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Background: While the efficacy of digital interventions for the treatment of depression is well established, comprehensive knowledge on how therapeutic changes come about is still limited. This systematic review aimed to provide an overview of research on change mechanisms in digital interventions for depression and meta-analytically evaluate indirect effects of potential mediators., Methods: The databases CENTRAL, Embase, MEDLINE, and PsycINFO were systematically searched for randomized controlled trials investigating mediators of digital interventions for adults with depression. Two reviewers independently screened studies for inclusion, assessed study quality and categorized potential mediators. Indirect effects were synthesized with a two-stage structural equation modeling approach (TSSEM)., Results: Overall, 25 trials (8110 participants) investigating 84 potential mediators were identified, of which attentional (8 %), self-related (6 %), biophysiological (6 %), affective (5 %), socio-cultural (2 %) and motivational (1 %) variables were the scope of this study. TSSEM revealed significant mediation effects for combined self-related variables (ab = -0.098; 95 %-CI: [-0.150, -0.051]), combined biophysiological variables (ab = -0.073; 95 %-CI: [-0.119, -0.025]) and mindfulness (ab = -0.042; 95 %-CI: [-0.080, -0.015]). Meta-analytical evaluations of the other three domains were not feasible., Limitations: Methodological shortcomings of the included studies, the considerable heterogeneity and the small number of investigated variables within domains limit the generalizability of the results., Conclusion: The findings further the understanding of potential change mechanisms in digital interventions for depression and highlight recommendations for future process research, such as the consideration of temporal precedence and experimental manipulation of potential mediators, as well as the application of network approaches., Competing Interests: Declaration of competing interest All authors declare that they have no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Passive sensing data from smartphones and wearables may help improve the prediction of suicidal thoughts and behaviors (STB). In this systematic review, we explored the feasibility and predictive validity of passive sensing for STB. On June 24, 2024, we systematically searched Medline, Embase, Web of Science, PubMed, and PsycINFO. Studies were eligible if they investigated the association between STB and passive sensing, or the feasibility of passive sensing in this context. From 2107 unique records, we identified eleven prediction studies, ten feasibility studies, and seven protocols. Studies indicated generally lower model performance for passive compared to active data, with three out of four studies finding no incremental value. PROBAST ratings revealed major shortcomings in methodology and reporting. Studies suggested that passive sensing is feasible in high-risk populations. In conclusion, there is limited evidence on the predictive value of passive sensing for STB. We highlight important quality characteristics for future research., (© 2024. The Author(s).)

Importance: While the effects of internet- and mobile-based interventions (IMIs) for depression have been extensively studied, no systematic evidence is available regarding the heterogeneity of treatment effects (HTEs), indicating to what extent patient-by-treatment interactions exist and personalized treatment models might be necessary., Objective: To investigate the HTEs in IMIs for depression as well as their efficacy and effectiveness., Data Sources: A systematic search in Embase, MEDLINE, Central, and PsycINFO for randomized clinical trials and supplementary reference searches was conducted on October 13, 2019, and updated March 25, 2022. The search string included various terms related to digital psychotherapy, depression, and randomized clinical trials., Study Selection: Titles, abstracts, and full texts were reviewed by 2 independent researchers. Studies of all populations with at least 1 intervention group receiving an IMI for depression and at least 1 control group were eligible, if they assessed depression severity as a primary outcome and followed a randomized clinical trial (RCT) design., Data Extraction and Synthesis: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines. Risk of bias was evaluated using the Cochrane Risk of Bias Tool. HTE was investigated using logarithmic variance ratios (lnVR) and effect sizes using Hedges g. Three-level bayesian meta-regressions were conducted., Main Outcomes and Measures: Heterogeneity of treatment effects was the primary outcome of this study; magnitudes of treatment effect sizes were the secondary outcome. Depression severity was measured by different self-report and clinician-rated scales in the included RCTs., Results: The systematic review of 102 trials included 19 758 participants (mean [SD] age, 39.9 [10.58] years) with moderate depression severity (mean [SD] in Patient Health Questionnaire-9 score, 12.81 [2.93]). No evidence for HTE in IMIs was found (lnVR = -0.02; 95% credible interval [CrI], -0.07 to 0.03). However, HTE was higher in more severe depression levels (β̂ = 0.04; 95% CrI, 0.01 to 0.07). The effect size of IMI was medium (g = -0.56; 95% CrI, -0.46 to -0.66). An interaction effect between guidance and baseline severity was found (β̂ = -0.24, 95% CrI, -0.03 to -0.46)., Conclusions and Relevance: In this systematic review and meta-analysis of RCTs, no evidence for increased patient-by-treatment interaction in IMIs among patients with subthreshold to mild depression was found. Guidance did not increase effect sizes in this subgroup. However, the association of baseline severity with HTE and its interaction with guidance indicates a more sensitive, guided, digital precision approach would benefit individuals with more severe symptoms. Future research in this population is needed to explore personalization strategies and fully exploit the potential of IMI.

