Factorial designs US Medical PG Practice Questions and MCQs
Practice US Medical PG questions for Factorial designs. These multiple choice questions (MCQs) cover important concepts and help you prepare for your exams.
Factorial designs US Medical PG Question 1: 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)
Factorial designs 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.
Factorial designs US Medical PG Question 2: A researcher is trying to determine whether a newly discovered substance X can be useful in promoting wound healing after surgery. She conducts this study by enrolling the next 100 patients that will be undergoing this surgery and separating them into 2 groups. She decides which patient will be in which group by using a random number generator. Subsequently, she prepares 1 set of syringes with the novel substance X and 1 set of syringes with a saline control. Both of these sets of syringes are unlabeled and the substances inside cannot be distinguished. She gives the surgeon performing the surgery 1 of the syringes and does not inform him nor the patient which syringe was used. After the study is complete, she analyzes all the data that was collected and performs statistical analysis. This study most likely provides which level of evidence for use of substance X?
- A. Level 3
- B. Level 1 (Correct Answer)
- C. Level 4
- D. Level 5
- E. Level 2
Factorial designs Explanation: ***Level 1***
- The study design described is a **randomized controlled trial (RCT)**, which is considered the **highest level of evidence (Level 1)** in the hierarchy of medical evidence.
- Key features like **randomization**, **control group**, and **blinding (double-blind)** help minimize bias and strengthen the validity of the findings.
*Level 2*
- Level 2 evidence typically comprises **well-designed controlled trials without randomization** (non-randomized controlled trials) or **high-quality cohort studies**.
- While strong, they do not possess the same level of internal validity as randomized controlled trials.
*Level 3*
- Level 3 evidence typically includes **case-control studies** or **cohort studies**, which are observational designs and carry a higher risk of bias compared to RCTs.
- These studies generally do not involve randomization or intervention assignment by the researchers.
*Level 4*
- Level 4 evidence is usually derived from **case series** or **poor quality cohort and case-control studies**.
- These studies provide descriptive information or investigate associations without strong control for confounding factors.
*Level 5*
- Level 5 evidence is the **lowest level of evidence**, consisting of **expert opinion** or **animal research/bench research**.
- This level lacks human clinical data or systematic investigative rigor needed for higher evidence levels.
Factorial designs US Medical PG Question 3: A pharmaceutical company conducts a randomized clinical trial in an attempt to show that their new anticoagulant drug prevents more thrombotic events following total knee arthroplasty than the current standard of care. However, a significant number of patients are lost to follow-up or fail to complete treatment according to the study arm to which they were assigned. Several patients in the novel drug arm are also switched at a later time to a novel anticoagulant or warfarin per their primary care physician. All patients enrolled in the study are subsequently analyzed based on the initial group they were assigned to and there is a significant improvement in outcome of the new drug. What analysis most appropriately describes this trial?
- A. Per protocol
- B. As treated
- C. Non-inferiority
- D. Intention to treat (Correct Answer)
- E. Modified intention to treat
Factorial designs Explanation: ***Intention to treat***
- **Intention-to-treat (ITT)** analysis includes all participants randomized to a treatment arm, regardless of whether they completed the intervention or switched treatments, reflecting a real-world scenario and preserving randomization benefits.
- This approach minimizes bias from **loss to follow-up** or **treatment crossovers** and provides a more conservative estimate of treatment effect.
*Per protocol*
- **Per-protocol analysis** only includes participants who completed the study exactly as planned without any deviations.
- This method is susceptible to **selection bias** because it excludes patients who may have experienced adverse events or treatment failures, potentially overestimating treatment efficacy.
*As treated*
- **As-treated analysis** analyzes patients based on the actual treatment received, rather than the treatment to which they were randomized.
- This approach can introduce **confounding** and selection bias, as patients who switch treatments may do so for reasons related to their prognosis or treatment response.
*Non-inferiority*
- A **non-inferiority trial** design aims to show that a new treatment is not appreciably worse than an active control, rather than proving superiority.
- This describes a **type of study design** or hypothesis, not an analysis method for handling patient data after randomization with non-adherence.
*Modified intention to treat*
- A **modified intention-to-treat (mITT)** analysis typically excludes a small, predefined group of patients from the ITT population, such as those who never received any study drug or were found to be ineligible after randomization.
- While similar to ITT, it involves specific exclusions that are not described in this scenario, where all randomized patients were analyzed **based on initial assignment**.
