Longitudinal vs cross-sectional approaches US Medical PG Practice Questions and MCQs
Practice US Medical PG questions for Longitudinal vs cross-sectional approaches. These multiple choice questions (MCQs) cover important concepts and help you prepare for your exams.
Longitudinal vs cross-sectional approaches US Medical PG Question 1: A study is funded by the tobacco industry to examine the association between smoking and lung cancer. They design a study with a prospective cohort of 1,000 smokers between the ages of 20-30. The length of the study is five years. After the study period ends, they conclude that there is no relationship between smoking and lung cancer. Which of the following study features is the most likely reason for the failure of the study to note an association between tobacco use and cancer?
- A. Late-look bias
- B. Latency period (Correct Answer)
- C. Confounding
- D. Effect modification
- E. Pygmalion effect
Longitudinal vs cross-sectional approaches Explanation: ***Latency period***
- **Lung cancer** typically has a **long latency period**, often **20-30+ years**, between initial exposure to tobacco carcinogens and the development of clinically detectable disease.
- A **five-year study duration** in young smokers (ages 20-30) is **far too short** to observe the development of lung cancer, which explains the false negative finding.
- This represents a **fundamental flaw in study design** rather than a bias—the biological timeline of disease development was not adequately considered.
*Late-look bias*
- **Late-look bias** occurs when a study enrolls participants who have already survived the early high-risk period of a disease, leading to **underestimation of true mortality or incidence**.
- Also called **survival bias**, it involves studying a population that has already been "selected" by survival.
- This is not applicable here, as the study simply ended before sufficient time elapsed for disease to develop.
*Confounding*
- **Confounding** occurs when a third variable is associated with both the exposure and outcome, distorting the apparent relationship between them.
- While confounding can affect study results, it would not completely eliminate the detection of a strong, well-established association like smoking and lung cancer in a properly conducted prospective cohort study.
- The issue here is temporal (insufficient follow-up time), not the presence of an unmeasured confounder.
*Effect modification*
- **Effect modification** (also called interaction) occurs when the magnitude of an association between exposure and outcome differs across levels of a third variable.
- This represents a **true biological phenomenon**, not a study design flaw or bias.
- It would not explain the complete failure to detect any association.
*Pygmalion effect*
- The **Pygmalion effect** (observer-expectancy effect) refers to a psychological phenomenon where higher expectations lead to improved performance in the observed subjects.
- This concept is relevant to **behavioral and educational research**, not to objective epidemiological studies of disease incidence.
- It has no relevance to the biological relationship between carcinogen exposure and cancer development.
Longitudinal vs cross-sectional approaches US Medical PG Question 2: Researchers are studying the effects of a new medication for the treatment of type 2 diabetes. A randomized group of 100 subjects is given the new medication 1st for 2 months, followed by a washout period of 2 weeks, and then administration of the gold standard medication for 2 months. Another randomized group of 100 subjects is given the gold standard medication 1st for 2 months, followed by a washout period of 2 weeks, and then administration of the new medication for 2 months. What is the main disadvantage of this study design?
- A. Hawthorne effect
- B. Increasing selection bias
- C. Increasing confounding bias
- D. Decreasing power
- E. Carryover effect (Correct Answer)
Longitudinal vs cross-sectional approaches Explanation: ***Carryover effect***
- The primary disadvantage here is the **carryover effect**, where the effects of the first treatment (new medication or gold standard) may persist into the period when the second treatment is administered, even after a washout period.
- This can **mask or alter the true effect** of the second treatment, making it difficult to accurately assess their individual efficacy.
*Hawthorne effect*
- The **Hawthorne effect** refers to subjects improving their behavior or performance in response to being observed or studied, not specifically an issue with sequential treatment administration.
- It would affect both groups equally and doesn't explain a disadvantage inherent to the crossover design itself.
*Increasing selection bias*
- **Selection bias** occurs when the randomization process fails to create comparable groups, but this study design involves **randomization** into two groups, and then a crossover, which typically aims to *reduce* selection bias by having each participant serve as their own control.
- The sequential administration within a randomized crossover design actually helps to mitigate selection bias between treatment arms.
*Increasing confounding bias*
- **Confounding bias** occurs when an unmeasured variable is associated with both the exposure and the outcome, distorting the observed relationship.
- This crossover design, where each participant receives both treatments, is intended to *reduce* confounding by inter-individual variability, as each subject acts as their own control, rather than increasing it.
*Decreasing power*
- **Power** is the ability of a study to detect a true effect if one exists. Crossover designs often *increase* statistical power compared to parallel designs because each participant receives both treatments, reducing inter-individual variability.
