@Article{info:doi/10.2196/27436,
author="Damerau, Mirjam
and Teufel, Martin
and Musche, Venja
and Dinse, Hannah
and Schweda, Adam
and Beckord, Jil
and Steinbach, Jasmin
and Schmidt, Kira
and Skoda, Eva-Maria
and B{\"a}uerle, Alexander",
title="Determining Acceptance of e-Mental Health Interventions in Digital Psychodiabetology Using a Quantitative Web-Based Survey: Cross-sectional Study",
journal="JMIR Form Res",
year="2021",
month="Jul",
day="30",
volume="5",
number="7",
pages="e27436",
keywords="e-mental health; acceptance; UTAUT; mental health; diabetes; e-mental health intervention; psychodiabetology",
abstract="Background: Diabetes is a very common chronic disease that exerts massive physiological and psychological burdens on patients. The digitalization of mental health care has generated effective e-mental health approaches, which offer an indubitable practical value for patient treatment. However, before implementing and optimizing e-mental health tools, their acceptance and underlying barriers and resources should be first determined for developing and establishing effective patient-oriented interventions. Objective: This study aims to assess the acceptance of e-mental health interventions among patients with diabetes and explore its underlying barriers and resources. Methods: A cross-sectional study was conducted in Germany from April 9, 2020, to June 15, 2020, through a web-based survey for which patients were recruited via web-based diabetes channels. The eligibility requirements were adult age (18 years or older), a good command of the German language, internet access, and a diagnosis of diabetes. Acceptance was measured using a modified questionnaire, which was based on the well-established Unified Theory of Acceptance and Use of Technology (UTAUT) and assessed health-related internet use, acceptance of e-mental health interventions, and its barriers and resources. Mental health was measured using validated and established instruments, namely the Generalized Anxiety Disorder Scale-7, Patient Health Questionnaire-2, and Distress Thermometer. In addition, sociodemographic and medical data regarding diabetes were collected. Results: Of the 340 participants who started the survey, 261 (76.8{\%}) completed it and the final sample comprised 258 participants with complete data sets. The acceptance of e-mental health interventions in patients with diabetes was overall moderate (mean 3.02, SD 1.14). Gender and having a mental disorder had a significant influence on acceptance (P<.001). In an extended UTAUT regression model (UTAUT predictors plus sociodemographics and mental health variables), distress ($\beta$=.11; P=.03) as well as the UTAUT predictors performance expectancy ($\beta$=.50; P<.001), effort expectancy ($\beta$=.15; P=.001), and social influence ($\beta$=.28; P<.001) significantly predicted acceptance. The comparison between an extended UTAUT regression model (13 predictors) and the UTAUT-only regression model (performance expectancy, effort expectancy, social influence) revealed no significant difference in explained variance (F10,244=1.567; P=.12). Conclusions: This study supports the viability of the UTAUT model and its predictors in assessing the acceptance of e-mental health interventions among patients with diabetes. Three UTAUT predictors reached a notable amount of explained variance of 75{\%} in the acceptance, indicating that it is a very useful and efficient method for measuring e-mental health intervention acceptance in patients with diabetes. Owing to the close link between acceptance and use, acceptance-facilitating interventions focusing on these three UTAUT predictors should be fostered to bring forward the highly needed establishment of effective e-mental health interventions in psychodiabetology. ",
issn="2561-326X",
doi="10.2196/27436",
url="https://formative.jmir.org/2021/7/e27436",
url="https://doi.org/10.2196/27436",
url="http://www.ncbi.nlm.nih.gov/pubmed/34328429"
}