Survivors of intimate partner violence (IPV) face serious health-related, social and economic consequences. Prior meta-analyses indicate efficacy of psychosocial interventions for support of IPV survivors, but their results are affected by methodological limitations. Extensive subgroup analyses on the moderating effects of intervention and study characteristics are lacking. To address these limitations in an up-to-date and comprehensive meta-analytic review, four literature databases (PsycInfo, Medline, Embase, and CENTRAL, March 23, 2022) were searched for randomized-controlled trials examining the efficacy of psychosocial interventions compared to control groups in improving safety-related, mental health, and psychosocial outcomes in IPV survivors. Weighted effects on IPV, depression, posttraumatic stress disorder (PTSD), and psychosocial outcomes were calculated under random-effects assumption. Subgroup analyses were performed to investigate moderating effects of predefined intervention and study characteristics. Study quality was rated. In all, 80 studies were included in qualitative synthesis, and 40 studies in meta-analyses. Psychosocial interventions significantly reduced symptoms of depression (SMD: -0.15 [95% confidence interval, CI [-0.25, -0.04]; p  = .006], I 2  = 54%) and PTSD (SMD: -0.15 [95% CI [-0.29, -0.01]; p  = .04], I 2  = 52%), but not IPV reexperience (SMD: -0.02 [95% CI [ -0.09, 0.06]; p  = .70], I 2  = 21%) compared to control conditions at post. High-intensive and integrative interventions, combining advocacy-based and psychological components, were favorable subgroups. Yielded effects were modest and not maintained long term. The quality of evidence was low and potential harms remain unclear. Future research should adopt higher standards of research conduct and reporting and must account for the complexity and diversity of IPV experiences., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: Despite severely burdened individuals, often being excluded from research studies on internet- and mobile-based interventions (IMIs), negative events (NEs) including suicidal thoughts and behaviors (STBs) can still occur during a trial. NEs require monitoring and adequate safety measures. However, study protocols frequently lack comprehensive descriptions of procedures for managing NEs., Aims: This study aimed to illustrate the assessment, monitoring, and procedures for addressing NEs in two studies on IMIs in adults and youth using case reports, to identify strengths and weaknesses of the NE management approaches, and to derive key learnings and recommendations., Methods: Two case reports were drawn from two distinct IMI studies. The first study, PSYCHOnlineTHERAPY, evaluates the combination of an IMI with on-site psychotherapy for anxiety and depressive disorders in adults (adult blended study). The second study evaluates a standalone, therapist-guided IMI for post-traumatic stress disorder (PTSD) in youth (youth standalone study). Potential NEs were predefined depending on the study sample. The case studies thoroughly document the systematic recording and ongoing monitoring of NEs through self-report and observer-based assessments during the interventions. The cases illustrate a variety of NE management strategies, including automated and personalized approaches, adapted to the specific nature and severity of the NEs. The NE management approaches are visualized using decision trees., Results: In the adult blended case study, online questionnaires detected STBs and triggered automated support information. As on-site therapy had already ended, a telephone consultation session allowed for the identification and discussion of the heightened intensity of suicidal thoughts, along with the development of specific additional help options. In the youth standalone case study, heightened tension in an adolescent with PTSD during trauma processing could be addressed in a telephone therapeutic session focusing on resource activation and emotion regulation. The referral to on-site treatment was supported. Overall, advantages of the NE management included automated procedures, multimodal assessment of a wide range of NEs, and standardized procedures tailored to different severity levels. Weaknesses included the use of single-item assessments for STBs and lack of procedures in case of deterioration or nonresponse to treatment., Conclusion: This study provides practical insights and derives key learnings and recommendations regarding the management of NEs in different IMI contexts for both adults and youth., Competing Interests: ACZ reports having received fees for lectures or workshops and for expert videos for an internet-based intervention for sexual dysfunction. IT reports having received fees for lectures/workshops in the e-mental-health context from training institutes and congresses for psychotherapists, but outside the submitted work. She was the project lead for the research project ImpleMentAll (funded by the European Commission) at GET.ON which aimed to investigate the effectiveness of tailored implementation strategies compared to implementation as usual for guided IMIs (11/2017–03/2021). HB received consultancy fees, reimbursement of congress attendance, and travel costs as well as payments for lectures from Psychotherapy and Psychiatry Associations as well as Psychotherapy Training Institutes in the context of E-Mental-Health topics. He has been the beneficiary of study support (third-party funding) from several public funding organizations. LBS received personal fees from Psychotherapy and Psychiatry Associations and Psychotherapy Training Institutes, including reimbursement of travel costs and payment for lectures in the context of E-Mental-Health but outside the submitted work. ChS, CeS, TS, and LS have no conflicts of interest to declare., (© 2024 The Authors.)

