Patient who refuses whitening because of a cancer claim

Correct answer: D. Tooth whitening

• A. No whitening is the COMPARISON or control condition.
• B. Oral cancer is the OUTCOME — the event being measured.
• C. Adults seeking cosmetic treatment constitute the POPULATION.
• D. CORRECT. PICO breaks a clinical question into Population, Intervention, Comparison and Outcome. Here the Population is adults undergoing cosmetic dental treatment, the INTERVENTION is tooth whitening, the Comparison is no whitening, and the Outcome is the incidence of oral cancer. The intervention is always the exposure or treatment being evaluated.

Correct answer: D. A randomised controlled trial

• A. A cohort study follows groups defined by an exposure they already have. The investigator observes; they do not assign.
• B. A cross-sectional study measures exposure and outcome at a single point in time and is purely observational.
• C. A case-control study looks backward from outcome to exposure. It is observational and retrospective.
• D. CORRECT. In an interventional (experimental) study the investigator ASSIGNS the exposure. In a randomised controlled trial participants are allocated by chance to receive the intervention or the comparator, which is what makes it experimental. In all observational designs the investigator only watches what happens.

Correct answer: B. A randomised controlled trial

• A. Case-control studies are vulnerable to recall bias and selection bias, and can only adjust for confounders that were measured.
• B. CORRECT. Randomisation is the only method that distributes UNKNOWN and unmeasured confounders evenly between groups, because allocation is independent of every patient characteristic — including those nobody has thought to measure. Statistical adjustment in observational studies can only handle confounders that were identified and recorded.
• C. A cross-sectional survey cannot establish temporality at all, let alone control unmeasured confounding.
• D. A case series has no comparison group and therefore no control of confounding whatsoever.

Note: The evidence hierarchy, ascending: case report → case series → cross-sectional → case-control → cohort → randomised controlled trial → systematic review and meta-analysis.

Correct answer: B. Prevalence

• A. Attributable risk is the excess risk in the exposed group attributable to the exposure.
• B. CORRECT. Prevalence is the total number of EXISTING cases — new and old together — present in a population at a given time. It measures the burden of disease and is the figure that matters for planning services and allocating resources.
• C. Incidence counts only NEW cases arising during a defined period. It measures risk of developing the disease and is the figure used to study causation.
• D. Relative risk compares the incidence between an exposed and an unexposed group. It is a ratio, not a count.

Note: The relationship worth remembering: prevalence ≈ incidence × duration. A disease that is common but short-lived has high incidence and low prevalence; a chronic incurable disease accumulates prevalence even with modest incidence.

Correct answer: D. Failing to detect a difference that genuinely exists (a false negative)

• A. That describes a Type I error (alpha) — a FALSE POSITIVE, rejecting a true null hypothesis. Alpha is conventionally set at 0.05.
• B. Inaccurate measurement is measurement or information bias, again a different category of problem.
• C. Unrepresentative sampling is selection bias, a threat to external validity, not a hypothesis-testing error.
• D. CORRECT. A Type II error (beta) is a FALSE NEGATIVE — the null hypothesis is accepted when it is in fact false, so a real effect is missed. The commonest cause is inadequate sample size. Statistical power equals 1 minus beta, and studies are conventionally designed for at least 80% power.

Note: Mnemonic: Type I error — you see something that isn't there (false positive, alpha). Type II error — you miss something that is there (false negative, beta).