Introduction: This blog presents a focused collection of multiple-choice questions on common Health-Related Quality of Life (HRQOL) instruments and their scoring, tailored for M.Pharm students studying Pharmacoepidemiology & Pharmacoeconomics. The questions cover widely used tools such as SF-36, EQ-5D, WHOQOL-BREF, EORTC QLQ-C30, FACT, PROMIS and preference-based scoring approaches used to derive utilities for QALY calculations. Emphasis is placed on scoring rules, transformation methods, handling missing data, psychometric properties, interpretation (MCID), and applications in cost-utility analysis. Use these MCQs for exam practice and to deepen practical understanding of HRQOL measurement in clinical trials and outcomes research.
Q1. Which statement correctly describes the SF-36 scoring structure?
- Eight domains each scored 0–100, with higher scores indicating better health
- Five domains with a single global score from 0–1, higher is worse
- Ten domains scored on a 0–10 scale and summed raw score
- Single index score derived from time trade-off valuations
Correct Answer: Eight domains each scored 0–100, with higher scores indicating better health
Q2. The EQ-5D descriptive system produces a health state that is converted into a utility using:
- A tariff (value set) based on general population preferences, e.g., time trade-off or discrete choice
- Raw sum of domain scores transformed linearly to 0–100
- Patient’s self-rated visual analogue scale only
- Principal component analysis of the five items
Correct Answer: A tariff (value set) based on general population preferences, e.g., time trade-off or discrete choice
Q3. Which is a correct feature of the EQ-5D-5L compared with EQ-5D-3L?
- Five-level severity options per dimension to reduce ceiling effects and improve sensitivity
- Only three dimensions instead of five to simplify scoring
- Generates domain scores on a 0–100 scale directly without conversion
- Uses PROMIS T-scores as default output
Correct Answer: Five-level severity options per dimension to reduce ceiling effects and improve sensitivity
Q4. In preference-based measures used for QALY calculations, the utility value range typically anchors at:
- 1.0 for full health and 0.0 for dead, with possible negative values for states worse than dead
- 0–100 with 100 representing worst health
- 0–1 where 0 always represents worst possible health and cannot be negative
- Mean 50, SD 10 standardized T-score metric
Correct Answer: 1.0 for full health and 0.0 for dead, with possible negative values for states worse than dead
Q5. Which scoring characteristic applies to WHOQOL-BREF?
- Four domain scores transformed to a 0–100 scale where higher scores denote better quality of life
- Produces a preference-based index directly suitable for QALY without mapping
- Specifically only for cancer patients with symptom indices
- Scored by time trade-off valuations for each domain
Correct Answer: Four domain scores transformed to a 0–100 scale where higher scores denote better quality of life
Q6. For EORTC QLQ-C30, which statement about scoring is correct?
- Functional scales and global health are scored so higher is better, symptom scales are scored so higher is worse; all transformed to 0–100
- All scales summed to a single score where higher is always worse
- Raw item totals are reported without transformation or interpretation guidance
- Domain scores are converted to utilities using an EQ-5D tariff
Correct Answer: Functional scales and global health are scored so higher is better, symptom scales are scored so higher is worse; all transformed to 0–100
Q7. What is the PROMIS T-score metric convention?
- T-scores have a mean of 50 and standard deviation of 10 in the reference population, higher scores indicate more of the trait measured
- Scores range 0–100 where 0 is perfect health and 100 is worst health
- Scores are preference weights for QALY calculations
- Item response theory is not used in PROMIS scoring
Correct Answer: T-scores have a mean of 50 and standard deviation of 10 in the reference population, higher scores indicate more of the trait measured
Q8. Which approach is commonly used to handle a single missing item within a multi-item scale for SF-36 or similar instruments?
- Prorating the scale score if a minimum number of items are present, using mean of completed items on that scale
- Automatically exclude the respondent from all analyses
- Replace missing with the global sample mean for the entire questionnaire
- Use time trade-off to estimate the missing response
Correct Answer: Prorating the scale score if a minimum number of items are present, using mean of completed items on that scale
Q9. Which statement best describes minimal clinically important difference (MCID) for HRQOL instruments?
- Smallest change in score perceived as important by patients or clinicians, often estimated by anchor- or distribution-based methods
- Arbitrary 10-point cutoff used for all instruments regardless of context
- Always equal to one standard deviation of baseline scores only
- Defined only for utility measures, not for domain scores
Correct Answer: Smallest change in score perceived as important by patients or clinicians, often estimated by anchor- or distribution-based methods
Q10. Which psychometric property is primarily assessed by Cronbach’s alpha?