Background: Digital formats have the potential to enhance accessibility to care for individuals with suicidal ideation. However, digital self-help interventions have faced limitations, including small effect sizes in reducing suicidal ideation, low adherence, and safety concerns., Objective: Therefore, we aimed to develop a remote blended cognitive behavioral therapy intervention that specifically targets suicidal ideation by blending video therapy with web-based self-help modules. The objective of this paper is to describe the collaborative development process and the resulting intervention and treatment rationale., Methods: First, we compiled intervention components from established treatment manuals designed for people with suicidal ideation or behavior, resulting in the development of 11 drafts of web-based modules. Second, we conducted a qualitative study, involving 5 licensed psychotherapists and 3 lay counselors specialized in individuals with suicidal ideation who reviewed these module drafts. Data were collected using the think-aloud method and semistructured interviews, and a qualitative content analysis was performed. The 4 a priori main categories of interest were blended care for individuals with suicidal ideation, contents of web-based modules, usability of modules, and layout. Subcategories emerged inductively from the interview transcripts. Finally, informed by previous treatment manuals and qualitative findings, we developed the remote blended treatment program., Results: The participants suggested that therapists should thoroughly prepare the web-based therapy with patients to tailor the therapy to each individual's needs. Participants emphasized that the web-based modules should explain concepts in a simple manner, convey empathy and validation, and include reminders for the safety plan. In addition, participants highlighted the need for a simple navigation and layout. Taking these recommendations into account, we developed a fully remote blended cognitive behavioral therapy intervention comprising 12 video therapy sessions and up to 31 web-based modules. The treatment involves collaboratively developing a personalized treatment plan to address individual suicidal drivers., Conclusions: This remote treatment takes advantage of the high accessibility of digital formats while incorporating full sessions with a therapist. In a subsequent pilot trial, we will seek input from individuals with lived experience and therapists to test the feasibility of the treatment., (©Rebekka Büscher, Lasse B Sander, Mattis Nuding, Harald Baumeister, Tobias Teismann. Originally published in JMIR Formative Research (https://formative.jmir.org), 21.09.2023.)

Introduction: New digital treatment formats may reduce barriers to treatment for individuals with suicidal ideation. This study aimed to investigate the feasibility of a remote blended care programme for this population, defined as acceptability, demand, practicality, adaptation, indications of efficacy and safety., Methods: We conducted a mixed-methods single-arm trial for proof-of-concept. Participants were eligible if they were at least 18 years old, had sufficient German proficiency, a Beck Scale for Suicidal Ideation score ≥2, internet access and lived near the outpatient clinic. The treatment consisted of 12 sessions of cognitive-behavioural videotherapy combined with online modules over 6 weeks., Results: We included 10 participants. All patients were satisfied with the treatment; most patients (80%) reported unpleasant memories resurfacing. All patients completed all therapy sessions and a mean of 13.7 modules (SD = 5.7); three patients switched to face-to-face treatment, in one case due to safety concerns. All patients and most therapists (83.3%) found the treatment overall practicable. Most patients (66.7%) and therapists (66.7%) considered remote treatment equivalent to face-to-face therapy. There were no serious adverse events., Conclusion: While promising, the results suggest changes to the programme might be needed, particularly for patients' safety. A controlled feasibility trial should investigate temporary deteriorations., (© 2023 The Authors. Clinical Psychology & Psychotherapy published by John Wiley & Sons Ltd.)

