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Engaging Caregivers through mHealth to Support Chronic Care Patients

Michal T. Ruprecht et al.

E-Service Journal2023https://doi.org/10.2979/esj.00006article
AJG 1ABDC B
Weight
0.45

Abstract

ABSTRACT: As the U.S. population ages, the demand for long-term care services and support has increased, including those typically provided by informal caregivers. As a result of increased reliance on informal caregivers, caregiver burden is a growing concern, impacting the well-being of caregivers and patient outcomes. This paper explores the development, pilot, and evaluation of a caregiver engagement app designed to alleviate caregiver burden and enhance patient care in rural Michigan counties. Drawing on a multi-step approach, including key-informant interviews, empathy interviews, and focus group discussions, caregiver needs were identified and incorporated into the app’s design and interface. The app, genusConnect, provided caregivers with educational resources, care coordination tools, and communication features to support them and patient care. Pre-post intervention data indicated positive perceptions of the app’s usability and efficacy in reducing caregiver burden and social isolation. Despite these promising findings, challenges remain in addressing financial support for caregivers and expanding the generalizability of the app to accommodate diverse caregiver populations and patient conditions. Future research should focus on addressing these limitations and further developing the app to better support caregivers and improve patient outcomes.

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https://doi.org/https://doi.org/10.2979/esj.00006

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@article{michal2023,
  title        = {{Engaging Caregivers through mHealth to Support Chronic Care Patients}},
  author       = {Michal T. Ruprecht et al.},
  journal      = {E-Service Journal},
  year         = {2023},
  doi          = {https://doi.org/https://doi.org/10.2979/esj.00006},
}

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Evidence weight

0.45

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.26 × 0.4 = 0.10
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.