, CHAPTER LIST
Chapter 1: Introduction
Chapter 2: Frequency
Chapter 3: Abnormality
Chapter 4: Diagnosis
Chapter 5: Risk: Basic Principles
Chapter 6: Risk: Exposure to Disease
Chapter 7: Risk: From Disease to Exposure
Chapter 8: Prognosis
Chapter 9: Treatment
Chapter 10: Prevention
Chapter 11: Chance
Chapter 12: Cause
Chapter 13: Summarizing the Evidence
Chapter 14: Knowledge Management
,Chapter 1: Introduction
Q1. A clinician wants to determine the most common type of infection in
hospitalized patients over a year. Which epidemiologic approach is most
appropriate?
A) Case-control study
B) Cohort study
C) Descriptive epidemiology
D) Randomized controlled trial
Answer: C
Rationale: Descriptive epidemiology summarizes disease patterns (frequency,
distribution) without testing causal hypotheses, which is appropriate for
identifying common infections in a population.
Key words: descriptive epidemiology, disease patterns, frequency, population
study
Q2. Which of the following best reflects the primary goal of clinical
epidemiology?
A) To develop new diagnostic laboratory tests
B) To understand disease patterns and improve clinical decision-making
C) To provide individualized treatment for rare diseases
D) To focus exclusively on laboratory research
Answer: B
Rationale: Clinical epidemiology integrates epidemiologic principles into
patient care, guiding clinical decisions and improving outcomes, rather than
focusing only on lab research or rare diseases.
Key words: clinical decision-making, disease patterns, patient outcomes
Q3. A study examines the effect of a new antihypertensive drug on blood
pressure reduction. Which epidemiologic principle ensures the findings are
applicable to broader patient populations?
A) Validity
B) Confounding
C) Selection bias
D) Random error
,Answer: A
Rationale: Validity ensures that study findings accurately reflect true effects
and can be generalized to the target population, which is essential in clinical
epidemiology.
Key words: validity, generalizability, clinical research
Q4. In evaluating a study on risk factors for diabetes, a clinician notes that
only patients with severe disease were included. This is an example of:
A) Confounding
B) Selection bias
C) Measurement bias
D) Randomization
Answer: B
Rationale: Selection bias occurs when the study population is not
representative of the target population, potentially distorting associations
between exposure and outcome.
Key words: selection bias, representativeness, study population
Q5. A researcher interprets a p-value of 0.03 in a clinical trial. What is the
correct interpretation?
A) The null hypothesis is definitely false
B) There is a 3% probability that the observed effect is due to chance
C) The probability that the null hypothesis is true is 3%
D) The intervention effect is clinically significant
Answer: B
Rationale: A p-value represents the probability of obtaining the observed data
(or more extreme) if the null hypothesis were true; it does not indicate the
probability that the null hypothesis itself is true.
Key words: p-value, chance, statistical inference, null hypothesis
Q6. A 45-year-old patient asks about the risk of developing heart disease based
on family history. Which concept is most relevant?
A) Incidence
B) Prevalence
C) Absolute risk
D) Odds ratio
,Answer: C
Rationale: Absolute risk quantifies the probability of an event occurring in a
specific population, which directly informs individual patient counseling.
Key words: absolute risk, patient counseling, probability
Q7. A study comparing two treatments reports relative risk = 0.7. Which
statement is correct?
A) The risk is increased by 70%
B) The risk is decreased by 30%
C) The treatment has no effect
D) The risk difference cannot be determined
Answer: B
Rationale: A relative risk <1 indicates a decreased risk; specifically, 1 – 0.7 =
0.3, or 30% reduction in risk.
Key words: relative risk, treatment effect, epidemiologic measure
Q8. A clinician is reading a study that uses patient records over 5 years to
describe the occurrence of stroke. What type of study is this?
A) Prospective cohort study
B) Retrospective cohort study
C) Cross-sectional study
D) Randomized controlled trial
Answer: B
Rationale: Retrospective cohort studies use existing records to follow
exposures and outcomes over time, enabling calculation of incidence and risk
without prospective data collection.
Key words: retrospective study, cohort, incidence, medical records
Q9. A patient-centered decision requires integrating best research evidence
with clinical expertise and patient values. This principle is known as:
A) Evidence-based medicine
B) Biostatistics
C) Clinical trial methodology
D) Epidemiologic surveillance
Answer: A
Rationale: Evidence-based medicine combines high-quality research, clinical
judgment, and patient preferences to optimize care decisions.