Background: While there is evolving knowledge on change processes of digital cognitive behavioral therapy (CBT) in the treatment of depression, little is known about how these interventions produce therapeutic change in the comorbid constellation of chronic back pain (CBP). Here, we examined whether the effects of a digital intervention to treat depression in patients with CBP are mediated by three pain-related variables (i.e., pain self-efficacy, pain-related disability, pain intensity)., Methods: This study is a secondary analysis of a randomized clinical trial conducted in routine care at 82 orthopedic clinics across Germany. In total, 209 adults with CBP and diagnosed depression (SCID interview) were randomly assigned to the intervention (n = 104) or treatment-as-usual (n = 105). Cross-lagged mediation models were estimated to investigate longitudinal mediation effects of putative mediators with depression symptom severity (PHQ-9) as primary outcome at post-treatment., Results: Longitudinal mediation effects were observed for pain self-efficacy (ß = -0.094, 95%-CI [-0.174, -0.014], p = 0.021) and pain-related disability (ß = -0.068, 95%-CI [-0.130, -0.001], p = 0.047). Furthermore, the hypothesized direction of the mediation effects was supported, reversed causation did not occur. Pain intensity did not reveal a mediation effect., Conclusions: The results suggest a relevant role of pain self-efficacy and pain-related disability as change processes in the treatment of depression for patients with CBP in routine care. However, further research is needed to disclose potential reciprocal relationships of mediators, and to extend and specify our knowledge of the mechanisms of change in digital CBT for depression., Competing Interests: Declaration of competing interest HB reports to have received consultancy fees, fees for lectures or workshops from chambers of psychotherapists and training institutes for psychotherapists and license fees for an Internet-intervention. MD reports to have received fees for lectures as well as for workshops for different psychotherapy training institutes. All other authors certify that they have no affiliations with or involvement in any organization or entity with financial interest, or nonfinancial interest in the subject matter or materials discussed in this manuscript., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Objective: Mental health self-report and clinician-rating scales with diagnoses defined by sum-score cut-offs are often used for depression screening. This study investigates whether machine learning (ML) can detect major depressive episodes (MDE) based on screening scales with higher accuracy than best-practice clinical sum-score approaches., Methods: Primary data was obtained from two RCTs on the treatment of depression. Ground truth were DSM 5 MDE diagnoses based on structured clinical interviews (SCID) and PHQ-9 self-report, clinician-rated QIDS-16, and HAM-D-17 were predictors. ML models were trained using 10-fold cross-validation. Performance was compared against best-practice sum-score cut-offs. Primary outcome was the Area Under the Curve (AUC) of the Receiver Operating Characteristic curve. DeLong's test with bootstrapping was used to test for differences in AUC. Secondary outcomes were balanced accuracy, precision, recall, F1-score, and number needed to diagnose (NND)., Results: A total of k = 1030 diagnoses (no diagnosis: k = 775; MDE: k = 255) were included. ML models achieved an AUC QIDS-16 = 0.94, AUC HAM-D-17 = 0.88, and AUC PHQ-9 = 0.83 in the testing set. ML AUC was significantly higher than sum-score cut-offs for QIDS-16 and PHQ-9 ( ps ≤ 0.01; HAM_D-17: p = 0.847). Applying optimal prediction thresholds, QIDS-16 classifier achieved clinically relevant improvements (Δbalanced accuracy = 8%, ΔF1-score = 14%, ΔNND = 21%). Differences for PHQ_9 and HAM-D-17 were marginal., Conclusions: ML augmented depression screenings could potentially make a major contribution to improving MDE diagnosis depending on questionnaire (e.g., QIDS-16). Confirmatory studies are needed before ML enhanced screening can be implemented into routine care practice., (© The Author(s) 2023.)

Background: Intimate partner violence (IPV) is a prevalent public health issue associated with multiple physical and mental health consequences for survivors. Digital interventions can provide low-threshold support to those experiencing IPV, but existing digital interventions have limited efficacy in improving the safety and mental health of IPV survivors. Digitally adapting an integrative intervention with advocacy-based and psychological content holds promise for increasing the efficacy of digital interventions in the context of IPV., Methods: This study examines the needs, acceptability and usability of an integrative digital intervention for people affected by IPV. We used the think-aloud method and semi-structured interviews with a sample of six people with lived experiences of IPV and six service providers. We analyzed the data using thematic analysis., Results: We identified the increasing general acceptance of digital support tools and the limited capacity of the current support system as societal context factors influencing the acceptance of and needs regarding digital interventions in the context of IPV. An integrative digital self-help intervention offers several opportunities to complement the current support system and to meet the needs of people affected by IPV, including the reduction of social isolation, a space for self-reflection and coping strategies to alleviate the situation. However, potentially ongoing violence, varying stages of awareness and psychological capacities, and as well as the diversity of IPV survivors make it challenging to develop a digital intervention suitable for the target group. We received feedback on the content of the intervention and identified design features required for intervention usability., Conclusion: An integrative digital self-help approach, with appropriate security measures and trauma-informed design, has the potential to provide well-accepted, comprehensive and continuous psychosocial support to people experiencing IPV. A multi-modular intervention that covers different topics and can be personalized to individual user needs could address the diversity of the target population. Providing guidance for the digital intervention is critical to spontaneously address individual needs. Further research is needed to evaluate the efficacy of an integrative digital self-help intervention and to explore its feasibility it in different settings and populations., (© 2023. The Author(s).)

