The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Patient Involvement With Home-Based Exercise Programs: Can Connected Health Interventions Influence Adherence?
Open accessAbstract
Adherence to home exercise in rehabilitation is a significant problem, with estimates of nonadherence as high as 50%, potentially having a detrimental effect on clinical outcomes. In this viewpoint, we discuss the many reasons why patients may not adhere to a prescribed exercise program and explore how connected health technologies have the ability to offer numerous interventions to enhance adherence; however, it is hard to judge the efficacy of these interventions without a robust measurement tool. We highlight how well-designed connected health technologies, such as the use of mobile devices, including mobile phones and tablets, as well as inertial measurement units, provide us with the opportunity to better support the patient and clinician, with a data-driven approach that incorporates features designed to increase adherence to exercise such as coaching, self-monitoring and education, as well as remotely monitor adherence rates more objectively.
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Cites
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Cited by
Measurement, determinants, barriers, and interventions for exercise adherence: a scoping review
Mahmood, A., Nayak, P., Deshmukh, A., English, C., N, M., Solomon M, J., & B, U. (2023) · Journal of Bodywork and Movement Therapies · doi:10.1016/j.jbmt.2022.09.014 · Cited by 60
Cui, D., Janela, D., Costa, F., Molinos, M., Areias, A. C., Moulder, R. G., Scheer, J. K., Bento, V., Cohen, S. P., Yanamadala, V., et al. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00870-3 · Cited by 60
Kim, H., Lee, S.-H., Cho, N.-B., You, H., Choi, T., & Kim, J. (2020) · JMIR mHealth and uHealth · doi:10.2196/19585 · Cited by 42
“The themes selected were important app quality indicators according to the experiences of the participants: app acceptability (49; 51), training program utilization (24; 16), emotional responses (22; 37), and learning experience (12; 28).”
Janela, D., Costa, F., Molinos, M., Moulder, R. G., Lains, J., Francisco, G. E., Bento, V., Cohen, S. P., & Correia, F. D. (2022) · Journal of Pain Research · doi:10.2147/jpr.s343308 · Cited by 33
“22,45,54,55,93,94 Not surprisingly, high compliance was correlated with better recovery (in both disability and pain), reinforcing the need to formally address patient engagement in all programs.”
BackgroundCarneiro, L., Rosenbaum, S., Ward, P. B., Clemente, F. M., Ramirez-Campillo, R., Monteiro-Júnior, R. S., Martins, A., & Afonso, J. (2022) · Brazilian Journal of Psychiatry · doi:10.1590/1516-4446-2021-2026 · Cited by 23
Metadata
- Authors
- Argent, R., Daly, A., & Caulfield, B.
- Venue
- JMIR mHealth and uHealth
- Publisher
- JMIR Publications Inc.
- Published
- 2018-03-01
- Volume
- 6
- Issue
- 3
- Pages
- e47
- ISSN
- 2291-5222 (ISSN-L)
- OpenAlex
- W2790465659
- Cited by
- 322
- References
- 55
- FWCI
- 28.23
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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