Lesson 1.3.2

1.3.2 Evaluating studies of health risk factors Quiz: Pearson Edexcel Biology A (Salters-Nuffield), Unit 1

20 questions

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Lesson 1.3.2, Evaluating studies of health risk factors: 20 multiple choice questions for the Pearson Edexcel Biology A (Salters-Nuffield) (9BI0), Unit 1: Lifestyle, Health and Risk, written with Revision Ninja.

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The 20 questions

  1. In a cohort study, what is the main way participants are grouped?

    • By whether they already have the disease, and then their past exposures are compared
    • By whether they were exposed to a risk factor, and then followed over time to see who develops disease
    • By random assignment to a treatment or placebo group, which is then given at the start
    • By a single survey at one point in time, which records exposure and disease together

  2. Which study design is best for showing that a treatment causes an effect?

    • A cross-sectional survey, in which a snapshot of the population is taken at one time
    • A case report, in which the history of a single patient is described in detail
    • A retrospective case-control study, in which past exposures of cases and controls are compared
    • A randomised controlled trial, in which participants are randomly allocated to treatment or control

  3. What is the main advantage of random sampling when selecting participants for a health study?

    • It reduces selection bias, so the sample is more likely to represent the population
    • It guarantees that the results are always exactly the same as in the whole population
    • It removes the need to measure any variables, because the groups are equal by chance
    • It ensures that all participants have the same disease, which makes the study easier to analyse

  4. Why does a larger sample size generally improve a study?

    • It reduces the effect of chance variation, giving more precise and reliable estimates
    • It ensures that the sample is always representative of the whole population of interest
    • It removes all confounding variables, so the result is free from any alternative explanation
    • It makes the study cheaper to run, because fewer measurements are needed per participant

  5. What is the difference between validity and reliability in a study?

    • Validity means the sample is large, and reliability means the sample is randomly chosen
    • Validity means measuring what is intended; reliability means results are consistent when repeated
    • Validity means results are consistent when repeated; reliability means measuring what is intended
    • Validity and reliability are the same, and both describe the size of the sample used in a study

  6. What is the purpose of a control group in a study of a health risk?

    • It ensures that all participants are exposed to the risk factor at the same level for the study
    • It is used only to measure the age of participants, which is needed for age-standardised rates
    • It provides a comparison, so the effect of the factor being studied can be judged against a baseline
    • It replaces the need for random sampling, because the control group represents the population

  7. Why are participants in a clinical trial often not told whether they receive the active treatment or a placebo?

    • To make the trial cheaper, because the placebo can be given without a record being kept
    • To ensure that the drug has no side effects, because participants who know they are treated report fewer
    • To reduce bias caused by participants' expectations and so keep the comparison fair
    • To remove the need for a control group, because blinded participants all respond in the same way

  8. What is selection bias in a study?

    • The tendency of researchers to select only the results that support their hypothesis for publication
    • The effect of a variable that was deliberately kept constant as a control in the investigation
    • Random error in measurements that occurs because the instrument used has been calibrated incorrectly
    • Systematic differences between the groups being compared because of how participants were chosen

  9. A study of 50 people finds an association between a food and heart disease. Which is the most important limitation to consider?

    • The study must have measured the correct variables, because all studies with fifty participants are reliable
    • The sample is small, so chance may account for the result and the findings may not generalise
    • The study cannot be valid because only fifty people were involved, which means it has no value
    • The result proves causation, because the sample size is large enough to remove all confounding

  10. In a case-control study comparing smokers with and without lung cancer, what is the main risk of bias?

    • Measurement bias, because the equipment used to measure smoking was not calibrated
    • Random sampling bias, because cases are always chosen randomly from the population
    • Placebo bias, because case participants are given a placebo instead of the risk factor
    • Recall bias, because people with the disease may remember past exposures differently from controls

  11. Why is a study that follows participants over many years at risk of attrition bias?

    • Researchers always change their methods during the study, which makes the data impossible to analyse
    • Participants become more likely to develop the disease simply because time has passed
    • Participants may drop out, and those who leave may differ systematically from those who stay
    • The results become invalid because the participants cannot remember their earlier exposures

  12. Which of these is the best way to control for a known confounding variable in an observational study?

    • Match the groups on the confounder, or adjust the results statistically for its effect
    • Ignore the confounder, because observational studies cannot be affected by any other variable
    • Remove all participants who have the confounder from the study without recording them
    • Assume the confounder has no effect, because it is only a correlation and not a cause

  13. A researcher finds that people who drink more coffee have a lower rate of disease. Which study design would best help to establish whether coffee causes the lower rate?

    • A randomised controlled trial in which people are randomly allocated to drink coffee or not
    • A cross-sectional survey asking people about their current coffee consumption and disease
    • A newspaper survey of readers who report their coffee habits without any follow-up
    • A single case study describing one person who drinks a large amount of coffee each day

  14. What does it mean if a study's result is described as statistically significant?

    • The sample size was larger than the number of variables, so the data are perfectly accurate
    • The result proves that the factor being studied causes the outcome in every participant
    • The result is important for public health, regardless of how large the observed effect is
    • The result is unlikely to have occurred by chance alone, given the chosen significance level

  15. Why is it important that a study is replicated by independent researchers?

    • Replication is needed only because the first study was invalid, so the second study is the real result
    • Replication removes the need for any control group, because the second study is always a control
    • Replication tests whether the findings hold up, which strengthens confidence in the conclusions
    • Replication makes the original results more accurate by averaging the original and new data

  16. A study reports that a treatment reduced the risk of CVD by 50% in a sample of 20 people. Which is the most appropriate evaluation?

    • The result is not useful at all, because a sample of 20 people can never give any information
    • The result is proof of causation, because the effect is large and the study was carried out carefully
    • The sample is too small to support a firm conclusion, so the result needs confirmation in larger studies
    • The result is valid and reliable, because a 50% reduction is a very large effect on any sample size

  17. Which statement describes a key feature of a double-blind trial?

    • Participants are told which treatment they receive, but researchers do not know the allocation
    • Researchers and the statistical analysts each know the allocation, but participants are kept unaware
    • Both the sample and the controls are chosen by a double process of random selection and matching
    • Neither the participants nor the researchers assessing outcomes know who receives the active treatment

  18. Which of these is a limitation of relying on an observational cohort study alone to establish a cause of disease?

    • Confounding factors may differ between groups, and the study cannot control allocation to exposure
    • Cohort studies must always use very small samples, which means their results cannot be replicated
    • Cohort studies cannot measure disease rates, because they follow people without any outcome
    • Cohort studies always show that exposure has no effect, because participants are not randomised

  19. A study of 1000 people reports that the number of people who develop disease is 12 in the exposed group and 4 in the unexposed group. The authors do not report the age of participants. Which evaluation is most appropriate?

    • The study cannot be evaluated, because the absence of age data means the result has no statistical meaning
    • The age distribution of the groups should be checked, because age could confound the apparent effect
    • The result shows the exposure causes the disease, because the exposed group has three times more cases
    • The result is valid, because the number of people in each group is fixed and so the age is irrelevant

  20. Why does a study that uses a self-selected volunteer sample have limited generalisability?

    • Volunteers always have the disease being studied, so the results cannot be applied to healthy people
    • Volunteers may differ systematically from the wider population in health behaviours or motivation
    • Volunteer samples are always too large to analyse, so the results cannot be used in public health
    • Volunteers are always randomly allocated, which means the sample cannot be used to infer anything

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