We are analyzing https://link.springer.com/article/10.1007/s40273-016-0429-5.

Title:
Using Best–Worst Scaling to Investigate Preferences in Health Care | PharmacoEconomics
Description:
Introduction Best–worst scaling (BWS) is becoming increasingly popular to elicit preferences in health care. However, little is known about current practice and trends in the use of BWS in health care. This study aimed to identify, review and critically appraise BWS in health care, and to identify trends over time in key aspects of BWS. Methods A systematic review was conducted, using Medline (via Pubmed) and EMBASE to identify all English-language BWS studies published up until April 2016. Using a predefined extraction form, two reviewers independently selected articles and critically appraised the study quality, using the Purpose, Respondents, Explanation, Findings, Significance (PREFS) checklist. Trends over time periods (≤2010, 2011, 2012, 2013, 2014 and 2015) were assessed further. Results A total of 62 BWS studies were identified, of which 26 were BWS object case studies, 29 were BWS profile case studies and seven were BWS multi-profile case studies. About two thirds of the studies were performed in the last 2 years. Decreasing sample sizes and decreasing numbers of factors in BWS object case studies, as well as use of less complicated analytical methods, were observed in recent studies. The quality of the BWS studies was generally acceptable according to the PREFS checklist, except that most studies did not indicate whether the responders were similar to the non-responders. Conclusion Use of BWS object case and BWS profile case has drastically increased in health care, especially in the last 2 years. In contrast with previous discrete-choice experiment reviews, there is increasing use of less sophisticated analytical methods.
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Keywords {🔍}

bws, case, health, studies, article, pubmed, google, scholar, scaling, care, bestworst, preferences, profile, choice, object, study, multiprofile, factors, methods, analysis, review, number, included, data, patient, research, dce, worst, experiments, articles, quality, discrete, conjoint, size, published, bridges, trends, flynn, results, sample, experiment, louviere, med, central, policy, assess, econ, current, respondents, method,

Topics {✒️}

eq-5d-5l health states kei long cheung de bekker‐grob child health utility-9d article download pdf bws multi-profile case adult health-state values free-text terms focusing competing multi-profile options mnl multinomial logistic regression smaller sample size minimal sample size sample size requirements full-text review resulted traditional discrete-choice experiments mickael hiligsmann designed health care goods/services privacy choices/manage cookies article cheung qual life res duchenne muscular dystrophy young adolescent sample caphri research school multinomial logistic regression refractory overactive bladder bmc palliat care smaller sample sizes van bodegom-vos related subjects health services research choice-based conjoint bws profile case bws profile case support health policy decreasing sample sizes health technology assessment worst scaling methodology discrete choice experiment conditions privacy policy full-text articles sample size health care research preference valuation techniques research team discussed valuing health outcomes health econ rev discrete choice experiments discrete-choice experiments full-text review bws survey administration

Questions {❓}

Eliciting preferences to the EQ-5D-5L health states: discrete choice experiment or multiprofile case of best–worst scaling?
Nothing about us without us?
PREFS assesses five criteria as acceptable (1) or unacceptable (0): the purpose of the study (is the purpose of the study in relation to preferences clearly stated?
Should I stay or should I go?
Should support for obesity interventions or perceptions of their perceived effectiveness shape policy?
What criteria guide national entrepreneurs’ policy decisions on user fee removal for maternal health care services?
What’s good and bad about contraceptive products?

Schema {🗺️}

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         Public Health
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