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Evaluating use of web-based interventions: an example of a Dutch sexual health intervention

With the current increase in web-based interventions, the question of how to measure, and consequently improve engagement in such interventions is gaining more importance. Modern day web analytics tools make it easy to monitor use of web-based interventions. However, in this article, we propose that...

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Detalles Bibliográficos
Autores principales: Metz, Gido, Roosjen, Hanneke, Zweers, Wessel, Crutzen, Rik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439511/
https://www.ncbi.nlm.nih.gov/pubmed/37596929
http://dx.doi.org/10.1093/heapro/daab190
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author Metz, Gido
Roosjen, Hanneke
Zweers, Wessel
Crutzen, Rik
author_facet Metz, Gido
Roosjen, Hanneke
Zweers, Wessel
Crutzen, Rik
author_sort Metz, Gido
collection PubMed
description With the current increase in web-based interventions, the question of how to measure, and consequently improve engagement in such interventions is gaining more importance. Modern day web analytics tools make it easy to monitor use of web-based interventions. However, in this article, we propose that it would be more meaningful to first examine how the developers envisioned the use of the intervention to establish behavior change (i.e. intended use), before looking into how the intervention is ultimately used with web analytics (i.e. actual use). Such an approach responds to the regularly expressed concern that behavioral interventions are often poorly described, leading to less meaningful evaluations as it is not clear what exactly is being evaluated. Using a page on chlamydia prevention (104 557 pageviews in 2020) from a Dutch sexual health intervention (Sense), we demonstrate the value of acyclic behavior change diagrams (ABCDs) as a method to visualize intended use of an intervention. ABCDs show at a glance how behavior change principles are applied in an intervention and target determinants of behavior. Based on this ABCD, we investigate actual use of the intervention, using web analytics tool Matomo. Despite being intended to stimulate STI-testing, only 14% of the 35 347 transfers from this page led to the STI-testing page and a high bounce rate (79%) and relatively high exit rate were reported (69%). Recommendations to further interpret the data are given. This real-life example demonstrates the potential of combining ABCDs and Matomo as methods to gain insight into use of web-based interventions.
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spelling pubmed-104395112023-08-20 Evaluating use of web-based interventions: an example of a Dutch sexual health intervention Metz, Gido Roosjen, Hanneke Zweers, Wessel Crutzen, Rik Health Promot Int Article With the current increase in web-based interventions, the question of how to measure, and consequently improve engagement in such interventions is gaining more importance. Modern day web analytics tools make it easy to monitor use of web-based interventions. However, in this article, we propose that it would be more meaningful to first examine how the developers envisioned the use of the intervention to establish behavior change (i.e. intended use), before looking into how the intervention is ultimately used with web analytics (i.e. actual use). Such an approach responds to the regularly expressed concern that behavioral interventions are often poorly described, leading to less meaningful evaluations as it is not clear what exactly is being evaluated. Using a page on chlamydia prevention (104 557 pageviews in 2020) from a Dutch sexual health intervention (Sense), we demonstrate the value of acyclic behavior change diagrams (ABCDs) as a method to visualize intended use of an intervention. ABCDs show at a glance how behavior change principles are applied in an intervention and target determinants of behavior. Based on this ABCD, we investigate actual use of the intervention, using web analytics tool Matomo. Despite being intended to stimulate STI-testing, only 14% of the 35 347 transfers from this page led to the STI-testing page and a high bounce rate (79%) and relatively high exit rate were reported (69%). Recommendations to further interpret the data are given. This real-life example demonstrates the potential of combining ABCDs and Matomo as methods to gain insight into use of web-based interventions. Oxford University Press 2021-11-22 /pmc/articles/PMC10439511/ /pubmed/37596929 http://dx.doi.org/10.1093/heapro/daab190 Text en © The Author(s) 2021. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
Metz, Gido
Roosjen, Hanneke
Zweers, Wessel
Crutzen, Rik
Evaluating use of web-based interventions: an example of a Dutch sexual health intervention
title Evaluating use of web-based interventions: an example of a Dutch sexual health intervention
title_full Evaluating use of web-based interventions: an example of a Dutch sexual health intervention
title_fullStr Evaluating use of web-based interventions: an example of a Dutch sexual health intervention
title_full_unstemmed Evaluating use of web-based interventions: an example of a Dutch sexual health intervention
title_short Evaluating use of web-based interventions: an example of a Dutch sexual health intervention
title_sort evaluating use of web-based interventions: an example of a dutch sexual health intervention
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439511/
https://www.ncbi.nlm.nih.gov/pubmed/37596929
http://dx.doi.org/10.1093/heapro/daab190
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