- This design typically requires a smaller sample size to achieve the same power as a parallel group study, so decreased power is not a disadvantage.
Longitudinal vs cross-sectional approaches US Medical PG Question 3: An 8-year-old boy is brought to the physician by his mother for a well-child examination at a clinic for low-income residents. Although her son's elementary school offers free afterschool programming, her son has not been interested in attending. Both the son's maternal and paternal grandmothers have major depressive disorder. The mother is curious about the benefits of afterschool programming and asks for the physician's input. Which of the following statements best addresses the potential benefits of afterschool programming for this child?
- A. High-quality afterschool programming would decrease this patient's risk of developing major depressive disorder.
- B. High-quality afterschool programming for low-income 8-year-olds may correlate with decreased ADHD risk in adults. (Correct Answer)
- C. High-quality afterschool programming has a greater effect on reducing psychotic disorder risk in adults than bipolar disorder risk.
- D. High-quality afterschool programming has a greater effect on reducing ADHD risk in adults than major depressive disorder risk.
- E. The patient's family history of psychiatric illness prevents any potential benefits from afterschool programming.
Longitudinal vs cross-sectional approaches Explanation: ***High-quality afterschool programming for low-income 8-year-olds may correlate with decreased ADHD risk in adults.***
- Research, including systematic reviews and longitudinal studies, indicates that structured, high-quality afterschool programs can lead to improved behavioral outcomes and reduced risk of **ADHD symptoms** persisting into adulthood, especially in **vulnerable populations** such as low-income children.
- These programs foster **social-emotional skills**, provide academic support, and promote healthy development, indirectly mitigating factors associated with ADHD through improved executive function and self-regulation.
*High-quality afterschool programming would decrease this patient's risk of developing major depressive disorder.*
- While afterschool programs provide mental health benefits through **social support** and structured activities, the direct reduction in risk of **major depressive disorder** is less consistently demonstrated compared to behavioral outcomes.
- Given the strong **family history** (both grandmothers affected), genetic factors play a significant role that afterschool programming alone cannot fully mitigate.
*The patient's family history of psychiatric illness prevents any potential benefits from afterschool programming.*
- Family history is a **risk factor** but does not negate the benefits of **preventive interventions** like afterschool programs.
- Evidence-based programs can still provide protective effects on mental health and behavioral outcomes, even in children with genetic vulnerabilities.
*High-quality afterschool programming has a greater effect on reducing psychotic disorder risk in adults than bipolar disorder risk.*
- There is **insufficient evidence** to support significant impacts of childhood afterschool programming specifically on reducing the risk of **psychotic disorders** or **bipolar disorder** in adulthood.
- These conditions have strong genetic and neurobiological components that are not primarily addressed by afterschool interventions.
*High-quality afterschool programming has a greater effect on reducing ADHD risk in adults than major depressive disorder risk.*
- While this comparison has some support in the literature, the **correct answer** is more appropriately hedged and specific to the patient population (low-income 8-year-olds).
- Both conditions can benefit from afterschool programming, but the evidence for **behavioral regulation** and ADHD symptom reduction is more robust and consistent.
Longitudinal vs cross-sectional approaches US Medical PG Question 4: An otherwise healthy 67-year-old woman comes to your clinic after being admitted to the hospital for 2 weeks after breaking her hip. She has not regularly seen a physician for the past several years because she has been working hard at her long-time job as a schoolteacher. You wonder if she has not been taking adequate preventative measures to prevent osteoporosis and order the appropriate labs. Although she is recovering from surgery well, she is visibly upset because she is worried that her hospital bill will bankrupt her. Which of the following best describes her Medicare coverage?
- A. Medicare Part C will cover the majority of drug costs during her inpatient treatment.
- B. Medicare Part A will cover the majority of her hospital fees, including inpatient drugs and lab tests. (Correct Answer)
- C. Medicare is unlikely to cover the cost of her admission because she has not been paying her premium.
- D. Medicare Part B will cover the majority of her hospital fees, including inpatient drugs and lab tests.
- E. Medicare Part D will cover the cost of drugs during her inpatient treatment.
Longitudinal vs cross-sectional approaches Explanation: ***Medicare Part A will cover the majority of her hospital fees, including inpatient drugs and lab tests.***
* **Medicare Part A** is hospital insurance and covers **inpatient hospital stays**, skilled nursing facility care, hospice care, and some home health care. This includes services received during an inpatient stay such as drugs, lab tests, and surgery.
* Given her 2-week hospital stay for a broken hip, which resulted in surgery and ongoing recovery, Part A would be the primary payer for the majority of these costs.
