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Using discrete choice experiments to inform the design of complex interventions

BACKGROUND: Complex health interventions must incorporate user preferences to maximize their potential effectiveness. Discrete choice experiments (DCEs) quantify the strength of user preferences and identify preference heterogeneity across users. We present the process of using a DCE to supplement c...

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Autores principales: Terris-Prestholt, Fern, Neke, Nyasule, Grund, Jonathan M., Plotkin, Marya, Kuringe, Evodius, Osaki, Haika, Ong, Jason J., Tucker, Joseph D., Mshana, Gerry, Mahler, Hally, Weiss, Helen A., Wambura, Mwita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399844/
https://www.ncbi.nlm.nih.gov/pubmed/30832718
http://dx.doi.org/10.1186/s13063-019-3186-x
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author Terris-Prestholt, Fern
Neke, Nyasule
Grund, Jonathan M.
Plotkin, Marya
Kuringe, Evodius
Osaki, Haika
Ong, Jason J.
Tucker, Joseph D.
Mshana, Gerry
Mahler, Hally
Weiss, Helen A.
Wambura, Mwita
author_facet Terris-Prestholt, Fern
Neke, Nyasule
Grund, Jonathan M.
Plotkin, Marya
Kuringe, Evodius
Osaki, Haika
Ong, Jason J.
Tucker, Joseph D.
Mshana, Gerry
Mahler, Hally
Weiss, Helen A.
Wambura, Mwita
author_sort Terris-Prestholt, Fern
collection PubMed
description BACKGROUND: Complex health interventions must incorporate user preferences to maximize their potential effectiveness. Discrete choice experiments (DCEs) quantify the strength of user preferences and identify preference heterogeneity across users. We present the process of using a DCE to supplement conventional qualitative formative research in the design of a demand creation intervention for voluntary medical male circumcision (VMMC) to prevent HIV in Tanzania. METHODS: The VMMC intervention was designed within a 3-month formative phase. In-depth interviews (n = 30) and participatory group discussions (n = 20) sought to identify broad setting-specific barriers to and facilitators of VMMC among adult men. Qualitative results informed the DCE development, identifying the role of female partners, service providers’ attitudes and social stigma. A DCE among 325 men in Njombe and Tabora, Tanzania, subsequently measured preferences for modifiable VMMC service characteristics. The final VMMC demand creation intervention design drew jointly on the qualitative and DCE findings. RESULTS: While the qualitative research informed the community mobilization intervention, the DCE guided the specific VMMC service configuration. The significant positive utilities (u) for availability of partner counselling (u = 0.43, p < 0.01) and age-separated waiting areas (u = 0.21, p < 0.05) led to the provision of community information booths for partners and provision of age-separated waiting areas. The strong disutility of female healthcare providers (u = − 0.24, p < 0.01) led to re-training all providers on client-friendliness. CONCLUSION: This is, to our knowledge, the first study documenting how user preferences from DCEs can directly inform the design of a complex intervention. The use of DCEs as formative research may help increase user uptake and adherence to complex interventions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13063-019-3186-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-63998442019-03-13 Using discrete choice experiments to inform the design of complex interventions Terris-Prestholt, Fern Neke, Nyasule Grund, Jonathan M. Plotkin, Marya Kuringe, Evodius Osaki, Haika Ong, Jason J. Tucker, Joseph D. Mshana, Gerry Mahler, Hally Weiss, Helen A. Wambura, Mwita Trials Methodology BACKGROUND: Complex health interventions must incorporate user preferences to maximize their potential effectiveness. Discrete choice experiments (DCEs) quantify the strength of user preferences and identify preference heterogeneity across users. We present the process of using a DCE to supplement conventional qualitative formative research in the design of a demand creation intervention for voluntary medical male circumcision (VMMC) to prevent HIV in Tanzania. METHODS: The VMMC intervention was designed within a 3-month formative phase. In-depth interviews (n = 30) and participatory group discussions (n = 20) sought to identify broad setting-specific barriers to and facilitators of VMMC among adult men. Qualitative results informed the DCE development, identifying the role of female partners, service providers’ attitudes and social stigma. A DCE among 325 men in Njombe and Tabora, Tanzania, subsequently measured preferences for modifiable VMMC service characteristics. The final VMMC demand creation intervention design drew jointly on the qualitative and DCE findings. RESULTS: While the qualitative research informed the community mobilization intervention, the DCE guided the specific VMMC service configuration. The significant positive utilities (u) for availability of partner counselling (u = 0.43, p < 0.01) and age-separated waiting areas (u = 0.21, p < 0.05) led to the provision of community information booths for partners and provision of age-separated waiting areas. The strong disutility of female healthcare providers (u = − 0.24, p < 0.01) led to re-training all providers on client-friendliness. CONCLUSION: This is, to our knowledge, the first study documenting how user preferences from DCEs can directly inform the design of a complex intervention. The use of DCEs as formative research may help increase user uptake and adherence to complex interventions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13063-019-3186-x) contains supplementary material, which is available to authorized users. BioMed Central 2019-03-04 /pmc/articles/PMC6399844/ /pubmed/30832718 http://dx.doi.org/10.1186/s13063-019-3186-x Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Terris-Prestholt, Fern
Neke, Nyasule
Grund, Jonathan M.
Plotkin, Marya
Kuringe, Evodius
Osaki, Haika
Ong, Jason J.
Tucker, Joseph D.
Mshana, Gerry
Mahler, Hally
Weiss, Helen A.
Wambura, Mwita
Using discrete choice experiments to inform the design of complex interventions
title Using discrete choice experiments to inform the design of complex interventions
title_full Using discrete choice experiments to inform the design of complex interventions
title_fullStr Using discrete choice experiments to inform the design of complex interventions
title_full_unstemmed Using discrete choice experiments to inform the design of complex interventions
title_short Using discrete choice experiments to inform the design of complex interventions
title_sort using discrete choice experiments to inform the design of complex interventions
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399844/
https://www.ncbi.nlm.nih.gov/pubmed/30832718
http://dx.doi.org/10.1186/s13063-019-3186-x
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