The high global prevalence of depression, together with the recent acceleration of remote care owing to the COVID-19 pandemic, has prompted increased interest in the efficacy of digital interventions for the treatment of depression. We provide a summary of the latest evidence base for digital interventions in the treatment of depression based on the largest study sample to date. A systematic literature search identified 83 studies (N = 15,530) that randomly allocated participants to a digital intervention for depression versus an active or inactive control condition. Overall heterogeneity was very high (I2 = 84%). Using a random-effects multilevel metaregression model, we found a significant medium overall effect size of digital interventions compared with all control conditions (g = .52). Subgroup analyses revealed significant differences between interventions and different control conditions (WLC: g = .70; attention: g = .36; TAU: g = .31), significantly higher effect sizes in interventions that involved human therapeutic guidance (g = .63) compared with self-help interventions (g = .34), and significantly lower effect sizes for effectiveness trials (g = .30) compared with efficacy trials (g = .59). We found no significant difference in outcomes between smartphone-based apps and computer- and Internet-based interventions and no significant difference between human-guided digital interventions and face-to-face psychotherapy for depression, although the number of studies in both comparisons was low. Findings from the current meta-analysis provide evidence for the efficacy and effectiveness of digital interventions for the treatment of depression for a variety of populations. However, reported effect sizes may be exaggerated because of publication bias, and compliance with digital interventions outside of highly controlled settings remains a significant challenge. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Providing accessible and effective healthcare solutions for people living in low- and middle-income countries, migrants, and indigenous people is central to reduce the global mental health treatment gap. Internet- and mobile-based interventions (IMI) are considered scalable psychological interventions to reduce the burden of mental disorders and are culturally adapted for implementation in these target groups. In October 2020, the databases PsycInfo, MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Web of Science were systematically searched for studies that culturally adapted IMI for mental disorders. Among 9438 screened records, we identified 55 eligible articles. We extracted 17 content, methodological, and procedural components of culturally adapting IMI, aiming to consider specific situations and perspectives of the target populations. Adherence and effectiveness of the adapted IMI seemed similar to the original IMI; yet, no included study conducted a direct comparison. The presented taxonomy of cultural adaptation of IMI for mental disorders provides a basis for future studies investigating the relevance and necessity of their cultural adaptation.PROSPERO registration number: CRD42019142320.

As e-health offerings rapidly expand, they are transforming and challenging traditional mental health care systems globally, presenting both promising opportunities and significant risks. This article critically examines the potential and pitfalls of integrating digital technologies into mental health care, particularly in the realms of diagnosis, prevention, and treatment. It explores current advancements and evidence-based practices, and provides a vision for how future technologies can evolve responsibly to meet mental health needs. The article concludes with the TEQUILA framework, addressing essential elements and challenges for fostering a beneficial and ethical future. A responsible future for digital mental health requires building Trust by ensuring data privacy, security, and transparency in AI-driven decisions, along with Evidence-based and robust regulatory oversight to maintain Quality. Usability, design, usability tailored to diverse needs, and ethical alignment with users' Interests will all be essential, while Liability and Accreditation standards will safeguard accountability in this evolving landscape.

