AIIMS PG (DM/MCh) Entrance Community Medicine, Research Methodology and Ethics Syllabus

Community Medicine, Research Methodology and Ethics syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for Community Medicine, Research Methodology and Ethics in AIIMS PG (DM/MCh) Entrance, not a summary of it.

1. 1

   Epidemiology and Biostatistics

   3 topics

   • Epidemiological Methods
     • Study designs: cohort, case-control, RCT
     • Measures of association and bias
   • Biostatistics
     • Descriptive statistics and distributions
     • Hypothesis testing and p-values
     • Sample size and statistical tests
   • Screening and Diagnostic Tests
     • Sensitivity, specificity and predictive values
     • ROC curves and likelihood ratios
2. 2

   Research Methodology and Evidence-Based Medicine

   3 topics

   • Critical Appraisal
     • Levels of evidence and systematic reviews
     • Meta-analysis interpretation
   • Clinical Trials
     • Phases of clinical trials
     • Randomization and blinding
   • Publication and Scientific Writing
     • Manuscript structure and reporting guidelines
     • Plagiarism and authorship
3. 3

   Public Health and National Programs

   3 topics

   • National Health Programs
     • Communicable disease control programs
     • Non-communicable disease and maternal-child programs
   • Health Systems and Demography
     • Health planning and indicators
     • Demographic transition and vital statistics
   • Nutrition and Environmental Health
     • Nutritional assessment and deficiency diseases
     • Water, sanitation and occupational health
4. 4

   Medical Ethics, Law and Professionalism

   3 topics

   • Bioethics Principles
     • Autonomy, beneficence, non-maleficence, justice
     • Informed consent and confidentiality
   • Research Ethics
     • Institutional ethics committees and ICMR guidelines
     • Ethics of human and animal research
   • Medical Law and Forensic Aspects
     • Medical negligence and consumer protection
     • Organ transplantation and brain death law

Community Medicine, Research Methodology and Ethics flashcards for AIIMS PG (DM/MCh) Entrance

20 of 51 cards from the Community Medicine, Research Methodology and Ethics deck — real questions with worked answers.

1. Define incidence and prevalence, and state how they relate.

   Incidence = number of NEW cases occurring in a population at risk over a time period. Prevalence = total (existing + new) cases at a point/period. Relationship: Prevalence ≈ Incidence × Duration of disease (P = I × D) for steady-state chronic conditions.

2. What is the difference between a cohort study and a case-control study in terms of direction and the measure of association each yields?

   Cohort study is prospective (exposure → outcome), yields Relative Risk (RR) and incidence. Case-control study is retrospective (outcome → exposure), yields Odds Ratio (OR); incidence cannot be directly calculated.

3. Give the formula for Relative Risk (RR) in a cohort study using a 2x2 table (a,b = exposed diseased/non-diseased; c,d = unexposed diseased/non-diseased).

   RR = [a/(a+b)] / [c/(c+d)] = incidence in exposed / incidence in unexposed.

4. Give the formula for the Odds Ratio (OR) in a case-control study (a,b,c,d as in standard 2x2 table).

   OR = (a × d) / (b × c), the cross-product ratio.

5. Define Attributable Risk (AR) and Attributable Risk Percent.

   AR (risk difference) = Incidence in exposed − Incidence in unexposed. AR% = [(Ie − Iu)/Ie] × 100, the proportion of disease in the exposed attributable to the exposure.

6. What is Population Attributable Risk (PAR) and its percent?

   PAR = Incidence in total population − Incidence in unexposed. PAR% = [(Ipop − Iu)/Ipop] × 100; it estimates the disease burden in the whole population removable by eliminating the exposure.

7. What is a confounder, and name two methods to control it at the analysis stage.

   A confounder is a variable associated with both exposure and outcome but not on the causal pathway. Analysis-stage control: stratification (e.g., Mantel-Haenszel) and multivariable regression. (Design-stage: randomization, matching, restriction.)

8. List the Bradford Hill criteria for causation (any 6 of the 9).

   Temporality (essential), Strength of association, Dose-response (biological gradient), Consistency, Specificity, Biological plausibility, Coherence, Experimental evidence, Analogy.

9. Distinguish selection bias from information (measurement) bias.

   Selection bias: systematic error in how subjects enter/remain in the study (e.g., Berkson's, healthy-worker effect). Information bias: systematic error in measuring exposure/outcome (e.g., recall bias, observer bias, misclassification).

10. What is a confounder versus an effect modifier (interaction)?

    A confounder distorts the true association and should be adjusted/removed. An effect modifier genuinely changes the magnitude/direction of the association across strata and should be reported separately (not adjusted away).

11. Define mean, median, and mode, and state which is preferred for skewed data.

    Mean = arithmetic average. Median = middle value when ordered. Mode = most frequent value. For skewed distributions the MEDIAN is preferred as it is unaffected by extreme values.

12. What is the difference between standard deviation (SD) and standard error of the mean (SEM)?

    SD measures variability/spread of individual observations. SEM = SD/√n, measures precision of the sample mean estimate. SEM is always smaller than SD and decreases with larger n.

13. State the empirical (68-95-99.7) rule for a normal distribution.

    In a normal distribution: ~68% of values lie within mean ±1 SD, ~95% within ±2 SD (precisely ±1.96 SD), and ~99.7% within ±3 SD.

14. Define a p-value and the conventional threshold for statistical significance.

    The p-value is the probability of obtaining results as extreme or more extreme than observed, assuming the null hypothesis is true. Conventional significance threshold is p < 0.05.

15. Define Type I and Type II errors, and the related quantities alpha, beta, and power.

    Type I error (α) = rejecting a true null (false positive). Type II error (β) = failing to reject a false null (false negative). Power = 1 − β = probability of detecting a true effect.

16. When should you use a paired t-test versus an unpaired (independent) t-test?

    Paired t-test: two measurements on the SAME subjects (before/after, matched pairs). Unpaired t-test: comparing means of two INDEPENDENT groups. Both assume approximately normal data.

17. Which test compares means across three or more groups, and what is its non-parametric equivalent?

    ANOVA (analysis of variance) compares means across ≥3 groups (parametric). Non-parametric equivalent: Kruskal-Wallis test.

18. What is the chi-square test used for, and name a non-parametric test for comparing two related ordinal/paired groups.

    Chi-square tests association between categorical variables (observed vs expected frequencies). Wilcoxon signed-rank test compares two paired/related non-normal groups; Mann-Whitney U for two independent non-normal groups.

19. What does a 95% confidence interval represent, and when does it indicate non-significance for an OR/RR or a difference?

    A 95% CI gives the range within which the true value is expected to lie with 95% confidence. Non-significant if the CI for OR/RR includes 1, or if the CI for a difference between means includes 0.

20. Define sensitivity and specificity of a screening/diagnostic test.

    Sensitivity = TP/(TP+FN) = ability to correctly identify those WITH disease (true positive rate). Specificity = TN/(TN+FP) = ability to correctly identify those WITHOUT disease (true negative rate).

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