Defining Effective Engagement For Enhancing Cancer Patients' Well-being with Mobile Digital Behavior Change Interventions
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arXiv
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| Auteurs principaux: | , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866913321949593600 |
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| author | Lisowska, Aneta Wilk, Szymon Locati, Laura Rizzo, Mimma Sacchi, Lucia Quaglini, Silvana Terzaghi, Matteo Tibollo, Valentina Peleg, Mor |
| author_facet | Lisowska, Aneta Wilk, Szymon Locati, Laura Rizzo, Mimma Sacchi, Lucia Quaglini, Silvana Terzaghi, Matteo Tibollo, Valentina Peleg, Mor |
| contents | Digital Behavior Change Interventions (DBCIs) are supporting development of new health behaviors. Evaluating their effectiveness is crucial for their improvement and understanding of success factors. However, comprehensive guidance for developers, particularly in small-scale studies with ethical constraints, is limited. Building on the CAPABLE project, this study aims to define effective engagement with DBCIs for supporting cancer patients in enhancing their quality of life. We identify metrics for measuring engagement, explore the interest of both patients and clinicians in DBCIs, and propose hypotheses for assessing the impact of DBCIs in such contexts. Our findings suggest that clinician prescriptions significantly increase sustained engagement with mobile DBCIs. In addition, while one weekly engagement with a DBCI is sufficient to maintain well-being, transitioning from extrinsic to intrinsic motivation may require a higher level of engagement. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_12007 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Defining Effective Engagement For Enhancing Cancer Patients' Well-being with Mobile Digital Behavior Change Interventions Lisowska, Aneta Wilk, Szymon Locati, Laura Rizzo, Mimma Sacchi, Lucia Quaglini, Silvana Terzaghi, Matteo Tibollo, Valentina Peleg, Mor Human-Computer Interaction Machine Learning Digital Behavior Change Interventions (DBCIs) are supporting development of new health behaviors. Evaluating their effectiveness is crucial for their improvement and understanding of success factors. However, comprehensive guidance for developers, particularly in small-scale studies with ethical constraints, is limited. Building on the CAPABLE project, this study aims to define effective engagement with DBCIs for supporting cancer patients in enhancing their quality of life. We identify metrics for measuring engagement, explore the interest of both patients and clinicians in DBCIs, and propose hypotheses for assessing the impact of DBCIs in such contexts. Our findings suggest that clinician prescriptions significantly increase sustained engagement with mobile DBCIs. In addition, while one weekly engagement with a DBCI is sufficient to maintain well-being, transitioning from extrinsic to intrinsic motivation may require a higher level of engagement. |
| title | Defining Effective Engagement For Enhancing Cancer Patients' Well-being with Mobile Digital Behavior Change Interventions |
| topic | Human-Computer Interaction Machine Learning |
| url | https://arxiv.org/abs/2403.12007 |