Background: Mental disorders are highly prevalent and associated with considerable disease burden and personal and societal costs. However, they can be effectively reduced through prevention measures. The Internet as a medium appears to be an opportunity for scaling up preventive interventions to a population level.Objective: The aim of this study was to systematically summarize the current state of research on Internet-based interventions for the prevention of mental disorders to give a comprehensive overview of this fast-growing field.Methods: A systematic database search was conducted (CENTRAL, Medline, PsycINFO). Studies were selected according to defined eligibility criteria (adult population, Internet-based mental health intervention, including a control group, reporting onset or severity data, randomized controlled trial). Primary outcome was onset of mental disorder. Secondary outcome was symptom severity. Study quality was assessed using the Cochrane Risk of Bias Tool. Meta-analytical pooling of results took place if feasible.Results: After removing duplicates, 1169 studies were screened of which 17 were eligible for inclusion. Most studies examined prevention of eating disorders or depression or anxiety. Two studies on posttraumatic stress disorder and 1 on panic disorder were also included. Overall study quality was moderate. Only 5 studies reported incidence data assessed by means of standardized clinical interviews (eg, SCID). Three of them found significant differences in onset with a number needed to treat of 9.3-41.3. Eleven studies found significant improvements in symptom severity with small-to-medium effect sizes (d=0.11- d=0.76) in favor of the intervention groups. The meta-analysis conducted for depression severity revealed a posttreatment pooled effect size of standardized mean difference (SMD) =−0.35 (95% CI, −0.57 to −0.12) for short-term follow-up, SMD = −0.22 (95% CI, −0.37 to −0.07) for medium-term follow-up, and SMD = −0.14 (95% CI, -0.36 to 0.07) for long-term follow-up in favor of the Internet-based psychological interventions when compared with waitlist or care as usual.Conclusions: Internet-based interventions are a promising approach to prevention of mental disorders, enhancing existing methods. Study results are still limited due to inadequate diagnostic procedures. To be able to appropriately comment on effectiveness, future studies need to report incidence data assessed by means of standardized interviews. Public health policy should promote research to reduce health care costs over the long term, and health care providers should implement existing, demonstrably effective interventions into routine care.

Background: The number of mobile health apps (MHAs), which are developed to promote healthy behaviors, prevent disease onset, manage and cure diseases, or assist with rehabilitation measures, has exploded. App store star ratings and descriptions usually provide insufficient or even false information about app quality, although they are popular among end users. A rigorous systematic approach to establish and evaluate the quality of MHAs is urgently needed. The Mobile App Rating Scale (MARS) is an assessment tool that facilitates the objective and systematic evaluation of the quality of MHAs. However, a German MARS is currently not available. Objective: The aim of this study was to translate and validate a German version of the MARS (MARS-G). Methods: The original 19-item MARS was forward and backward translated twice, and the MARS-G was created. App description items were extended, and 104 MHAs were rated twice by eight independent bilingual researchers, using the MARS-G and MARS. The internal consistency, validity, and reliability of both scales were assessed. Mokken scale analysis was used to investigate the scalability of the overall scores. Results: The retranslated scale showed excellent alignment with the original MARS. Additionally, the properties of the MARS-G were comparable to those of the original MARS. The internal consistency was good for all subscales (ie, omega ranged from 0.72 to 0.91). The correlation coefficients (r) between the dimensions of the MARS-G and MARS ranged from 0.93 to 0.98. The scalability of the MARS (H=0.50) and MARS-G (H=0.48) were good. Conclusions: The MARS-G is a reliable and valid tool for experts and stakeholders to assess the quality of health apps in German-speaking populations. The overall score is a reliable quality indicator. However, further studies are needed to assess the factorial structure of the MARS and MARS-G.

Background: Mobile health applications (apps) are considered to complement traditional psychological treatments for Post-Traumatic Stress Disorder (PTSD). However, the use for clinical practice and quality of available apps is unknown. Objective: To assess the general characteristics, therapeutic background, content, and quality of apps for PTSD and to examine their concordance with established PTSD treatment and self-help methods. Method: A web crawler systematically searched for apps targeting PTSD in the British Google Play and Apple iTunes stores. Two independent researchers rated the apps using the Mobile App Rating Scale (MARS). The content of high-quality apps was checked for concordance with psychological treatment and self-help methods extracted from current literature on PTSD treatment. Results: Out of 555 identified apps, 69 met the inclusion criteria. The overall app quality based on the MARS was medium (M = 3.36, SD = 0.65). Most apps (50.7%) were based on cognitive behavioural therapy and offered a wide range of content, including established psychological PTSD treatment methods such as processing of trauma-related emotions and beliefs, relaxation exercises, and psychoeducation. Notably, data protection and privacy standards were poor in most apps and only one app (1.4%) was scientifically evaluated in a randomized controlled trial. Conclusions: High-quality apps based on established psychological treatment techniques for PTSD are available in commercial app stores. However, users are confronted with great difficulties in identifying useful high-quality apps and most apps lack an evidence-base. Commercial distribution channels do not exploit the potential of apps to complement the psychological treatment of PTSD.