*Medicare Part C will cover the majority of drug costs during her inpatient treatment.*
* **Medicare Part C**, also known as **Medicare Advantage**, is an alternative to original Medicare provided by private companies, often including Part A, B, and D benefits.
* While Part C plans can cover drug costs, **inpatient drugs** administered during a hospital stay are typically covered under **Part A**, not a separate drug plan, if the patient is using original Medicare. If she has a Part C plan, it would integrate these benefits.
*Medicare is unlikely to cover the cost of her admission because she has not been paying her premium.*
* Medicare Part A is generally **premium-free** for most individuals who have paid Medicare taxes through their employment for at least 10 years (or 40 quarters).
* Given her long career as a schoolteacher, it is highly likely she would qualify for premium-free Part A, making this statement incorrect.
*Medicare Part B will cover the majority of her hospital fees, including inpatient drugs and lab tests.*
* **Medicare Part B** is medical insurance and covers **doctor's services**, outpatient care, medical supplies, and preventive services.
* While it covers some outpatient lab tests and physician services received during an inpatient stay, it does not cover the primary costs of **inpatient hospital fees** or drugs administered during an inpatient stay, which fall under Part A.
*Medicare Part D will cover the cost of drugs during her inpatient treatment.*
* **Medicare Part D** is prescription drug coverage provided by private companies and covers **outpatient prescription drugs**.
* Medications administered to an **inpatient** during a hospital stay (i.e., when she is admitted) are typically covered under **Medicare Part A**, not Part D.
Longitudinal vs cross-sectional approaches US Medical PG Question 5: A research group wants to assess the safety and toxicity profile of a new drug. A clinical trial is conducted with 20 volunteers to estimate the maximum tolerated dose and monitor the apparent toxicity of the drug. The study design is best described as which of the following phases of a clinical trial?
- A. Phase 0
- B. Phase III
- C. Phase V
- D. Phase II
- E. Phase I (Correct Answer)
Longitudinal vs cross-sectional approaches Explanation: ***Phase I***
- **Phase I clinical trials** involve a small group of healthy volunteers (typically 20-100) to primarily assess **drug safety**, determine a safe dosage range, and identify side effects.
- The main goal is to establish the **maximum tolerated dose (MTD)** and evaluate the drug's pharmacokinetic and pharmacodynamic profiles.
*Phase 0*
- **Phase 0 trials** are exploratory studies conducted in a very small number of subjects (10-15) to gather preliminary data on a drug's **pharmacodynamics and pharmacokinetics** in humans.
- They involve microdoses, not intended to have therapeutic effects, and thus cannot determine toxicity or MTD.
*Phase III*
- **Phase III trials** are large-scale studies involving hundreds to thousands of patients to confirm the drug's **efficacy**, monitor side effects, compare it to standard treatments, and collect information that will allow the drug to be used safely.
- These trials are conducted after safety and initial efficacy have been established in earlier phases.
*Phase V*
- "Phase V" is not a standard, recognized phase in the traditional clinical trial classification (Phase 0, I, II, III, IV).
- This term might be used in some non-standard research contexts or for post-marketing studies that go beyond Phase IV surveillance, but it is not a formal phase for initial drug development.
*Phase II*
- **Phase II trials** involve several hundred patients with the condition the drug is intended to treat, focusing on **drug efficacy** and further evaluating safety.
- While safety is still monitored, the primary objective shifts to determining if the drug works for its intended purpose and at what dose.
Longitudinal vs cross-sectional approaches US Medical PG Question 6: Study X examined the relationship between coffee consumption and lung cancer. The authors of Study X retrospectively reviewed patients' reported coffee consumption and found that drinking greater than 6 cups of coffee per day was associated with an increased risk of developing lung cancer. However, Study X was criticized by the authors of Study Y. Study Y showed that increased coffee consumption was associated with smoking. What type of bias affected Study X, and what study design is geared to reduce the chance of that bias?
- A. Observer bias; double blind analysis
- B. Selection bias; randomization
- C. Lead time bias; placebo
- D. Measurement bias; blinding
- E. Confounding; randomization (Correct Answer)
Longitudinal vs cross-sectional approaches Explanation: ***Confounding; randomization***
- Study Y suggests that **smoking** is a **confounding variable** because it is associated with both increased coffee consumption (exposure) and increased risk of lung cancer (outcome), distorting the apparent relationship between coffee and lung cancer.
- **Randomization** in experimental studies (such as randomized controlled trials) helps reduce confounding by ensuring that known and unknown confounding factors are evenly distributed among study groups.
- In observational studies where randomization is not possible, confounding can be addressed through **stratification**, **matching**, or **multivariable adjustment** during analysis.
