Drivers and Barriers to Acceptance of Web-Based Aftercare of Patients in Inpatient Routine Care: A Cross-Sectional Survey

Abstract

BackgroundWeb-based aftercare can help to stabilize treatment effects and support transition after inpatient treatment, yet uptake by patients seems limited in routine care and little is known about the mechanisms of adoption and implementation.ObjectiveThe aim of this study was to (1) determine acceptance of Web-based aftercare and (2) explore its drivers and barriers in different subgroups of a mixed inpatient sample.MethodIn a cross-sectional design, 38.3% (374/977) of the inpatients from a broad spectrum of diagnostic groups (psychosomatic, cardiologic, orthopedic, pediatric, and substance-related disorders) filled out a self-administered questionnaire prior to discharge. Drivers and barriers to patients’ acceptance of Web-based aftercare were examined based on an extension to the “unified theory of acceptance and use of technology” (UTAUT). In total, 16.7% (59/353) of the participants indicated prior use of eHealth interventions.ResultsAcceptance (min 1, max 5) was low (mean 2.56, SD 1.22) and differed between diagnostic groups (Welch F4,133.10 =7.77, P<.001), with highest acceptance in adolescent patients (mean 3.46, SD 1.42). Acceptance was significantly predicted by 3 UTAUT predictors: social influence (beta=.39, P<.001), performance expectancy (beta=.31, P<.001), and effort expectancy (beta=.22, P<.001). Furthermore, stress due to permanent availability (beta=−.09, P=.01) was negatively associated with acceptance.ConclusionThis study demonstrated a limited acceptance of Web-based aftercare in inpatients. Expectations, social environment’s attitude, and negative experience with permanent availability influence eHealth acceptance. Improving implementation, therefore, means increasing eHealth experience and literacy and facilitating positive attitudes in patients and health professionals through education and reduction of misconceptions about effectiveness or usability.

Evaluating clinicians’ user experience and acceptability of LearnTB, a smartphone application for tuberculosis in India

“…Furthermore, studies have been largely concentrated in the western hemisphere: Canada, United States of America and Europe (18). Amongst studies evaluating factors influencing mHealth adoption, the Technology Acceptance Model (TAM) has been used with different groups of health care professionals, including doctors and nurses, university faculty members, university students, nursing home residents and inpatient diagnostic groups (29)(30)(31)(32)(33).…”

Does self-help increase rates of help seeking for student mental health problems by minimizing stigma as a barrier?

“…Previous research suggests that variables indicated in the Theory of Planned Behavior 21 are predictive of intentions to use online self-help including normative beliefs, attitudes, and self-efficacy. 22,23 Thus, we Does self-help minimize stigma? 6 predicted that lower self-efficacy, attitudes, knowledge, and normative beliefs regarding selfhelp would all relate to lower intentions to use self-help.…”

Feasibility and Effects of Digital Interventions to Support People in Recovery From Substance Use Disorders: Systematic Review (Preprint)

“…One paper [33] reports on a survey about the general acceptance of different kinds of digital aftercare interventions among inpatients. …”