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Identifying the impact of social influences in health-related discrete choice experiments
Several disciplines, among them health, sociology, and economics, provide strong evidence that social context is important to individual choices. It is therefore surprising that relatively little research has been focused on integrating the effect of social influence into choice models, especially g...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581381/ https://www.ncbi.nlm.nih.gov/pubmed/36260642 http://dx.doi.org/10.1371/journal.pone.0276141 |
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author | de Bekker-Grob, Esther W. Howard, Kirsten Swait, Joffre |
author_facet | de Bekker-Grob, Esther W. Howard, Kirsten Swait, Joffre |
author_sort | de Bekker-Grob, Esther W. |
collection | PubMed |
description | Several disciplines, among them health, sociology, and economics, provide strong evidence that social context is important to individual choices. It is therefore surprising that relatively little research has been focused on integrating the effect of social influence into choice models, especially given the importance of such choices in healthcare. This study developed and empirically tested a choice model that accounts for social network influences in a discrete choice experiment (DCE). We focused on maternal choices for childhood vaccination in Australia, and used an econometric choice model that explicitly 1) incorporated vaccine schedule characteristics, benefits and costs, and 2) represented up to ten different identifiable key influencer types (e.g., partner, parents, friends, healthcare professionals, inter alia), allowing for the attribution of directional importance of each influencer on the gravid woman’s decision to adhere to or reject childhood vaccination. Pregnant women (N = 604) aged 18 years and older recruited from an online panel completed a survey, including a DCE and questions about key influencers. A two-class ordered latent class model was conducted to analyse the DCE data, which assumes that the underlying latent driver (in our case the WHO vaccine hesitancy scale) is ordered, to give a practical interpretation of the meaning of the classes. When the choice model considered both childhood vaccination attributes and key influencers, a very high model fit was reached. The impact of key influencers on maternal choice for childhood vaccination was massive compared to the impact of childhood vaccination attributes. The marginal impact differed between key influencers. Our DCE study showed that the maternal decision for childhood vaccination was essentially almost completely socially driven, suggesting that the potential impact of social network influences can and should be considered in health-related DCEs, particular those where there are likely to be strong underlying social norms dictating decision maker behaviour. |
format | Online Article Text |
id | pubmed-9581381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-95813812022-10-20 Identifying the impact of social influences in health-related discrete choice experiments de Bekker-Grob, Esther W. Howard, Kirsten Swait, Joffre PLoS One Research Article Several disciplines, among them health, sociology, and economics, provide strong evidence that social context is important to individual choices. It is therefore surprising that relatively little research has been focused on integrating the effect of social influence into choice models, especially given the importance of such choices in healthcare. This study developed and empirically tested a choice model that accounts for social network influences in a discrete choice experiment (DCE). We focused on maternal choices for childhood vaccination in Australia, and used an econometric choice model that explicitly 1) incorporated vaccine schedule characteristics, benefits and costs, and 2) represented up to ten different identifiable key influencer types (e.g., partner, parents, friends, healthcare professionals, inter alia), allowing for the attribution of directional importance of each influencer on the gravid woman’s decision to adhere to or reject childhood vaccination. Pregnant women (N = 604) aged 18 years and older recruited from an online panel completed a survey, including a DCE and questions about key influencers. A two-class ordered latent class model was conducted to analyse the DCE data, which assumes that the underlying latent driver (in our case the WHO vaccine hesitancy scale) is ordered, to give a practical interpretation of the meaning of the classes. When the choice model considered both childhood vaccination attributes and key influencers, a very high model fit was reached. The impact of key influencers on maternal choice for childhood vaccination was massive compared to the impact of childhood vaccination attributes. The marginal impact differed between key influencers. Our DCE study showed that the maternal decision for childhood vaccination was essentially almost completely socially driven, suggesting that the potential impact of social network influences can and should be considered in health-related DCEs, particular those where there are likely to be strong underlying social norms dictating decision maker behaviour. Public Library of Science 2022-10-19 /pmc/articles/PMC9581381/ /pubmed/36260642 http://dx.doi.org/10.1371/journal.pone.0276141 Text en © 2022 de Bekker-Grob et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article de Bekker-Grob, Esther W. Howard, Kirsten Swait, Joffre Identifying the impact of social influences in health-related discrete choice experiments |
title | Identifying the impact of social influences in health-related discrete choice experiments |
title_full | Identifying the impact of social influences in health-related discrete choice experiments |
title_fullStr | Identifying the impact of social influences in health-related discrete choice experiments |
title_full_unstemmed | Identifying the impact of social influences in health-related discrete choice experiments |
title_short | Identifying the impact of social influences in health-related discrete choice experiments |
title_sort | identifying the impact of social influences in health-related discrete choice experiments |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581381/ https://www.ncbi.nlm.nih.gov/pubmed/36260642 http://dx.doi.org/10.1371/journal.pone.0276141 |
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