Attribute Selection for a Discrete Choice Experiment Incorporating a Best-Worst Scaling Survey
Although literature exists on using qualitative methods to generate potential attributes for a discrete choice experiment (DCE), there is little on selecting which attributes to include. We present a case study in which a best-worst scaling case 1 (BWS-1) survey was used to guide attribute selection...
Gespeichert in:
Veröffentlicht in: | Value in health 2021-04, Vol.24 (4), p.575-584 |
---|---|
Hauptverfasser: | , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 584 |
---|---|
container_issue | 4 |
container_start_page | 575 |
container_title | Value in health |
container_volume | 24 |
creator | Webb, Edward J.D. Meads, David Lynch, Yvonne Judge, Simon Randall, Nicola Goldbart, Juliet Meredith, Stuart Moulam, Liz Hess, Stephane Murray, Janice |
description | Although literature exists on using qualitative methods to generate potential attributes for a discrete choice experiment (DCE), there is little on selecting which attributes to include. We present a case study in which a best-worst scaling case 1 (BWS-1) survey was used to guide attribute selection for a DCE. The case study’s context was the decision making of professionals around the choice of augmentative and alternative communication (AAC) systems for children with limited natural speech.
BWS-1 survey attributes were generated from literature reviews and focus groups. DCE attributes were selected from BWS-1 attributes. The selection criteria were: include mostly important attributes; create coherent descriptions of children and AAC systems; address the project’s research aims; have an appropriate respondent burden. Attributes’ importance was judged using BWS-1 relative importance scores.
The BWS-1 survey included 19 child and 18 AAC device/system attributes and was administered to N = 93 AAC professionals. Four child and five device/system attributes were selected for the DCE, administered to N = 155 AAC professionals.
In this case study BWS-1 results were useful in DCE attribute selection. Four recommendations are made for future studies: define selection criteria for DCE attributes a priori; consider the impact participant’s perspective will have on BWS-1 and DCE results; clearly define key terminology at the start of the study and refine it as the study progresses to reflect interim findings; BWS will be useful when there is little existing stated preference work on a topic and/or qualitative work is difficult. |
doi_str_mv | 10.1016/j.jval.2020.10.025 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2511897978</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1098301520345125</els_id><sourcerecordid>2511897978</sourcerecordid><originalsourceid>FETCH-LOGICAL-c428t-35c5c1bb7d12992e0af82d742bdcafbbbdb87f7447cb2fb231df1d69673d95a63</originalsourceid><addsrcrecordid>eNp9kEtr3DAURkVpaV79A10EQzfZeKKXLRuySaaTBwS6mJTuKvS4bmU81kSSh-TfV2bSLLLISuLTuZdPB6GvBC8IJvV5v-h3alhQTOdggWn1AR2SivKSC8Y-5jtum5JhUh2goxh7jHHNaPUZHTDWcMxZfYh-X6YUnJ4SFGsYwCTnx6LzoVDFdxdNgPyw_OudgWL1tIXgNjCm4m40Pmx9UMmNfzJ6BTGVv3yIqVgbNczhego7eD5Bnzo1RPjych6jn9erh-Vtef_j5m55eV8aTptUsspUhmgtLKFtSwGrrqFWcKqtUZ3W2upGdIJzYTTtNGXEdsTWbS2YbStVs2N0tt-7Df5xym3kJreHYVAj-ClKWhHStKIVTUa_vUF7P4Uxt5spwUkjOM4U3VMm-BgDdHKb_67CsyRYzvZlL2f7crY_Z9l-Hjp9WT3pDdjXkf-6M3CxByC72DkIMhoHowHrQnYvrXfv7f8H-J-WPA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2517418740</pqid></control><display><type>article</type><title>Attribute Selection for a Discrete Choice Experiment Incorporating a Best-Worst Scaling Survey</title><source>Elsevier ScienceDirect Journals Complete</source><source>Applied Social Sciences Index & Abstracts (ASSIA)</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Webb, Edward J.D. ; Meads, David ; Lynch, Yvonne ; Judge, Simon ; Randall, Nicola ; Goldbart, Juliet ; Meredith, Stuart ; Moulam, Liz ; Hess, Stephane ; Murray, Janice</creator><creatorcontrib>Webb, Edward J.D. ; Meads, David ; Lynch, Yvonne ; Judge, Simon ; Randall, Nicola ; Goldbart, Juliet ; Meredith, Stuart ; Moulam, Liz ; Hess, Stephane ; Murray, Janice</creatorcontrib><description>Although literature exists on using qualitative methods to generate potential attributes for a discrete choice experiment (DCE), there is little on selecting which attributes to include. We present a case study in which a best-worst scaling case 1 (BWS-1) survey was used to guide attribute selection for a DCE. The case study’s context was the decision making of professionals around the choice of augmentative and alternative communication (AAC) systems for children with limited natural speech.
