Determining Acceptance of e-Mental Health Interventions in Digital Psychodiabetology Using a Quantitative Web-Based Survey: Cross-sectional Study (Preprint)
Authors: Damerau Mirjam , Teufel Martin , Musche Venja , Dinse Hannah , Schweda Adam , Beckord Jil , Steinbach Jasmin , Schmidt Kira , Skoda Eva-Maria , Bäuerle Alexander 
Published: January 2021

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 (<i>P</i>&lt;.001). In an extended UTAUT regression model (UTAUT predictors plus sociodemographics and mental health variables), distress (β=.11; <i>P</i>=.03) as well as the UTAUT predictors <i>performance expectancy</i> (β=.50; <i>P</i>&lt;.001), <i>effort expectancy</i> (β=.15; <i>P</i>=.001), and <i>social influence</i> (β=.28; <i>P</i>&lt;.001) significantly predicted acceptance. The comparison between an extended UTAUT regression model (13 predictors) and the UTAUT-only regression model (<i>performance expectancy</i>, <i>effort expectancy</i>, <i>social influence</i>) revealed no significant difference in explained variance (<i>F</i><sub>10,244</sub>=1.567; <i>P=</i>.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.