Factorial designs US Medical PG Question 4: A 28-year-old male presents to his primary care physician with complaints of intermittent abdominal pain and alternating bouts of constipation and diarrhea. His medical chart is not significant for any past medical problems or prior surgeries. He is not prescribed any current medications. Which of the following questions would be the most useful next question in eliciting further history from this patient?
- A. "Does the diarrhea typically precede the constipation, or vice-versa?"
- B. "Is the diarrhea foul-smelling?"
- C. "Please rate your abdominal pain on a scale of 1-10, with 10 being the worst pain of your life"
- D. "Are the symptoms worse in the morning or at night?"
- E. "Can you tell me more about the symptoms you have been experiencing?" (Correct Answer)
Factorial designs Explanation: ***Can you tell me more about the symptoms you have been experiencing?***
- This **open-ended question** encourages the patient to provide a **comprehensive narrative** of their symptoms, including details about onset, frequency, duration, alleviating/aggravating factors, and associated symptoms, which is crucial for diagnosis.
- In a patient presenting with vague, intermittent symptoms like alternating constipation and diarrhea, allowing them to elaborate freely can reveal important clues that might not be captured by more targeted questions.
*Does the diarrhea typically precede the constipation, or vice-versa?*
- While knowing the sequence of symptoms can be helpful in understanding the **pattern of bowel dysfunction**, it is a very specific question that might overlook other important aspects of the patient's experience.
- It prematurely narrows the focus without first obtaining a broad understanding of the patient's overall symptomatic picture.
*Is the diarrhea foul-smelling?*
- Foul-smelling diarrhea can indicate **malabsorption** or **bacterial overgrowth**, which are important to consider in some gastrointestinal conditions.
- However, this is a **specific symptom inquiry** that should follow a more general exploration of the patient's symptoms, as it may not be relevant if other crucial details are missed.
*Please rate your abdominal pain on a scale of 1-10, with 10 being the worst pain of your life*
- Quantifying pain intensity is useful for assessing the **severity of discomfort** and monitoring changes over time.
- However, for a patient with intermittent rather than acute, severe pain, understanding the **character, location, and triggers** of the pain is often more diagnostically valuable than just a numerical rating initially.
*Are the symptoms worse in the morning or at night?*
- Diurnal variation can be relevant in certain conditions, such as inflammatory bowel diseases where nocturnal symptoms might be more concerning, or functional disorders whose symptoms might be stress-related.
- This is another **specific question** that should come after gathering a more complete initial picture of the patient's symptoms to ensure no key information is overlooked.
Factorial designs US Medical PG Question 5: You are interested in studying the etiology of heart failure reduced ejection fraction (HFrEF) and attempt to construct an appropriate design study. Specifically, you wish to look for potential causality between dietary glucose consumption and HFrEF. Which of the following study designs would allow you to assess for and determine this causality?
- A. Cross-sectional study
- B. Case series
- C. Cohort study (Correct Answer)
- D. Case-control study
- E. Randomized controlled trial
Factorial designs Explanation: ***Cohort study***
- A **cohort study** observes a group of individuals over time to identify risk factors and outcomes, allowing for the assessment of **temporal relationships** between exposure (dietary glucose) and outcome (HFrEF).
- This design is suitable for establishing a potential **causal link** as it tracks participants from exposure to outcome, enabling the calculation of incidence rates and relative risks.
*Cross-sectional study*
- A **cross-sectional study** measures exposure and outcome simultaneously at a single point in time, making it impossible to determine the **temporal sequence** of events.
- This design can only identify **associations** or correlations, not causation, as it cannot establish whether high glucose consumption preceded HFrEF.
*Case series*
- A **case series** describes characteristics of a group of patients with a particular disease or exposure, often to highlight unusual clinical features, but it lacks a **comparison group**.
- It cannot assess causality because it does not provide information on the frequency of exposure in healthy individuals or the incidence of the disease in unexposed individuals.
*Case-control study*
- A **case-control study** compares individuals with the outcome (cases) to those without the outcome (controls) to determine past exposures, which makes it prone to **recall bias**.
- While it can suggest associations, it cannot definitively establish a temporal relationship or causation as the outcome is already known when exposure is assessed.
*Randomized controlled trial*
- A **randomized controlled trial (RCT)** is the gold standard for establishing causation by randomly assigning participants to an intervention or control group, but it may not be ethical or feasible for studying long-term dietary exposures and chronic diseases like HFrEF due to the long follow-up period and complexity of diet.
