the variable

How it will be measured? What is the instrument used? How precise will you measure it? How will you categorise it (if relevant)?

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Definition vs. Operational definition e.g. Obese Definition: A condition of abnormal or excessive

fat accumulation in adipose tissue, to the extent that health may be impaired (WHO 1998)

Operational: BMI ≥ 30 kg/m2 (WHO 1998)

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Definition vs. Operational definition e.g. Hypertension Definition: A chronic medical condition in which

the blood pressure in the arteries is persistently elevated

Operational: BP ≥ 140/90 (JNC7 2004)

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Example of a data dictionaryName Label Tool Level of

measurement

Code Unit Precision Link

age Age (years) Questionnaire Numerical N/A Years Nearest 1 year

sex Sex Questionnaire Categorical 1=Male2=Female

N/A N/A

weight Body weight (kg)

Seca 762 Numerical N/A kg Nearest 0.1 kg

height Height (cm) Seca 206 Numerical N/A cm Nearest to 1 cm

obese Obesity Based on BMI calculation. BMI ≥ 30 kg/m2 (WHO 1998)

Categorical 1=Yes2=No

N/A N/A Refer to Weight & Height

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Adapt & adopt known scale How valid is the scale – Refer to original paper You may need to translate & validate it Even if had been validated, you need to pre-test it Easier to validate a known tool rather than to

create one

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Produce your dummy tableBased on your specific objectives

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Mock table (or graph) create PRIOR to data collection

Dummy table is a smart table

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How will you present the results? Table or graph or even texts Answer for each objective Can include your expected results

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How to report your research? Clinical study – CONSORT (www.consort-statement.org) Observational study – STROBE (www.strobe-statement.org)

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The 4 steps that will ease your research are:1. Clear conceptual framework2. SMART objectives3. Detail data dictionary4. Expected dummy table

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