Mapping the Cardiometabolic Patient Experience and Self-Care Behaviors to Inform Design, Implementation, and Persistent Use of Digital Health Care Solutions: Mixed Methods Study

Cardiometabolic conditions including acute coronary syndrome (ACS) and type 2 diabetes (T2D) require comprehensive care and patient engagement in self-care behaviors, and the drivers of those behaviors at the individual and health system level are still poorly understood. We aim to gain insights int...

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Published inJMIR formative research Vol. 8; p. e43683
Main Authors Liska, Jan, Mical, Marie, Maillard, Christophe, Dessapt, Cécile, Bendig, Europa, Mai, Daniel, Piette, John D, De Geest, Sabina, Fontaine, Guillaume
Format Journal Article
LanguageEnglish
Published Canada JMIR Publications 01.01.2024
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Summary:Cardiometabolic conditions including acute coronary syndrome (ACS) and type 2 diabetes (T2D) require comprehensive care and patient engagement in self-care behaviors, and the drivers of those behaviors at the individual and health system level are still poorly understood. We aim to gain insights into self-care behaviors of individuals with cardiometabolic conditions. A convenience sample of 98 adult patients with ACS and T2D was recruited in the United States, Germany, and Taiwan to participate in a mixed methods study using ethnographic methods. All participants completed 7-day web-based diaries tracking their level of engagement, and 48 completed 90-minute web-based semistructured interviews between February 4, 2021, and March 27, 2021, focusing on themes including moments of engagement. Qualitative analysis identified factors influencing self-care practices and a Patient Mind States Model prototype. Patient reports indicate that many patients feel social pressure to adhere to treatment. Patients' experience can be understood within 5 categories defined in terms of their degree of engagement and adherence ("ignoring," "struggling," "juggling," "controlling," and "reframing"). For people living with ACS and T2D, the self-care journey is defined by patterns of patient experiences, which can identify areas that tailored digital health care interventions may play a meaningful role.
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ISSN:2561-326X
2561-326X
DOI:10.2196/43683