- While ideal for causality, directly controlling and randomizing dietary glucose intake over decades to observe HFrEF development might be practically challenging or unethical.
Factorial designs US Medical PG Question 6: A clinical trial is conducted to determine the efficacy of ginkgo biloba in the treatment of Parkinson disease. A sample of patients with Parkinson disease is divided into two groups. Participants in the first group are treated with ginkgo biloba, and participants in the other group receive a placebo. A change in the Movement Disorder Society-Unified Parkinson Disease Rating Scale (MDS-UPDRS) score is used as the primary endpoint for the study. The investigators, participants, and data analysts were meant to be blinded throughout the trial. However, while the trial is being conducted, the patients' demographics and their allocated treatment groups are mistakenly disclosed to the investigators, but not to the participants or the data analysts, because of a technical flaw. The study concludes that there is a significant decrease in MDS-UPDRS scores in patients treated with ginkgo biloba. Which of the following is most likely to have affected the validity of this study?
- A. Effect modification
- B. Recall bias
- C. Pygmalion effect (Correct Answer)
- D. Hawthorne effect
- E. Procedure bias
Factorial designs Explanation: ***Pygmalion effect***
- The **Pygmalion effect**, also known as **observer-expectancy bias** or experimenter bias, occurs when an investigator's expectations about the outcome of a study unintentionally influence the results.
- In this case, the **investigators becoming unblinded** to treatment assignments could lead them to unconsciously influence patient assessments or interactions based on their knowledge of who received ginkgo biloba, potentially leading to inflated positive outcomes for the treatment group.
*Effect modification*
- **Effect modification** describes a phenomenon where the effect of an exposure on an outcome is different across various strata of a third variable.
- This is a true biological interaction and does not represent a bias or flaw in the study design due to unblinding.
*Recall bias*
- **Recall bias** occurs when participants' memories of past exposures or events differ based on their current health status or knowledge of their condition.
- This bias primarily affects studies that rely on **retrospective reporting** of past events and is not relevant to the unblinding of investigators in a prospective clinical trial.
*Hawthorne effect*
- The **Hawthorne effect** describes a phenomenon where participants in a study change their behavior simply because they are aware of being observed, regardless of the intervention they receive.
- While participant blinding is important to prevent this, the scenario describes investigators being unblinded, not the participants.
*Procedure bias*
- **Procedure bias** (also known as interviewer bias or performance bias) arises from systematic differences in the way data is collected or procedures are performed for different study groups.
- While investigator unblinding can lead to elements of procedure bias, the more specific and encompassing term for an investigator's expectations influencing results is the **Pygmalion effect** (observer-expectancy bias).
Factorial designs US Medical PG Question 7: A study seeks to investigate the therapeutic efficacy of treating asymptomatic subclinical hypothyroidism in preventing symptoms of hypothyroidism. The investigators found 300 asymptomatic patients with subclinical hypothyroidism, defined as serum thyroid-stimulating hormone (TSH) of 5 to 10 μU/mL with normal serum thyroxine (T4) levels. The patients were randomized to either thyroxine 75 μg daily or placebo. Both investigators and study subjects were blinded. Baseline patient characteristics were distributed similarly in the treatment and control group (p > 0.05). Participants' serum T4 and TSH levels and subjective quality of life were evaluated at a 3-week follow-up. No difference was found between the treatment and placebo groups. Which of the following is the most likely explanation for the results of this study?
- A. Observer effect
- B. Berkson bias
- C. Latency period (Correct Answer)
- D. Confounding bias
- E. Lead-time bias
Factorial designs Explanation: ***Latency period***
- A **latency period** refers to the time between exposure to a cause (e.g., treatment) and the manifestation of its effects (e.g., symptom improvement). The study's **3-week follow-up is too short** to observe the therapeutic benefits of thyroxine in subclinical hypothyroidism.
- Levothyroxine (T4) has a **half-life of approximately 7 days**, and it typically takes **6-8 weeks or longer** for steady-state levels to be achieved and for clinical symptoms to improve. The slow onset of action for thyroid hormone replacement and the gradual nature of symptom resolution mean a longer observation period (typically 3-6 months) is needed to assess efficacy in hypothyroidism.
- The null results likely reflect insufficient follow-up time rather than lack of treatment effect.
