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Presentation at Course Program held at King Fahad Medical City, Riyadh via Online Course at 1:00 PM - 3:00pm on 30 August 2020 by Professor Omar Hasan Kasule MB ChB (MUK), MPH (Harvard), DrPH (Harvard) Professor of Epidemiology and Bioethics King Fahad Medical City
INTRODUCTION
• The concepts and procedures of study analysis discussed in this section are needed for critical reading of scientific literature.
• There are many scientific journals many of which are peer-reviewed and they try to maintain the highest standards.
• There are however lapses from time to time that allows poorly- designed, poorly-analyzed, or poorly-reported studies to be published.
• The reader must be equipped with tools to be able to analyze their methodology and data analysis critically before accepting their conclusions.
THE COMMON PROBLEMS IN PUBLISHED STUDIES
• Incomplete documentation.
• Design deficiencies.
• Improper significance testing and interpretation.
TITLE, ABSTRACT, and INTRODUCTION
• The title must be relevant to the body of the article.
• The abstract is very important since it shows the focus of the study. It gives summary information that can be used for preliminary assessment of (a) study design and analysis (b) significance of the conclusions.
• The decision whether to read further can be made after studying the abstract. The introduction states the reason for the study. It reviews previous studies in order to establish the need for the study and indicate its potential contribution.
• The introduction gives a general background and a historical perspective to the study. It may also refer to the population to be studied.
• The hypothesis of the study may also be stated in the introduction. Having a prior hypothesis prevents the pitfalls of going on a fishing expedition.
MATERIALS AND METHODS 1: OVERVIEW
The materials and methods section covers the following: }study subjects,
• study design,
• data collection,
• data analysis,
• assessment of errors.
MATERIALS AND METHODS 2: Study subjects
• Identification of the study population,
• Identification of the sample,
• Methodology of sampling,
• Methods of subject selection,
• Eligibility and exclusion criteria,
• Exposure and outcome criteria,
• Sample size,
• Study power,
• Representativeness of the sample.
MATERIALS AND METHODS 3: Study design
• Experimental study: community or clinical randomization.
• Observational (follow-up, cross-sectional, case-control).
• Common design deficiencies: Study design not appropriate for the hypothesis tested lack of a comparison group, selecting a control sample from a population different from that of the study sample, Sample size not being big enough to answer the research questions raised.
MATERIALS AND METHODS 4: Data collection and analysis
• Data collection involves records, measurements, or interviews. An assessment must be made of the accuracy of measurements.
• Data analysis may be descriptive or analytic. An assessment is made whether the appropriate scale and test were used.
• Data normality is also assessed since the statistical test is determined by normality.
RESULTS
• The reporting of results is sometimes selective showing only favorable outcomes.
• Missing denominators and numbers that do not add up are common deficiencies.
• Tables must be labeled well and completely. Marginal totals (rows or columns) must equal the sum of the respective cells. The column totals must equal row totals. Row or column percentages must add up to 100%s. Numbers in the table must reconcile with the text.
• A check is made on numerical consistency: rounding, decimals, units.
• The following must be checked about statistical tests: is hypothesis testing using confidence intervals or p-value? Are both negative and positive findings presented?
• The following pit-falls are common with the t-test: not stating the degrees of freedom, not stating the CI, use of the t-test for non- Gaussian data, and Multiple comparisons.
CONCLUSIONS / DISCUSSIONS 1: Overview
• The conclusion highlights the major findings without repeating the results section.
• Consistency of conclusions with the data and hypothesis, was there extrapolation beyond the data?
• What are the shortcomings and limitations?
• The statistical conclusions are evaluated after assessment of errors (random & non-random) and assessment of bias (misclassification, selection, and confounding).
CONCLUSIONS / DISCUSSIONS 2: common pitfalls of statistical conclusions
• Use of wrong statistical test,
• Drawing inappropriate conclusions for example significant findings may not be important or important findings may not be significant,
• Wrong interpretation of the age effect by ignoring the cohort effect.
CONCLUSIONS / DISCUSSIONS 2: common pitfalls of statistical conclusions, con’t.
• A distinction must be made between precision (lack of random error: size and efficiency) and validity (lack of systematic error). Validity is internal & external. Internal validity is ensuring that the study carried out was accurate in its findings. Internal validity is achieved when the study is internally consistent and the results and conclusions reflect the data. External validity is generalizability ie how far can the findings of the present study be applicable to other situations. External validity is achieved by several independent studies showing the same result. The following are common mistakes: numerator without a denominator, inappropriate denominator, a missing comparison group, inappropriate comparison, missing standardization for age, loss of information due to censoring (loss to follow-up), inappropriate tests for rates based on person-year, using mean +/- 2SD on non-normal data, the Berkson's fallacy, and multiple comparison or multiple significance.