BWS-1 survey attributes were generated from literature reviews and focus groups. DCE attributes were selected from BWS-1 attributes. The selection criteria were: include mostly important attributes; create coherent descriptions of children and AAC systems; address the project’s research aims; have an appropriate respondent burden. Attributes’ importance was judged using BWS-1 relative importance scores.
The BWS-1 survey included 19 child and 18 AAC device/system attributes and was administered to N = 93 AAC professionals. Four child and five device/system attributes were selected for the DCE, administered to N = 155 AAC professionals.
In this case study BWS-1 results were useful in DCE attribute selection. Four recommendations are made for future studies: define selection criteria for DCE attributes a priori; consider the impact participant’s perspective will have on BWS-1 and DCE results; clearly define key terminology at the start of the study and refine it as the study progresses to reflect interim findings; BWS will be useful when there is little existing stated preference work on a topic and/or qualitative work is difficult.</description><identifier>ISSN: 1098-3015</identifier><identifier>EISSN: 1524-4733</identifier><identifier>DOI: 10.1016/j.jval.2020.10.025</identifier><identifier>PMID: 33840436</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>attribute development ; attribute selection ; Attributes ; Augmentative and alternative communication ; best-worst scaling ; Case studies ; Children ; Children & youth ; Decision making ; Discrete choice ; discrete choice experiment ; Discrete element method ; Literature reviews ; methodology ; Polls & surveys ; Qualitative research ; Selection criteria ; Speech ; Terminology</subject><ispartof>Value in health, 2021-04, Vol.24 (4), p.575-584</ispartof><rights>2020 ISPOR–The Professional Society for Health Economics and Outcomes Research</rights><rights>Copyright © 2020 ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Science Ltd. Apr 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c428t-35c5c1bb7d12992e0af82d742bdcafbbbdb87f7447cb2fb231df1d69673d95a63</citedby><cites>FETCH-LOGICAL-c428t-35c5c1bb7d12992e0af82d742bdcafbbbdb87f7447cb2fb231df1d69673d95a63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jval.2020.10.025$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,30999,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33840436$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Webb, Edward J.D.</creatorcontrib><creatorcontrib>Meads, David</creatorcontrib><creatorcontrib>Lynch, Yvonne</creatorcontrib><creatorcontrib>Judge, Simon</creatorcontrib><creatorcontrib>Randall, Nicola</creatorcontrib><creatorcontrib>Goldbart, Juliet</creatorcontrib><creatorcontrib>Meredith, Stuart</creatorcontrib><creatorcontrib>Moulam, Liz</creatorcontrib><creatorcontrib>Hess, Stephane</creatorcontrib><creatorcontrib>Murray, Janice</creatorcontrib><title>Attribute Selection for a Discrete Choice Experiment Incorporating a Best-Worst Scaling Survey</title><title>Value in health</title><addtitle>Value Health</addtitle><description>Although literature exists on using qualitative methods to generate potential attributes for a discrete choice experiment (DCE), there is little on selecting which attributes to include. We present a case study in which a best-worst scaling case 1 (BWS-1) survey was used to guide attribute selection for a DCE. The case study’s context was the decision making of professionals around the choice of augmentative and alternative communication (AAC) systems for children with limited natural speech.
BWS-1 survey attributes were generated from literature reviews and focus groups. DCE attributes were selected from BWS-1 attributes. The selection criteria were: include mostly important attributes; create coherent descriptions of children and AAC systems; address the project’s research aims; have an appropriate respondent burden. Attributes’ importance was judged using BWS-1 relative importance scores.
