instruction:
Given a passage with a context and an answer, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the passage. Avoid creating questions that (i) can't be answered correctly without actually understanding the passage and (ii) uses the same words or phrases given in the passage.
question:
Context: To determine the prevalence of five physical frailty phenotype components and to assess the relationship between them and other clinical factors.', "A population-based cross-sectional study was performed. Subjects 75 years and older were randomly selected from primary care databases (with sampling stratified by gender). Physical frailty phenotypes were assessed using Fried's criteria. Sociodemographic data, comorbidities, nutritional status, and functional capacity were assessed.", '126 subjects were recruited (47% women). Prevalence rates were poor muscle strength: 50%; low physical activity: 29%; slow gait: 28%; exhaustion: 27%; and weight loss: 5%. Prefrailty and frailty prevalence rates were 35.7% and 29.4%, respectively. Poor muscle strength and low physical activity showed a close relationship and concordance (kappa = 0.92). Most frailty components were associated with outdoor activity, hours walked daily, and certain comorbidities.
Answer: Poor muscle strength was the most prevalent frailty component and was closely associated with physical activity, suggesting that training programs may revert or prevent the frailty process.
answer:
Do poor Muscle Strength and Low Physical Activity Are the Most Prevalent Frailty Components in Community-Dwelling Older Adults?


question:
Context: A computerized physician order entry (CPOE) system with embedded clinical decision support can reduce medication errors in hospitals, but might increase the time taken to generate orders.', 'We aimed to quantify the effects of temporal (month, day of week, hour of shift) and other factors (grade of doctor, prior experience with the system, alert characteristics, and shift type) on the time taken to generate a prescription order.', 'A large university teaching hospital using a locally developed CPOE system with an extensive audit database.', 'We retrospectively analyzed prescription orders from the audit database between August 2011 and July 2012.', 'The geometric mean time taken to generate a prescription order within the CPOE system was 11.75\u2005s (95% CI 11.72 to 11.78). Time to prescribe was most affected by the display of high-level (24.59\u2005s (24.43 to 24.76); p<0.001) or previously unseen (18.87\u2005s (18.78 to 18.96); p<0.001) alerts. Prescribers took significantly less time at weekends (11.29\u2005s (11.23 to 11.35)) than on weekdays (11.88\u2005s (11.84 to 11.91); p<0.001), in the first (11.25\u2005s (11.16 to 11.34); p<0.001) and final (11.56\u2005s (11.47 to 11.66); p<0.001) hour of their shifts, and after the first month of using the system.
Answer: The display of alerts, prescribing experience, system familiarity, and environment all affect the time taken to generate a prescription order. Our study reinforces the need for appropriate alerts to be presented to individuals at an appropriate place in the workflow, in order to improve prescribing efficiency.
answer:
Do temporal and other factors that influence the time doctors take to prescribe using an electronic prescribing system?


question:
Context: The study's aim was to assess the internal reliability for the nine domains of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) to evaluate homogeneity across clinical studies and whether sample characteristics predict coefficient heterogeneity.", 'A systematic literature review was undertaken. Internal reliability was assessed against Cronbach α coefficient >0.70. Reliability generalization was undertaken using fixed- and random-effects models. A weighted least squares regression model was applied to determine whether baseline sample characteristics (language, percentage of women, sample size, sample means and standard deviations, and cancer type) predicted variation in α coefficients.', 'A total of 33 studies were identified. Eight domains demonstrated good internal reliability (unweighted/weighted by sample variance). One domain, Cognitive Functioning, consistently performed poorly. In terms of moderating variables, none of the sample characteristic variables explained sample variance for the Physical or Role Functioning domains. For the other domains, language, percentage of women, and sample means and variances accounted for some of the heterogeneity observed.
Answer: Most domains on the EORTC QLQ-C30 are reliable and may therefore be used to help inform decision-making processes, such as those involving individual patients.
answer:

Are most domains of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 reliable?