- Internal consistency (how well items on a scale measure the same construct)
- Test–retest reliability across separate administrations
- Responsiveness to clinical change over time
- Convergent validity with other instruments
Correct Answer: Internal consistency (how well items on a scale measure the same construct)
Q11. Which of the following is TRUE about mapping (cross-walking) from non–preference-based HRQOL instruments to utility values?
- Statistical models (e.g., OLS, Tobit, beta regression) predict utility values from domain or item scores when direct utility data are absent
- Mapping produces identical utilities to direct valuation with no prediction error
- Is not allowed in health technology assessment and therefore never used
- Requires converting all scores to VAS before modeling
Correct Answer: Statistical models (e.g., OLS, Tobit, beta regression) predict utility values from domain or item scores when direct utility data are absent
Q12. The Health Utilities Index (HUI) differs from SF-36 primarily by:
- Being a preference-based multi-attribute utility instrument with defined health state classification and community-derived utility weights
- Providing only domain scores on a 0–100 scale without utility conversion
- Using item-response theory and T-scores like PROMIS
- Measuring only mental health and ignoring physical functioning
Correct Answer: Being a preference-based multi-attribute utility instrument with defined health state classification and community-derived utility weights
Q13. When calculating QALYs from longitudinal utility data, the most appropriate method is:
- Area under the curve (AUC) approach interpolating utilities between measurement points over time
- Taking the midpoint utility only and multiplying by total follow-up duration regardless of change
- Using baseline utility for all follow-up periods to avoid complexity
- Summing raw HRQOL domain scores as a substitute for utilities
Correct Answer: Area under the curve (AUC) approach interpolating utilities between measurement points over time
Q14. Which of the following indicates a responsiveness statistic commonly used to express change magnitude in HRQOL studies?
- Standardized Response Mean (SRM) defined as mean change divided by the standard deviation of change scores
- Factor loading from exploratory factor analysis
- Cronbach’s alpha divided by sample size
- Number needed to treat (NNT) derived directly from domain scores
Correct Answer: Standardized Response Mean (SRM) defined as mean change divided by the standard deviation of change scores
Q15. Which practice is recommended when comparing HRQOL scores across countries?
- Consider cultural adaptation, validated translations, and use country-specific value sets for preference measures when available
- Assume all instruments are culturally equivalent and use the same tariff globally
- Only compare raw item scores without any adjustment for language or culture
- Convert all scores to SF-36 norms regardless of the instrument used
Correct Answer: Consider cultural adaptation, validated translations, and use country-specific value sets for preference measures when available
Q16. In EORTC QLQ-C30 scoring, how are missing items within a multi-item scale usually handled?
- Compute the scale score if at least half the items in that scale are completed by prorating the mean of completed items
- Replace all missing items with the worst possible score
- Discard the entire questionnaire if any item is missing
- Use preference-based tariffs to impute missing values
Correct Answer: Compute the scale score if at least half the items in that scale are completed by prorating the mean of completed items
Q17. Which instrument is cancer-specific and includes subscales such as physical well-being, social/family well-being, emotional well-being, and functional well-being?
- FACT-G (Functional Assessment of Cancer Therapy – General)
- SF-6D general population preference measure
- EQ-5D descriptive system only
- PROMIS Pain Interference short form
Correct Answer: FACT-G (Functional Assessment of Cancer Therapy – General)
Q18. Which statement about ceiling and floor effects in HRQOL instruments is correct?
- High ceiling or floor effects limit an instrument’s ability to detect improvement or deterioration respectively and reduce responsiveness
- Ceiling effects mean the instrument is very sensitive to detecting small changes at the top end
- Floor effects indicate perfect measurement with no variability among respondents
- Ceiling and floor effects are irrelevant for preference-based measures used in economic models
Correct Answer: High ceiling or floor effects limit an instrument’s ability to detect improvement or deterioration respectively and reduce responsiveness
Q19. Which of the following is an example of an anchor-based method to estimate MCID?
- Using patient global impression of change (PGIC) categories to link score change to perceived meaningful improvement
- Calculating half a standard deviation of baseline scores only
- Using Cronbach’s alpha threshold to set the MCID
- Randomly selecting a point on the 0–100 scale as the MCID
Correct Answer: Using patient global impression of change (PGIC) categories to link score change to perceived meaningful improvement
Q20. Which property best describes convergent validity when evaluating an HRQOL instrument?
- Degree to which the instrument correlates with other measures that assess the same or related constructs
- Consistency of scores when the same respondents complete the instrument twice with no change in health
- Ability to predict future hospitalization events regardless of health status
- How quickly respondents can complete the questionnaire in minutes
Correct Answer: Degree to which the instrument correlates with other measures that assess the same or related constructs