The BWS-1 survey included 19 child and 18 AAC device/system attributes and was administered to N = 93 AAC professionals. Four child and five device/system attributes were selected for the DCE, administered to N = 155 AAC professionals.
In this case study BWS-1 results were useful in DCE attribute selection. Four recommendations are made for future studies: define selection criteria for DCE attributes a priori; consider the impact participant’s perspective will have on BWS-1 and DCE results; clearly define key terminology at the start of the study and refine it as the study progresses to reflect interim findings; BWS will be useful when there is little existing stated preference work on a topic and/or qualitative work is difficult.</description><subject>attribute development</subject><subject>attribute selection</subject><subject>Attributes</subject><subject>Augmentative and alternative communication</subject><subject>best-worst scaling</subject><subject>Case studies</subject><subject>Children</subject><subject>Children & youth</subject><subject>Decision making</subject><subject>Discrete choice</subject><subject>discrete choice experiment</subject><subject>Discrete element method</subject><subject>Literature reviews</subject><subject>methodology</subject><subject>Polls & surveys</subject><subject>Qualitative research</subject><subject>Selection criteria</subject><subject>Speech</subject><subject>Terminology</subject><issn>1098-3015</issn><issn>1524-4733</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>7QJ</sourceid><recordid>eNp9kEtr3DAURkVpaV79A10EQzfZeKKXLRuySaaTBwS6mJTuKvS4bmU81kSSh-TfV2bSLLLISuLTuZdPB6GvBC8IJvV5v-h3alhQTOdggWn1AR2SivKSC8Y-5jtum5JhUh2goxh7jHHNaPUZHTDWcMxZfYh-X6YUnJ4SFGsYwCTnx6LzoVDFdxdNgPyw_OudgWL1tIXgNjCm4m40Pmx9UMmNfzJ6BTGVv3yIqVgbNczhego7eD5Bnzo1RPjych6jn9erh-Vtef_j5m55eV8aTptUsspUhmgtLKFtSwGrrqFWcKqtUZ3W2upGdIJzYTTtNGXEdsTWbS2YbStVs2N0tt-7Df5xym3kJreHYVAj-ClKWhHStKIVTUa_vUF7P4Uxt5spwUkjOM4U3VMm-BgDdHKb_67CsyRYzvZlL2f7crY_Z9l-Hjp9WT3pDdjXkf-6M3CxByC72DkIMhoHowHrQnYvrXfv7f8H-J-WPA</recordid><startdate>202104</startdate><enddate>202104</enddate><creator>Webb, Edward J.D.</creator><creator>Meads, David</creator><creator>Lynch, Yvonne</creator><creator>Judge, Simon</creator><creator>Randall, Nicola</creator><creator>Goldbart, Juliet</creator><creator>Meredith, Stuart</creator><creator>Moulam, Liz</creator><creator>Hess, Stephane</creator><creator>Murray, Janice</creator><general>Elsevier Inc</general><general>Elsevier Science Ltd</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QJ</scope><scope>7X8</scope></search><sort><creationdate>202104</creationdate><title>Attribute Selection for a Discrete Choice Experiment Incorporating a Best-Worst Scaling Survey</title><author>Webb, Edward J.D. ; Meads, David ; Lynch, Yvonne ; Judge, Simon ; Randall, Nicola ; Goldbart, Juliet ; Meredith, Stuart ; Moulam, Liz ; Hess, Stephane ; Murray, Janice</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c428t-35c5c1bb7d12992e0af82d742bdcafbbbdb87f7447cb2fb231df1d69673d95a63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>attribute development</topic><topic>attribute selection</topic><topic>Attributes</topic><topic>Augmentative and alternative communication</topic><topic>best-worst scaling</topic><topic>Case studies</topic><topic>Children</topic><topic>Children & youth</topic><topic>Decision making</topic><topic>Discrete choice</topic><topic>discrete choice experiment</topic><topic>Discrete element method</topic><topic>Literature reviews</topic><topic>methodology</topic><topic>Polls & surveys</topic><topic>Qualitative research</topic><topic>Selection criteria</topic><topic>Speech</topic><topic>Terminology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Webb, Edward J.D.</creatorcontrib><creatorcontrib>Meads, David</creatorcontrib><creatorcontrib>Lynch, Yvonne</creatorcontrib><creatorcontrib>Judge, Simon</creatorcontrib><creatorcontrib>Randall, Nicola</creatorcontrib><creatorcontrib>Goldbart, Juliet</creatorcontrib><creatorcontrib>Meredith, Stuart</creatorcontrib><creatorcontrib>Moulam, Liz</creatorcontrib><creatorcontrib>Hess, Stephane</creatorcontrib><creatorcontrib>Murray, Janice</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>MEDLINE - Academic</collection><jtitle>Value in health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Webb, Edward J.D.