Which of the following is not a causal guideline?
sample size
biological plausibility
consistency of association
strength of association
The correct answer and explanation is:
The correct answer is sample size.
Explanation:
Causal guidelines are criteria used to establish whether a relationship between a cause and an effect is valid. Sir Austin Bradford Hill proposed nine principles to guide the determination of causality in epidemiology. These principles are:
- Strength of association: The stronger the association between an exposure and an outcome, the more likely it is causal. A large effect size supports a causal link.
- Consistency of association: This refers to the repeated observation of the association in different studies, settings, and populations. Consistent findings strengthen the likelihood that the relationship is causal.
- Biological plausibility: This guideline suggests that the relationship between exposure and outcome should make sense biologically. There should be a known mechanism that can explain how the exposure leads to the outcome.
- Temporality: The cause must precede the effect in time. This is a fundamental criterion for establishing causality, as an effect cannot occur before its cause.
- Specificity: The more specific the association (i.e., a single cause leads to a single effect), the stronger the argument for causality.
- Dose-response relationship: If an increase in exposure leads to an increase in the effect (or vice versa), this suggests causality.
- Reversibility: If removing or reducing the exposure leads to a decrease in the effect, it provides evidence of causality.
- Coherence: The relationship should be consistent with known facts about the disease or phenomenon, fitting within the broader body of scientific knowledge.
- Experiment: The ability to demonstrate causality through experimental evidence (e.g., clinical trials) can be a strong argument for a causal link.
Sample size, on the other hand, is a methodological consideration rather than a causal guideline. While a larger sample size can increase the precision and reliability of a study, it does not provide direct evidence for a causal relationship. A small sample size can still yield valid causal conclusions, though it may limit the generalizability of the findings.