A systematic review and meta analysis on digital mental health interventions in inpatient settings.

E-mental health (EMH) interventions gain increasing importance in the treatment of mental health disorders. Their outpatient efficacy is well-established. However, research on EMH in inpatient settings remains sparse and lacks a meta-analytic synthesis. This paper presents a meta-analysis on the efficacy of EMH in inpatient settings. Searching multiple databases (PubMed, ScienceGov, PsycInfo, CENTRAL, references), 26 randomized controlled trial (RCT) EMH inpatient studies (n = 6112) with low or medium assessed risk of bias were included. A small significant total effect of EMH treatment was found (g = 0.3). The effect was significant both for blended interventions (g = 0.42) and post-treatment EMH-based aftercare (g = 0.29). EMH treatment yielded significant effects across different patient groups and types of therapy, and the effects remained stable post-treatment. The results show the efficacy of EMH treatment in inpatient settings. The meta-analysis is limited by the small number of included studies.

Adherence to Dietary Behavior Recommendations Moderates the Effect Between Time Since Metabolic and Bariatric Surgery and Percentage Total Weight Loss.

PURPOSE: Metabolic and bariatric surgery (MBS) is the gold standard in treating severe obesity. Previous research implies that different psychological and behavior-related factors might be critical for MBS' sustained success. Yet adherence to dietary behavior recommendations and its impact on weight development is rarely examined. This study investigated the relationship between adherence to dietary behavior recommendations and the percentage of total weight loss (%TWL) after MBS. MATERIALS AND METHODS: This study is a cohort study (acquisition in Germany). N = 485 patients after MBS, being in grade III of obesity (body mass index (BMI) ≥ 40 kg/m2) pre-MBS, were included. Participants answered a standardized assessment on the relevant constructs, including adherence to dietary behavior recommendations, depression symptoms, weight, diet, and MBS characteristics. RESULTS: BMI pre-MBS, type of MBS, age, regularity of physical activity, and depression symptoms were identified as significant covariates of %TWL and adherence. Within 6 months after MBS, adherence seems to peak, F(5,352) = 12.35, p < .001. Adherence and time since MBS predict %TWL. A higher adherence (moderator) is related to a higher %TWL, R2 = 52.65%, F(13,344) = 31.54, p < .001. CONCLUSION: After MBS, adherence to dietary behavior recommendations seems crucial for maximizing its success. Implications for the optimization of MBS' success in aftercare management arise. In particular, behavior modification interventions should be routinely implemented.

Needs and Demands for eHealth Pain Management Interventions in Chronic Pain Patients.

Although chronic pain is a global health problem, the current care situation is often inadequate. eHealth offers many advantages as an additional option for treating chronic pain. Yet, an intervention's efficacy can only be fully exhausted if patients intend to use it. This study aims to identify the needs and demands of patients with chronic pain regarding intervention concepts and frameworks to develop specifically tailored eHealth pain management interventions. A cross-sectional study was conducted, including 338 individuals with chronic pain. Within the cohort, a distinction between a high- and a low-burden group was made. Respondents generally preferred a permanently accompanying mobile app, but the preferred content varied with group. According to the majority, interventions should be made available on smartphones, offer sessions once per week with a duration from 10 to 30 min, and be recommended by experts. These results can provide the basis for future eHealth pain management interventions tailored to the patients' needs and demands.

Determinants of Acceptance of Weight Management Applications in Overweight and Obese Individuals: Using an Extended Unified Theory of Acceptance and Use of Technology Model.

Overweight and obesity carry a tremendous burden in terms of physiological and psychological comorbidities. There is a great variety of weight management applications to support weight reduction, but a systematical analysis of individuals' needs and requirements to adopt sustaining lifestyle changes is missing so far. This study aimed to assess the acceptance of such applications and its underlying predictors in individuals with overweight/obesity. A cross-sectional study was conducted, including 439 overweight/obese individuals. Health-related internet use and acceptance of weight management applications were examined using a modified questionnaire based on the Unified Theory of Acceptance and Use of Technology (UTAUT). The general acceptance of weight management applications was high, with significant age differences. Compared to older individuals, younger ones showed a higher acceptance. BMI was not significantly associated with acceptance. Besides psychometric data and eHealth-related data, performance expectancy, effort expectancy, and social influence proved to be significant predictors for acceptance. The total variance explanation provided by the extended UTAUT model was 61.2%. The knowledge of the influencing factors on acceptance might be useful in developing, optimizing, and establishing weight management applications. For determining acceptance and its predictors of weight management applications, the UTAUT model is a valid approach.