Literature DB >> 33549068

Do people have differing motivations for participating in a stated-preference study? Results from a latent-class analysis.

Ilene L Hollin1, Ellen Janssen2, Marcella A Kelley3,4, John F P Bridges5,6.   

Abstract

BACKGROUND: Researchers and policy makers have long suspected that people have differing, and potentially nefarious, motivations for participating in stated-preference studies such as discrete-choice experiments (DCE). While anecdotes and theories exist on why people participate in surveys, there is a paucity of evidence exploring variation in preferences for participating in stated-preference studies.
METHODS: We used a DCE to estimate preferences for participating in preference research among an online survey panel sample. Preferences for the characteristics of a study to be conducted at a local hospital were assessed across five attributes (validity, relevance, bias, burden, time and payment) and described across three levels using a starring system. A D-efficient experimental design was used to construct three blocks of 12 choice tasks with two profiles each. Respondents were also asked about factors that motivated their choices. Mixed logistic regression was used to analyze the aggregate sample and latent class analysis identified segments of respondents.
RESULTS: 629 respondents completed the experiment. In aggregate "study validity" was most important. Latent class results identified two segments based on underlying motivations: a quality-focused segment (76%) who focused most on validity, relevance, and bias and a convenience-focused segment (24%) who focused most on reimbursement and time. Quality-focused respondents spent more time completing the survey (p < 0.001) and were more likely to identify data quality (p < 0.01) and societal well-being (p < 0.01) as motivations to participate.
CONCLUSIONS: This information can be used to better understand variability in motivations to participate in stated-preference surveys and the impact of motivations on response quality.

Entities:  

Keywords:  Discrete choice experiments; Stated preferences; Surveys

Mesh:

Year:  2021        PMID: 33549068      PMCID: PMC7868025          DOI: 10.1186/s12911-021-01412-1

Source DB:  PubMed          Journal:  BMC Med Inform Decis Mak        ISSN: 1472-6947            Impact factor:   2.796


  22 in total

1.  'Irrational' stated preferences: a quantitative and qualitative investigation.

Authors:  Fernando San Miguel; Mandy Ryan; Mabelle Amaya-Amaya
Journal:  Health Econ       Date:  2005-03       Impact factor: 3.046

2.  Who pays attention in stated-choice surveys?

Authors:  Semra Ozdemir; Ateesha F Mohamed; F Reed Johnson; A Brett Hauber
Journal:  Health Econ       Date:  2010-01       Impact factor: 3.046

3.  Conjoint analysis applications in health--a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force.

Authors:  John F P Bridges; A Brett Hauber; Deborah Marshall; Andrew Lloyd; Lisa A Prosser; Dean A Regier; F Reed Johnson; Josephine Mauskopf
Journal:  Value Health       Date:  2011-04-22       Impact factor: 5.725

4.  The Internal Validity of Discrete Choice Experiment Data: A Testing Tool for Quantitative Assessments.

Authors:  F Reed Johnson; Jui-Chen Yang; Shelby D Reed
Journal:  Value Health       Date:  2018-09-27       Impact factor: 5.725

5.  Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force.

Authors:  A Brett Hauber; Juan Marcos González; Catharina G M Groothuis-Oudshoorn; Thomas Prior; Deborah A Marshall; Charles Cunningham; Maarten J IJzerman; John F P Bridges
Journal:  Value Health       Date:  2016-05-12       Impact factor: 5.725

6.  Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review.

Authors:  Mo Zhou; Winter Maxwell Thayer; John F P Bridges
Journal:  Pharmacoeconomics       Date:  2018-02       Impact factor: 4.981

7.  Constructing experimental designs for discrete-choice experiments: report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force.

Authors:  F Reed Johnson; Emily Lancsar; Deborah Marshall; Vikram Kilambi; Axel Mühlbacher; Dean A Regier; Brian W Bresnahan; Barbara Kanninen; John F P Bridges
Journal:  Value Health       Date:  2013 Jan-Feb       Impact factor: 5.725

8.  Conducting discrete choice experiments to inform healthcare decision making: a user's guide.

Authors:  Emily Lancsar; Jordan Louviere
Journal:  Pharmacoeconomics       Date:  2008       Impact factor: 4.981

9.  Developing a Patient-Centered Benefit-Risk Survey: A Community-Engaged Process.

Authors:  Ilene L Hollin; Caroline Hanson; John F P Bridges; Holly Peay
Journal:  Value Health       Date:  2016 Sep - Oct       Impact factor: 5.725

10.  Education and patient preferences for treating type 2 diabetes: a stratified discrete-choice experiment.

Authors:  Ellen M Janssen; Daniel R Longo; Joan K Bardsley; John Fp Bridges
Journal:  Patient Prefer Adherence       Date:  2017-10-06       Impact factor: 2.711

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