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  2. Matching Content Categories
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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.
Website Age:
28 years and 1 months (reg. 1997-05-29).

Matching Content Categories {📚}

  • Education
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  • Science

Content Management System {📝}

What CMS is link.springer.com built with?

Custom-built

No common CMS systems were detected on Link.springer.com, and no known web development framework was identified.

Traffic Estimate {📈}

What is the average monthly size of link.springer.com audience?

🌠 Phenomenal Traffic: 5M - 10M visitors per month


Based on our best estimate, this website will receive around 7,642,828 visitors per month in the current month.

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How Does Link.springer.com Make Money? {💸}

We find it hard to spot revenue streams.

The purpose of some websites isn't monetary gain; they're meant to inform, educate, or foster collaboration. Everyone has unique reasons for building websites. This could be an example. Link.springer.com could be getting rich in stealth mode, or the way it's monetizing isn't detectable.

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 {🗺️}

WebPage:
      mainEntity:
         headline:Using Best–Worst Scaling to Investigate Preferences in Health Care
         description: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. 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. 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. 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.
         datePublished:2016-07-11T00:00:00Z
         dateModified:2016-07-11T00:00:00Z
         pageStart:1195
         pageEnd:1209
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            Choice Task
            Conjoint Analysis
            Balance Incomplete Block Design
            Decrease Sample Size
            Included Factor
            Pharmacoeconomics and Health Outcomes
            Quality of Life Research
            Health Economics
            Health Administration
            Public Health
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      headline:Using Best–Worst Scaling to Investigate Preferences in Health Care
      description: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. 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. 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. 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.
      datePublished:2016-07-11T00:00:00Z
      dateModified:2016-07-11T00:00:00Z
      pageStart:1195
      pageEnd:1209
      sameAs:https://doi.org/10.1007/s40273-016-0429-5
      keywords:
         Choice Task
         Conjoint Analysis
         Balance Incomplete Block Design
         Decrease Sample Size
         Included Factor
         Pharmacoeconomics and Health Outcomes
         Quality of Life Research
         Health Economics
         Health Administration
         Public Health
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                     name:Department of Health Services Research, CAPHRI Research School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
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                  name:Epilepsy Centre Kempenhaeghe
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                     name:Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, The Netherlands
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Ilene L. Hollin
            affiliation:
                  name:Johns Hopkins Bloomberg School of Public Health
                  address:
                     name:Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
                     type:PostalAddress
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                     type:PostalAddress
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                  name:Johns Hopkins Bloomberg School of Public Health
                  address:
                     name:Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
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                  address:
                     name:Department of Health Services Research, CAPHRI Research School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
                     type:PostalAddress
                  type:Organization
            type:Person
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                  name:Maastricht University
                  address:
                     name:Department of Health Services Research, CAPHRI Research School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
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      name:Kei Long Cheung
      url:http://orcid.org/0000-0001-7648-4556
      affiliation:
            name:Maastricht University
            address:
               name:Department of Health Services Research, CAPHRI Research School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
               type:PostalAddress
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      email:[email protected]
      name:Ben F. M. Wijnen
      affiliation:
            name:Maastricht University
            address:
               name:Department of Health Services Research, CAPHRI Research School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
               type:PostalAddress
            type:Organization
            name:Epilepsy Centre Kempenhaeghe
            address:
               name:Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, The Netherlands
               type:PostalAddress
            type:Organization
      name:Ilene L. Hollin
      affiliation:
            name:Johns Hopkins Bloomberg School of Public Health
            address:
               name:Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
               type:PostalAddress
            type:Organization
      name:Ellen M. Janssen
      affiliation:
            name:Johns Hopkins Bloomberg School of Public Health
            address:
               name:Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
               type:PostalAddress
            type:Organization
      name:John F. Bridges
      affiliation:
            name:Johns Hopkins Bloomberg School of Public Health
            address:
               name:Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
               type:PostalAddress
            type:Organization
      name:Silvia M. A. A. Evers
      affiliation:
            name:Maastricht University
            address:
               name:Department of Health Services Research, CAPHRI Research School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
               type:PostalAddress
            type:Organization
      name:Mickael Hiligsmann
      affiliation:
            name:Maastricht University
            address:
               name:Department of Health Services Research, CAPHRI Research School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
               type:PostalAddress
            type:Organization
PostalAddress:
      name:Department of Health Services Research, CAPHRI Research School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
      name:Department of Health Services Research, CAPHRI Research School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
      name:Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, The Netherlands
      name:Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
      name:Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
      name:Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
      name:Department of Health Services Research, CAPHRI Research School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands
      name:Department of Health Services Research, CAPHRI Research School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands

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