Determining the Acceptance of Digital Cardiac Rehabilitation and Its Influencing Factors among Patients Affected by Cardiac Diseases

被引:10
|
作者
Baeuerle, Alexander [1 ,2 ]
Mallien, Charlotta [1 ,2 ]
Rassaf, Tienush [3 ]
Jahre, Lisa [1 ,2 ]
Rammos, Christos [3 ]
Skoda, Eva-Maria [1 ,2 ]
Teufel, Martin [1 ,2 ]
Lortz, Julia [3 ]
机构
[1] Univ Duisburg Essen, LVR Univ Hosp Essen, Clin Psychosomat Med & Psychotherapy, D-45147 Essen, Germany
[2] Univ Duisburg Essen, Ctr Translat Neuroand Behav Sci C TNBS, D-45147 Essen, Germany
[3] Univ Duisburg Essen, West German Heart & Vasc Ctr Essen, Dept Cardiol & Vasc Med, D-45147 Essen, Germany
关键词
UTAUT; mHealth; cardiac disease; internet; rehabilitation; MYOCARDIAL-INFARCTION; USER ACCEPTANCE; GLOBAL BURDEN; TELEREHABILITATION; TECHNOLOGY; ANXIETY; STRESS; LIFE;
D O I
10.3390/jcdd10040174
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Cardiac diseases are a major global health issue with an increasing prevalence of affected people. Rehabilitation following cardiac events is underutilized, despite its proven effectiveness. Digital interventions might present a useful addition to traditional cardiac rehabilitation. Aims: This study aims to assess the acceptance of mobile health (mHealth) cardiac rehabilitation and to investigate the underlying factors of acceptance in patients with ischemic heart disease and congestive heart failure. Methods: A cross-sectional study was conducted from November 2021 to September 2022 with N = 290 patients. Sociodemographic, medical, and eHealth-related data were assessed. The Unified Theory of Acceptance and Use of Technology (UTAUT) was applied. Group differences in acceptance were examined and a multiple hierarchical regression analysis was conducted. Results: The overall acceptance of mHealth cardiac rehabilitation was high (M = 4.05, SD = 0.93). Individuals with mental illness reported significantly higher acceptance (t(288) = 3.15, p(adj) = 0.007, d = 0.43). Depressive symptoms (beta = 0.34, p < 0.001); digital confidence (beta = 0.19, p = 0.003); and the UTAUT predictors of performance expectancy (beta = 0.34, p < 0.001), effort expectancy (beta = 0.34, p < 0.001), and social influence (beta = 0.26, p < 0.001) significantly predicted acceptance. The extended UTAUT model explained 69.5% of the variance in acceptance. Conclusions: As acceptance is associated with the actual use of mHealth, the high level of acceptance found in this study is a promising basis for the future implementation of innovative mHealth offers in cardiac rehabilitation.
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页数:11
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