Research requires properly planned methodology. I would like to recommend that researchers to focus on these 4 critical steps. If these steps are fulfilled, you will find it easy to conduct your research.

1. Research Made Easy
Assoc. Prof. Dr. Jamalludin Ab Rahman MD MPH
Department of Community Medicine
Kulliyyah (Faculty) of Medicine

2. Effective strategies
to produce
good research.
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Good research is
not 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 design
Sampling plan
Sample size determination
Plan for data collection
Plan for statistical analysis
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6. The 4 easy steps
1. Clear conceptual framework
2. SMART objectives
3. Detail data dictionary
4. Expected dummy table
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7. Clear conceptual framework
Preparing the blue print of your research
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8. 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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11. Constructing objective
Specific, 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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13. 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
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SpecificMeasurable Specific
Timely
Specific
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14. Approach
1. General – Specific
 Specific objectives are subsets of the general objective
 Specific objectives determine the order of the
analysis/report
2. Primary – Secondary
 Primary & secondary are independent objectives
 Primary = main outcome, not necessary to be
analysed/reported first
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15. Example
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Specific objective is the
backbone of your study
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It determines:
1. What variables to collect
2. The sequence for reporting results
3. How you discuss the study

17. Detail data dictionary
Nothing hidden
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Data
dictionary
Definition
used
Protocol for
measurement
Codebook
Statistics
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 questionnaire
For 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.
• AsthmaYes 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

19. What’s the info for?
 Standardisation of data collection
 Proper declaration of instruments &
measurement used
 For statistical analysis
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20. 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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21. 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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22. 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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23. Example of a data dictionary
Name 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=Male
2=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=Yes
2=No
N/A N/A Refer to
Weight &
Height
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24. 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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27. Produce your dummy table
Based 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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29. 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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30. How to report your research?
 Clinical study – CONSORT (www.consort-statement.org)
 Observational study – STROBE (www.strobe-statement.org)
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33. The 4 steps that will ease your
research are:
1. Clear conceptual framework
2. SMART objectives
3. Detail data dictionary
4. Expected dummy table
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