ArticleTranslational behavioral medicine2025
Progressing implementation of behavior change frameworks for digital health interventions: challenges and ways forward.
Article in Translational behavioral medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
backgroundNew behavior change theories, models, and frameworks (TMFs) to support digital behavior change interventions have been called for and are emerging, but low reported usage impedes progress in the field. AIMS AND
objectivesThis study aims to highlight key barriers to the implementation of digital-focused TMFs and provide recommendations to mitigate these barriers.
methodsThe adoption of seven novel TMFs designed for digital behavior change interventions was analyzed based on the number of citations and the number of interventions developed using the TMFs, in comparison with the longer-established behavior change wheel (BCW) framework.
resultsThe uptake of the novel TMFs appears slow compared to the well-established and commonly used BCW framework, even when accounting for the recentness of the novel TMFs. Potential barriers to adoption include a lack of awareness, insufficient empirical evidence, and challenges in operationalizing these models. Researchers creating these TMFs could mitigate these barriers by improving their design (e.g. by making them more adaptable) and reporting and developing, and testing interventions based on their TMFs to start building an evidence base. CONCLUSIONS AND FUTURE RESEARCH: New TMFs with a focus on digital technologies have the potential to improve the efficacy and outcomes of digital behavior-change interventions, but their accessibility, evidence base, and reporting must improve to facilitate their adoption in intervention design. Further review work comparing the novel TMFs with traditional frameworks and a repository to guide researchers in framework selection could also help with faster uptake.
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