*Observer bias; double blind analysis*
- **Observer bias** occurs when researchers' beliefs or expectations influence the study outcome, which is not the primary issue described here regarding the relationship between coffee, smoking, and lung cancer.
- **Double-blind analysis** is a method to mitigate observer bias by ensuring neither participants nor researchers know who is in the control or experimental groups.
*Selection bias; randomization*
- **Selection bias** happens when the study population is not representative of the target population, leading to inaccurate results, which is not directly indicated by the interaction between coffee and smoking.
- While **randomization** is used to reduce selection bias by creating comparable groups, the core problem identified in Study X is confounding, not flawed participant selection.
*Lead time bias; placebo*
- **Lead time bias** occurs in screening programs when early detection without improved outcomes makes survival appear longer, an issue unrelated to the described association between coffee, smoking, and lung cancer.
- A **placebo** is an inactive treatment used in clinical trials to control for psychological effects, and its relevance here is limited to treatment intervention studies.
*Measurement bias; blinding*
- **Measurement bias** arises from systematic errors in data collection, such as inaccurate patient reporting of coffee consumption, but the main criticism from Study Y points to a third variable (smoking) affecting the association, not just flawed measurement.
- **Blinding** helps reduce measurement bias by preventing participants or researchers from knowing group assignments, thus minimizing conscious or unconscious influences on data collection.
Longitudinal vs cross-sectional approaches US Medical PG Question 7: A scientist is designing a study to determine whether eating a new diet is able to lower blood pressure in a group of patients. In particular, he believes that starting the diet may help decrease peak blood pressures throughout the day. Therefore, he will equip study participants with blood pressure monitors and follow pressure trends over a 24-hour period. He decides that after recruiting subjects, he will start them on either the new diet or a control diet and follow them for 1 month. After this time, he will switch patients onto the other diet and follow them for an additional month. He will analyze the results from the first month against the results from the second month for each patient. This type of study design is best at controlling for which of the following problems with studies?
- A. Hawthorne effect
- B. Recall bias
- C. Confounding (Correct Answer)
- D. Selection bias
- E. Pygmalion effect
Longitudinal vs cross-sectional approaches Explanation: ***Confounding***
- This **crossover design** (switching patients to the other diet) effectively controls for **confounding variables** by making each patient their own control, ensuring that inherent patient characteristics do not bias the comparison between diets.
- By comparing the effects of both diets within the same individual, individual variability in factors such as genetics, lifestyle, and other co-morbidities are accounted for, reducing their potential as confounders.
*Hawthorne effect*
- The **Hawthorne effect** refers to subjects modifying their behavior in response to being observed, which this study design does not specifically address or eliminate.
- While patients are being monitored, the design aims to compare the diets' effects, not to prevent behavioral changes due to observation itself.
*Recall bias*
- **Recall bias** occurs when participants' memories of past events are inaccurate, often influenced by their current health status or beliefs.
- This study measures **real-time blood pressure** data, not relying on recollection of past exposures or outcomes, thereby mitigating recall bias.
*Selection bias*
- **Selection bias** arises from non-random selection of participants into study groups, leading to systematic differences between groups.
- While patient recruitment could introduce selection bias into the overall study population, the **crossover design** itself helps control for differences between treatment arms because all participants eventually receive both treatments.
*Pygmalion effect*
- The **Pygmalion effect** (or observer-expectancy effect) describes phenomena where higher expectations lead to increased performance, usually from a researcher influencing a subject.
- This effect is not directly addressed by the crossover design; the design focuses on controlling for patient-specific confounders rather than investigator bias in expectations.
Longitudinal vs cross-sectional approaches US Medical PG Question 8: A population is studied for risk factors associated with testicular cancer. Alcohol exposure, smoking, dietary factors, social support, and environmental exposure are all assessed. The researchers are interested in the incidence and prevalence of the disease in addition to other outcomes. Which pair of studies would best assess the 1. incidence and 2. prevalence?
- A. 1. Prospective cohort study 2. Cross sectional study (Correct Answer)
- B. 1. Prospective cohort study 2. Retrospective cohort study
- C. 1. Cross sectional study 2. Retrospective cohort study
- D. 1. Case-control study 2. Prospective cohort study
- E. 1. Clinical trial 2. Cross sectional study
Longitudinal vs cross-sectional approaches Explanation: ***1. Prospective cohort study 2. Cross sectional study***
- A **prospective cohort study** is ideal for measuring **incidence** (new cases over time) because it follows a group of individuals forward in time to observe who develops the disease.
- A **cross-sectional study** is suitable for measuring **prevalence** (existing cases at a specific point in time) as it surveys a population at one moment to determine the proportion with the disease.