</au><au>Meads, David</au><au>Lynch, Yvonne</au><au>Judge, Simon</au><au>Randall, Nicola</au><au>Goldbart, Juliet</au><au>Meredith, Stuart</au><au>Moulam, Liz</au><au>Hess, Stephane</au><au>Murray, Janice</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Attribute Selection for a Discrete Choice Experiment Incorporating a Best-Worst Scaling Survey</atitle><jtitle>Value in health</jtitle><addtitle>Value Health</addtitle><date>2021-04</date><risdate>2021</risdate><volume>24</volume><issue>4</issue><spage>575</spage><epage>584</epage><pages>575-584</pages><issn>1098-3015</issn><eissn>1524-4733</eissn><abstract>Although literature exists on using qualitative methods to generate potential attributes for a discrete choice experiment (DCE), there is little on selecting which attributes to include. We present a case study in which a best-worst scaling case 1 (BWS-1) survey was used to guide attribute selection for a DCE. The case study’s context was the decision making of professionals around the choice of augmentative and alternative communication (AAC) systems for children with limited natural speech.
BWS-1 survey attributes were generated from literature reviews and focus groups. DCE attributes were selected from BWS-1 attributes. The selection criteria were: include mostly important attributes; create coherent descriptions of children and AAC systems; address the project’s research aims; have an appropriate respondent burden. Attributes’ importance was judged using BWS-1 relative importance scores.
The BWS-1 survey included 19 child and 18 AAC device/system attributes and was administered to N = 93 AAC professionals. Four child and five device/system attributes were selected for the DCE, administered to N = 155 AAC professionals.
In this case study BWS-1 results were useful in DCE attribute selection. Four recommendations are made for future studies: define selection criteria for DCE attributes a priori; consider the impact participant’s perspective will have on BWS-1 and DCE results; clearly define key terminology at the start of the study and refine it as the study progresses to reflect interim findings; BWS will be useful when there is little existing stated preference work on a topic and/or qualitative work is difficult.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>33840436</pmid><doi>10.1016/j.jval.2020.10.025</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1098-3015 |
ispartof | Value in health, 2021-04, Vol.24 (4), p.575-584 |
issn | 1098-3015 1524-4733 |
language | eng |
recordid | cdi_proquest_miscellaneous_2511897978 |
source | Elsevier ScienceDirect Journals Complete; Applied Social Sciences Index & Abstracts (ASSIA); EZB-FREE-00999 freely available EZB journals |
subjects | attribute development attribute selection Attributes Augmentative and alternative communication best-worst scaling Case studies Children Children & youth Decision making Discrete choice discrete choice experiment Discrete element method Literature reviews methodology Polls & surveys Qualitative research Selection criteria Speech Terminology |
title | Attribute Selection for a Discrete Choice Experiment Incorporating a Best-Worst Scaling Survey |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T21%3A03%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Attribute%20Selection%20for%20a%20Discrete%20Choice%20Experiment%20Incorporating%20a%20Best-Worst%20Scaling%20Survey&rft.jtitle=Value%20in%20health&rft.au=Webb,%20Edward%20J.D.&rft.date=2021-04&rft.volume=24&rft.issue=4&rft.spage=575&rft.epage=584&rft.pages=575-584&rft.issn=1098-3015&rft.eissn=1524-4733&rft_id=info:doi/10.1016/j.jval.2020.10.025&rft_dat=%3Cproquest_cross%3E2511897978%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2517418740&rft_id=info:pmid/33840436&rft_els_id=S1098301520345125&rfr_iscdi=true |