,Key words: evidence-based medicine, clinical decision-making, patient-
centered
Q10. A study finds an association between coffee intake and heart disease, but
the effect disappears after adjusting for smoking. This illustrates:
A) Random error
B) Confounding
C) Selection bias
D) Reverse causation
Answer: B
Rationale: Confounding occurs when an extraneous factor (smoking) distorts
the observed relationship between exposure (coffee) and outcome (heart
disease).
Key words: confounding, adjustment, risk factors
Q11. Which of the following statements best describes the role of probability in
clinical epidemiology?
A) It eliminates uncertainty in patient outcomes
B) It quantifies the likelihood of disease or outcomes
C) It guarantees causation
D) It replaces clinical judgment
Answer: B
Rationale: Probability is used to quantify uncertainty, helping clinicians
estimate risk and make informed decisions, but it does not eliminate
uncertainty or guarantee causation.
Key words: probability, uncertainty, risk estimation
Q12. A hospital wants to track the number of new cases of pneumonia per
month. Which measure should they use?
A) Prevalence
B) Incidence rate
C) Mortality rate
D) Case-fatality rate
Answer: B
Rationale: Incidence rate measures the frequency of new cases in a defined
population over a specified period, which is appropriate for monitoring trends.
Key words: incidence, new cases, disease frequency
, Q13. During an outbreak, public health officials calculate that 15% of exposed
individuals develop symptoms. This is an example of:
A) Relative risk
B) Attributable risk
C) Attack rate
D) Odds ratio
Answer: C
Rationale: Attack rate is the proportion of people who become ill after
exposure during a defined period, commonly used in outbreak investigations.
Key words: attack rate, outbreak, disease frequency
Q14. A clinician reading a study notes wide confidence intervals around an
effect estimate. This most likely reflects:
A) High precision
B) Low precision
C) Lack of bias
D) Randomization
Answer: B
Rationale: Wide confidence intervals indicate low precision in estimating the
true effect, often due to small sample size or high variability.
Key words: confidence interval, precision, variability
Q15. A study concludes that a new vaccine reduces infection risk but the
authors note that results could be due to chance. Which principle are they
acknowledging?
A) Validity
B) Random error
C) Bias
D) Confounding
Answer: B
Rationale: Random error refers to variation in results due to chance, which
can be quantified statistically (e.g., p-values, confidence intervals).
Key words: random error, chance, statistical inference
Chapter 1: Introduction
Chapter 2: Frequency
Chapter 3: Abnormality
Chapter 4: Diagnosis
Chapter 5: Risk: Basic Principles
Chapter 6: Risk: Exposure to Disease
Chapter 7: Risk: From Disease to Exposure
Chapter 8: Prognosis
Chapter 9: Treatment
Chapter 10: Prevention
Chapter 11: Chance
Chapter 12: Cause
Chapter 13: Summarizing the Evidence
Chapter 14: Knowledge Management
,Chapter 1: Introduction
Q1. A clinician wants to determine the most common type of infection in
hospitalized patients over a year. Which epidemiologic approach is most
appropriate?
A) Case-control study
B) Cohort study
C) Descriptive epidemiology
D) Randomized controlled trial
Answer: C
Rationale: Descriptive epidemiology summarizes disease patterns (frequency,
distribution) without testing causal hypotheses, which is appropriate for
identifying common infections in a population.
Key words: descriptive epidemiology, disease patterns, frequency, population
study
Q2. Which of the following best reflects the primary goal of clinical
epidemiology?
A) To develop new diagnostic laboratory tests
B) To understand disease patterns and improve clinical decision-making
C) To provide individualized treatment for rare diseases
D) To focus exclusively on laboratory research
Answer: B
Rationale: Clinical epidemiology integrates epidemiologic principles into
patient care, guiding clinical decisions and improving outcomes, rather than
focusing only on lab research or rare diseases.
Key words: clinical decision-making, disease patterns, patient outcomes
Q3. A study examines the effect of a new antihypertensive drug on blood
pressure reduction. Which epidemiologic principle ensures the findings are
applicable to broader patient populations?
A) Validity
B) Confounding
C) Selection bias
D) Random error
,Answer: A
Rationale: Validity ensures that study findings accurately reflect true effects
and can be generalized to the target population, which is essential in clinical
epidemiology.
Key words: validity, generalizability, clinical research
Q4. In evaluating a study on risk factors for diabetes, a clinician notes that
only patients with severe disease were included. This is an example of:
A) Confounding
B) Selection bias
C) Measurement bias
D) Randomization
Answer: B
Rationale: Selection bias occurs when the study population is not
representative of the target population, potentially distorting associations
between exposure and outcome.
