EHealth interventions can be effective in treating health problems. However, adoption in inpatient routine care seems limited. The present study therefore aimed to investigate barriers and facilitators to acceptance of eHealth interventions and of online aftercare in particular in health professionals of inpatient treatment. A total of 152 out of 287 health professionals of various professional groups in four inpatient rehabilitation facilities filled out a self-administered web-based questionnaire (response rate: 53%); 128 individuals were eligible for further data analysis. Acceptance and possible predictors were investigated with a complex research model based on the Unified Theory of Acceptance and Use of Technology. Acceptance of eHealth interventions was rather low (M = 2.47, SD = 0.98); however, acceptance of online aftercare was moderate (M = 3.08, SD = 0.96, t(127) = 8.22, p < .001), and eHealth literacy was elevated. Social influence, performance expectancy, and treatment-related internet and mobile use significantly predicted overall acceptance. No differences were found between professional and age groups. Although acceptance of eHealth interventions was limited in health professionals of inpatient treatment, moderate acceptance of online aftercare for work-related stress implies a basis for future implementation. Tailored eHealth education addressing misconceptions about inferiority and incongruity with conventional treatment considering the systemic aspect of acceptance formation are needed.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Mobile health applications (mHealth apps) may have the potential to promote self-management of people with multiple sclerosis (MS) in everyday life. However, the uptake of MS apps remains poor and little is known about the facilitators and barriers for their efficient utilization, such as technology acceptance. Objective: The aim of this study was to examine the acceptance of mHealth apps for disease-management in the sense of behavioral intentions to use and explore determinants of utilization among people with MS based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Methods: Participants for this Web-based cross-sectional study were recruited Germany-wide with the support of regional MS associations and self-help groups. To identify determinants of intention to use MS apps, a measure based on the UTAUT was adapted with four key determinants (performance-/effort-expectancy, social influence, facilitating conditions) and extended by Intolerance of Uncertainty (IU) and eHealth literacy. Potential influencing effects of both MS and computer self-efficacy as mediators and fatigue as a moderator were analyzed using Hayes' PROCESS macro for SPSS. Results: 98 participants (M age=47.03 years, SD=10.17; 67.3% female, 66/98) with moderate fatigue levels completed the survey. Although most participants (91.9%; 91/98) were daily smartphone users, almost two-thirds (63.3%, 62/98) reported no experience with MS apps. Overall, the acceptance was moderate on average (M=3.11, SD=1.31, min 1 max 5), with lower scores among persons with no experience (P=.04) and higher scores among current users (P<.001). In multiple regression analysis (R2=63% variance explained), performance expectancy (beta=.41) and social influence (beta=.33) were identified as significant predictors of acceptance (all P<.001). Computer self-efficacy was confirmed as a partial mediator in the relationship between IU and acceptance; (indirect effect: B=-.095, 95% CI-0.227,-0.01). Furthermore, a moderated mediation by computer self-efficacy was shown in the relationship between IU and behavioral intentions to use MS apps for low (95% CI -0.42,-0.01) and moderate levels (95% CI -0.27,-0.01) of fatigue. Conclusions: Overall, this exploratory pilot study indicates for the first time that positive expectations about the helpfulness for self-management purposes and social support might be important factors to be considered for improving the acceptance of MS apps among smartphone users with MS. However, given some inconsistent findings, especially regarding the role of effort expectancy and IU and self-efficacy, the conceptual model needs replication with a larger sample of people with MS, varying more in fatigue levels, and a longitudinal assessment of the actual usage of MS apps predicted by acceptance in the sense of behavioral intentions to use. Clinical Trial: not applicable

Mental disorders are characterized by a high likelihood of recurrence. Thus, aftercare and follow-up interventions aim to maintain treatment gains and to prevent relapse. Internet- and mobile-based interventions (IMIs) may represent promising instruments in tertiary prevention. This systematic review summarizes and evaluates the research on the efficacy of IMIs as aftercare or follow-up interventions for adults with mental health issues. A systematic database search (PsycInfo, MEDLINE, CENTRAL) was conducted and studies selected according to predefined eligibility criteria (RCTs, adult population, clinical symptoms/disorder, assessed with validated instruments, clinical-psychological intervention rationale, aftercare/follow-up intervention, web-/mobile-based, minimum follow-up measurement of three months, inclusion of a control group). Inspected outcomes were symptom severity, recurrence- and rehospitalization rates, functioning, quality of life and adherence to primary treatment.Systematic review registration: PROSPERO CRD42017055289. Sixteen RCTs met the inclusion criteria, covering trials on depression (n = 5), eating disorders (n = 4) and transdiagnostic interventions (n = 7). The majority of the interventions were based on Cognitive Behavioral Therapy (CBT) principles and were web-based (n = 11). Methodological quality of included studies was suboptimal. Limitations included attrition bias and non-specification of routine care co-interventions. IMIs yielded small to medium post-treatment effects for symptom severity (d = -0.08 - d = -0.45) in comparison to control groups. Best evidence base was found for symptom severity of depression and anxiety. Study results regarding recurrence and rehospitalization were inconsistent. There is some evidence, that IMIs are feasible instruments for maintaining treatment gains for some mental disorders. However, further high quality, large-scale trials are needed to expand research fields, improve adherence to and uptake of IMIs and facilitate implementation of effective interventions into routine care.

Background: Chronic stress is a major public health concern. Mobile health (mHealth) apps can help promote coping skills in daily life and prevent stress-related issues. However, little is known about the determinant factors of public acceptance of stress management in relation to preferences for psychological services.Objective: The aim of this survey study was to (1) assess determinant factors of public acceptance (behavioral use intention) of stress management apps based on an adapted and extended version of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and (2) explore preferences for mHealth apps compared with other mental health services.Methods: Using convenience sampling, participants completed a multiscale 54-item Web-based survey. Based on significant correlations with acceptance, hierarchical stepwise regression analysis was performed within three blocks: (1) background and stress-related control variables, (2) beliefs and attitudes toward using mHealth, and (3) the core UTAUT determinants. The preference for mHealth apps in comparison with nine other mental health services (operationalized as readiness to use) was analyzed using paired t tests.Results: Of 141 participants, nearly half (69/141, 48.9%) indicated prior mHealth use. Acceptance of stress coping apps was moderate (mean 3.10, SD 1.03, range 1-5). Hierarchical stepwise regression including four of 11 variables (R2=.62; P=.01, f2=1.63) identified positive attitudes toward using mHealth for stress coping (beta=0.69, P<.001, 46% R2 increase above block 1, f2=0.85), skepticism/perceived risks (beta=−0.14, P=.01, f2=0.16), and stress symptoms (beta=0.12, P=.03, f2=0.14) as significant predictors of acceptance. UTAUT determinants added no predictive contribution beyond attitudes (all P>.05, R2 increase of 1%), whereas post hoc analysis showed significant R2 increases of attitudes and skepticism/perceived risks beyond UTAUT determinants (all P<.001, R2 increase of 13%). The readiness to use apps was equivalent to or significantly higher than most service types, but lower than information websites.Conclusions: Attitudes may be at least as predictive for the acceptance of stress management apps as for more elaborated outcome beliefs. Efforts aimed at improving the public adoption of mHealth could put more emphasis on the pleasant aspects of app use, address misconceptions, offer stress screening tools on health websites, and increase options to try high-quality apps.