*Observer effect*
- The **observer effect**, or Hawthorne effect, occurs when subjects change their behavior because they know they are being observed. This study used **double-blinding** (both investigators and subjects), which effectively minimizes the observer effect.
- The primary issue here is the lack of observed therapeutic effect due to timing, not a change in behavior due to observation.
*Berkson bias*
- **Berkson bias** is a form of selection bias that arises in case-control studies conducted in hospitals, where the probability of being admitted to the hospital can be affected by both exposure and disease.
- This study is a **randomized controlled trial**, not a case-control study, and the selection of participants does not illustrate this specific bias.
*Confounding bias*
- **Confounding bias** occurs when an extraneous variable is associated with both the exposure and the outcome, distorting the observed relationship. The study states that **baseline patient characteristics were similarly distributed (p > 0.05)**, indicating successful randomization and minimization of confounding.
- While confounding is a common concern in observational studies, the RCT design and reported baseline similarities make it unlikely to be the primary explanation for the null results compared to an insufficient follow-up period.
*Lead-time bias*
- **Lead-time bias** is a form of detection bias where early detection of a disease through screening appears to prolong survival, even if the treatment does not change the course of the disease.
- This study is evaluating the **efficacy of treatment** in asymptomatic individuals with subclinical hypothyroidism, not the effect of screening on survival, making lead-time bias irrelevant to these results.
Factorial designs US Medical PG Question 8: In the study, all participants who were enrolled and randomly assigned to treatment with pulmharkimab were analyzed in the pulmharkimab group regardless of medication nonadherence or refusal of allocated treatment. A medical student reading the abstract is confused about why some participants assigned to pulmharkimab who did not adhere to the regimen were still analyzed as part of the pulmharkimab group. Which of the following best reflects the purpose of such an analysis strategy?
- A. To minimize type 2 errors
- B. To assess treatment efficacy more accurately
- C. To reduce selection bias (Correct Answer)
- D. To increase internal validity of study
- E. To increase sample size
Factorial designs Explanation: ***To reduce selection bias***
- Analyzing participants in their originally assigned groups, regardless of adherence, is known as **intention-to-treat (ITT) analysis**.
- This method helps **preserve randomization** and minimizes **selection bias** that could arise if participants who did not adhere to treatment were excluded or re-assigned.
- **This is the most direct and specific purpose** of ITT analysis - preventing systematic differences between groups caused by post-randomization exclusions.
*To minimize type 2 errors*
- While ITT analysis affects statistical power, its primary purpose is not specifically to minimize **type 2 errors** (false negatives).
- ITT analysis may sometimes *increase* the likelihood of a type 2 error by diluting the treatment effect due to non-adherence.
*To assess treatment efficacy more accurately*
- ITT analysis assesses the **effectiveness** of *assigning* a treatment in a real-world setting, rather than the pure biological **efficacy** of the treatment itself.
- Efficacy is better assessed by a **per-protocol analysis**, which only includes compliant participants.
- ITT provides a more **conservative** and **pragmatic** estimate of treatment effect.
*To increase internal validity of study*
- While ITT analysis does contribute to **internal validity** by maintaining randomization, this is a **broader, secondary benefit** rather than the primary purpose.
- Internal validity encompasses many aspects of study design; ITT specifically addresses **post-randomization bias prevention**.
- The more precise answer is that ITT reduces **selection bias**, which is one specific threat to internal validity.
- Many other design features also contribute to internal validity (blinding, standardized protocols, etc.), making this option less specific.
*To increase sample size*
- ITT analysis includes all randomized participants, so it maintains the initial **sample size** that was randomized.
- However, the primary purpose is to preserve the integrity of randomization and prevent bias, not simply to increase the number of participants in the final analysis.
Factorial designs US Medical PG Question 9: A randomized control double-blind study is conducted on the efficacy of 2 sulfonylureas. The study concluded that medication 1 was more efficacious in lowering fasting blood glucose than medication 2 (p ≤ 0.05; 95% CI: 14 [10-21]). Which of the following is true regarding a 95% confidence interval (CI)?
- A. If the same study were repeated multiple times, approximately 95% of the calculated confidence intervals would contain the true population parameter. (Correct Answer)
- B. The 95% confidence interval is the probability chosen by the researcher to be the threshold of statistical significance.
- C. When a 95% CI for the estimated difference between groups contains the value ‘0’, the results are significant.