Key words: selection bias, representativeness, study population
Q5. A researcher interprets a p-value of 0.03 in a clinical trial. What is the
correct interpretation?
A) The null hypothesis is definitely false
B) There is a 3% probability that the observed effect is due to chance
C) The probability that the null hypothesis is true is 3%
D) The intervention effect is clinically significant
Answer: B
Rationale: A p-value represents the probability of obtaining the observed data
(or more extreme) if the null hypothesis were true; it does not indicate the
probability that the null hypothesis itself is true.
Key words: p-value, chance, statistical inference, null hypothesis
Q6. A 45-year-old patient asks about the risk of developing heart disease based
on family history. Which concept is most relevant?
A) Incidence
B) Prevalence
C) Absolute risk
D) Odds ratio
,Answer: C
Rationale: Absolute risk quantifies the probability of an event occurring in a
specific population, which directly informs individual patient counseling.
Key words: absolute risk, patient counseling, probability
Q7. A study comparing two treatments reports relative risk = 0.7. Which
statement is correct?
A) The risk is increased by 70%
B) The risk is decreased by 30%
C) The treatment has no effect
D) The risk difference cannot be determined
Answer: B
Rationale: A relative risk <1 indicates a decreased risk; specifically, 1 – 0.7 =
0.3, or 30% reduction in risk.
Key words: relative risk, treatment effect, epidemiologic measure
Q8. A clinician is reading a study that uses patient records over 5 years to
describe the occurrence of stroke. What type of study is this?
A) Prospective cohort study
B) Retrospective cohort study
C) Cross-sectional study
D) Randomized controlled trial
Answer: B
Rationale: Retrospective cohort studies use existing records to follow
exposures and outcomes over time, enabling calculation of incidence and risk
without prospective data collection.
Key words: retrospective study, cohort, incidence, medical records
Q9. A patient-centered decision requires integrating best research evidence
with clinical expertise and patient values. This principle is known as:
A) Evidence-based medicine
B) Biostatistics
C) Clinical trial methodology
D) Epidemiologic surveillance
Answer: A
Rationale: Evidence-based medicine combines high-quality research, clinical
judgment, and patient preferences to optimize care decisions.
,Key words: evidence-based medicine, clinical decision-making, patient-
centered
Q10. A study finds an association between coffee intake and heart disease, but
the effect disappears after adjusting for smoking. This illustrates:
A) Random error
B) Confounding
C) Selection bias
D) Reverse causation
Answer: B
Rationale: Confounding occurs when an extraneous factor (smoking) distorts
the observed relationship between exposure (coffee) and outcome (heart
disease).
Key words: confounding, adjustment, risk factors
Q11. Which of the following statements best describes the role of probability in
clinical epidemiology?
A) It eliminates uncertainty in patient outcomes
B) It quantifies the likelihood of disease or outcomes
C) It guarantees causation
D) It replaces clinical judgment
Answer: B
Rationale: Probability is used to quantify uncertainty, helping clinicians
estimate risk and make informed decisions, but it does not eliminate
uncertainty or guarantee causation.
Key words: probability, uncertainty, risk estimation
Q12. A hospital wants to track the number of new cases of pneumonia per
month. Which measure should they use?
A) Prevalence
B) Incidence rate
C) Mortality rate
D) Case-fatality rate
Answer: B
Rationale: Incidence rate measures the frequency of new cases in a defined
population over a specified period, which is appropriate for monitoring trends.
Key words: incidence, new cases, disease frequency
, Q13. During an outbreak, public health officials calculate that 15% of exposed
individuals develop symptoms. This is an example of:
A) Relative risk
B) Attributable risk
C) Attack rate
D) Odds ratio
Answer: C
Rationale: Attack rate is the proportion of people who become ill after
exposure during a defined period, commonly used in outbreak investigations.
Key words: attack rate, outbreak, disease frequency
Q14. A clinician reading a study notes wide confidence intervals around an
effect estimate. This most likely reflects:
A) High precision
B) Low precision
C) Lack of bias
D) Randomization
Answer: B
Rationale: Wide confidence intervals indicate low precision in estimating the
true effect, often due to small sample size or high variability.
Key words: confidence interval, precision, variability
Q15. A study concludes that a new vaccine reduces infection risk but the
authors note that results could be due to chance. Which principle are they
acknowledging?
A) Validity
B) Random error
C) Bias
D) Confounding
Answer: B
Rationale: Random error refers to variation in results due to chance, which
can be quantified statistically (e.g., p-values, confidence intervals).
Key words: random error, chance, statistical inference