*1. Prospective cohort study 2. Retrospective cohort study*
- A **retrospective cohort study** assesses past exposures and outcomes and can measure incidence, but it is not the primary choice for prevalence.
- While a prospective cohort study is appropriate for incidence, a retrospective cohort study is less suited for determining current prevalence.
*1. Cross sectional study 2. Retrospective cohort study*
- A **cross-sectional study** measures prevalence, not incidence, as it captures disease status at a single point in time.
- A **retrospective cohort study** looks back in time to identify past exposures and subsequent outcomes, which is not the best method for current prevalence.
*1. Case-control study 2. Prospective cohort study*
- A **case-control study** compares exposures between individuals with a disease (cases) and those without (controls) and is best for studying rare diseases and estimating odds ratios, not incidence or prevalence directly.
- A **prospective cohort study** is suitable for incidence, but a case-control study is not for incidence or prevalence.
*1. Clinical trial 2. Cross sectional study*
- A **clinical trial** is an experimental study designed to test the efficacy of interventions and is not primarily used to measure disease incidence or prevalence in a general population.
- While a cross-sectional study is appropriate for prevalence, a clinical trial is not designed for incidence measurement.
Longitudinal vs cross-sectional approaches US Medical PG Question 9: A statistician wants to study the effects of a medicine in three groups-humans, animals, and plants. He then selects randomly from these three groups. Which type of sampling is being performed?
- A. Simple random sampling
- B. Systematic sampling
- C. Stratified random sampling (Correct Answer)
- D. Cluster sampling
- E. Convenience sampling
Longitudinal vs cross-sectional approaches Explanation: ***Stratified random sampling***
- This method involves dividing the population into **distinct subgroups (strata)** based on shared characteristics (in this case, humans, animals, and plants), and then performing a simple random sample within each stratum.
- This ensures that all subgroups are proportionally represented in the sample, which is appropriate when studying effects across different biological categories.
*Simple random sampling*
- This method involves selecting individuals from the entire population **purely by chance**, without first dividing them into subgroups.
- It would not guarantee representation from all three distinct groups (humans, animals, and plants), which is essential for studying differential effects.
*Systematic sampling*
- This involves selecting samples at **regular intervals** from an ordered list or sequence.
- This method is not suitable here because the population is divided into distinct, non-ordered groups rather than a continuous sequence.
*Cluster sampling*
- This method involves dividing the population into **clusters**, then randomly selecting some clusters and sampling all individuals within those selected clusters.
- In this scenario, the initial groups (humans, animals, plants) are strata, not clusters, as the intent is to sample from within each group, not to treat the groups themselves as primary sampling units.
*Convenience sampling*
- This is a **non-probability sampling method** where subjects are selected based on ease of access rather than random selection.
- The question explicitly states that random selection is performed from each group, ruling out convenience sampling.
Longitudinal vs cross-sectional approaches US Medical PG Question 10: A study was undertaken to establish the relationship between the consumption of a vegetarian or non-vegetarian diet and the presence of diseases. Which statistical test should be used?
- A. Chi-square test (Correct Answer)
- B. T-test
- C. ANOVA
- D. Fisher's exact test
- E. Mann-Whitney U test
Longitudinal vs cross-sectional approaches Explanation: ***Chi-square test***
- The **chi-square test** is appropriate when analyzing the relationship between two **categorical variables**. In this scenario, "diet type" (vegetarian/non-vegetarian) and "presence of disease" (yes/no) are both categorical variables.
- This test determines if there is a statistically significant association between the frequency counts of these two variables in a contingency table.
*T-test*
- A **t-test** is used to compare the **means** of two groups, typically when the dependent variable is continuous.
- This test is unsuitable here because the presence of disease and diet type are categorical, not continuous, variables.
*ANOVA*
- **ANOVA** (Analysis of Variance) is used to compare the **means** of three or more groups, often with a continuous dependent variable.
- Similar to the t-test, ANOVA is not applicable as the study involves categorical variables, not the comparison of means across multiple groups.
*Fisher's exact test*
- **Fisher's exact test** is similar to the chi-square test but specifically used for **small sample sizes** where the expected frequencies in any cell of the contingency table are less than 5.
- While it analyzes categorical data, the chi-square test is the more general and commonly preferred test for larger sample sizes, which is generally assumed unless otherwise specified.
*Mann-Whitney U test*
- The **Mann-Whitney U test** is a non-parametric test used to compare differences between two independent groups when the dependent variable is **ordinal or continuous** but not normally distributed.
- This test is not appropriate for analyzing the association between two categorical variables, as it requires at least one variable to have ranked or continuous data.
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