- D. It represents the probability that chance would not produce the difference shown, 95% of the time.
- E. The study is adequately powered at the 95% confidence interval.
Factorial designs Explanation: ***If the same study were repeated multiple times, approximately 95% of the calculated confidence intervals would contain the true population parameter.***
- This statement accurately defines the **frequentist interpretation** of a confidence interval (CI). It reflects the long-run behavior of the CI over hypothetical repetitions of the study.
- A 95% CI means that if you were to repeat the experiment many times, 95% of the CIs calculated from those experiments would capture the **true underlying population parameter**.
*The 95% confidence interval is the probability chosen by the researcher to be the threshold of statistical significance.*
- The **alpha level (α)**, typically set at 0.05 (or 5%), is the threshold for statistical significance (p ≤ 0.05), representing the probability of a Type I error.
- The 95% confidence level (1-α) is related to statistical significance, but it is not the *threshold* itself; rather, it indicates the **reliability** of the interval estimate.
*When a 95% CI for the estimated difference between groups contains the value ‘0’, the results are significant.*
- If a 95% CI for the difference between groups **contains 0**, it implies that there is **no statistically significant difference** between the groups at the 0.05 alpha level.
- A statistically significant difference (p ≤ 0.05) would be indicated if the 95% CI **does NOT contain 0**, suggesting that the intervention had a real effect.
*It represents the probability that chance would not produce the difference shown, 95% of the time.*
- This statement misinterprets the meaning of a CI and probability. The chance of not producing the observed difference is typically addressed by the **p-value**, not directly by the CI in this manner.
- A CI provides a **range of plausible values** for the population parameter, not a probability about the role of chance in producing the observed difference.
*The study is adequately powered at the 95% confidence interval.*
- **Statistical power** is the probability of correctly rejecting a false null hypothesis, typically set at 80% or 90%. It is primarily determined by sample size, effect size, and alpha level.
- A 95% CI is a measure of the **precision** of an estimate, while power refers to the **ability of a study to detect an effect** if one exists. They are related but distinct concepts.
Factorial designs US Medical PG Question 10: A randomized controlled trial is conducted investigating the effects of different diagnostic imaging modalities on breast cancer mortality. 8,000 women are randomized to receive either conventional mammography or conventional mammography with breast MRI. The primary outcome is survival from the time of breast cancer diagnosis. The conventional mammography group has a median survival after diagnosis of 17.0 years. The MRI plus conventional mammography group has a median survival of 19.5 years. If this difference is statistically significant, which form of bias may be affecting the results?
- A. Recall bias
- B. Selection bias
- C. Misclassification bias
- D. Because this study is a randomized controlled trial, it is free of bias
- E. Lead-time bias (Correct Answer)
Factorial designs Explanation: ***Lead-time bias***
- This bias occurs when a screening test diagnoses a disease earlier, making **survival appear longer** even if the actual time of death is unchanged.
- In this scenario, adding **MRI** may detect breast cancer at an earlier, asymptomatic stage, artificially extending the apparent survival duration from diagnosis without necessarily changing the ultimate prognosis.
*Recall bias*
- **Recall bias** applies to retrospective studies where subjects are asked to recall past exposures, and those with the outcome are more likely to remember potential exposures.
- It's irrelevant here as this is a **prospective randomized controlled trial** studying objective survival outcomes, not subjective past recollections.
*Selection bias*
- **Selection bias** occurs when participants are not randomly assigned to groups, leading to systematic differences between the groups influencing the outcome.
- This study is a **randomized controlled trial**, which is designed to minimize selection bias by ensuring participants have an equal chance of being assigned to either treatment arm.
*Misclassification bias*
- **Misclassification bias** happens when either the exposure or the outcome is incorrectly categorized, leading to erroneous associations.
- This study uses objective diagnostic imaging and survival data, thus reducing the likelihood of **misclassification of diagnosis or survival status**.
*Because this study is a randomized controlled trial, it is free of bias*
- While **randomized controlled trials (RCTs)** are considered the **gold standard** for minimizing bias, they are not entirely immune to all forms of bias.
- **Lead-time bias**, for instance, can still occur in RCTs involving screening or early diagnosis, as seen in this example, and other biases like **information bias** or **reporting bias** can also arise.
More Factorial designs US Medical PG questions available in the OnCourse app. Practice MCQs, flashcards, and get detailed explanations.