Objective: The mechanisms of change in digital interventions for the prevention of depression are largely unknown. Here, we explored whether five theoretically derived intervening variables (i.e., pain intensity, pain-related disability, pain self-efficacy, quality of life [QoL], and work capacity) were mediating the effectiveness of a digital intervention specifically designed to prevent depression in patients with chronic back pain (CBP)., Method: This study is a secondary analysis of a pragmatic, observer-masked randomized clinical trial conducted at 82 orthopedic clinics in Germany. A total of 295 adults with a diagnosis of CBP and subclinical depressive symptoms were randomized to either the intervention group ( n = 149) or treatment-as-usual ( n = 146). Longitudinal mediation analyses were conducted with structural equation modeling and depression symptom severity as primary outcome (Patient Health Questionnaire-9 [PHQ-9]; 6 months after randomization) on an intention-to-treat basis., Results: Beside the effectiveness of the digital intervention in preventing depression, we found a significant causal mediation effect for QoL as measured with the complete scale of Assessment of Quality of Life (AQoL-6D; axb: -0.234), as well as for the QoL subscales mental health (axb: -0.282) and coping (axb: -0.249). All other potential intervening variables were not significant., Conclusion: Our findings suggest a relevant role of QoL, including active coping, as change mechanism in the prevention of depression. Yet, more research is needed to extend and specify our knowledge on empirically supported processes in digital depression prevention. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Background: Accurate and timely diagnostics are essential for effective mental healthcare. Given a resource- and time-limited mental healthcare system, novel digital and scalable diagnostic approaches such as smart sensing, which utilizes digital markers collected via sensors from digital devices, are explored. While the predictive accuracy of smart sensing is promising, its acceptance remains unclear. Based on the unified theory of acceptance and use of technology, the present study investigated (1) the effectiveness of an acceptance facilitating intervention (AFI), (2) the determinants of acceptance, and (3) the acceptance of adults toward smart sensing., Methods: The participants ( N  = 202) were randomly assigned to a control group (CG) or intervention group (IG). The IG received a video AFI on smart sensing, and the CG a video on mindfulness. A reliable online questionnaire was used to assess acceptance, performance expectancy, effort expectancy, facilitating conditions, social influence, and trust. The self-reported interest in using and the installation of a smart sensing app were assessed as behavioral outcomes. The intervention effects were investigated in acceptance using t -tests for observed data and latent structural equation modeling (SEM) with full information maximum likelihood to handle missing data. The behavioral outcomes were analyzed with logistic regression. The determinants of acceptance were analyzed with SEM. The root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR) were used to evaluate the model fit., Results: The intervention did not affect the acceptance ( p  = 0.357), interest (OR = 0.75, 95% CI: 0.42-1.32, p  = 0.314), or installation rate (OR = 0.29, 95% CI: 0.01-2.35, p  = 0.294). The performance expectancy ( γ  = 0.45, p  < 0.001), trust ( γ  = 0.24, p  = 0.002), and social influence ( γ  = 0.32, p  = 0.008) were identified as the core determinants of acceptance explaining 68% of its variance. The SEM model fit was excellent (RMSEA = 0.06, SRMR = 0.05). The overall acceptance was M  = 10.9 (SD = 3.73), with 35.41% of the participants showing a low, 47.92% a moderate, and 10.41% a high acceptance., Discussion: The present AFI was not effective. The low to moderate acceptance of smart sensing poses a major barrier to its implementation. The performance expectancy, social influence, and trust should be targeted as the core factors of acceptance. Further studies are needed to identify effective ways to foster the acceptance of smart sensing and to develop successful implementation strategies., Clinical Trial Registration: identifier 10.17605/OSF.IO/GJTPH., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Terhorst, Weilbacher, Suda, Simon, Messner, Sander and Baumeister.)

Background: Suicide is a global public health problem. Digital interventions are considered a low-threshold treatment option for people with suicidal ideation or behaviors. Internet-based cognitive behavioral therapy (iCBT) targeting suicidal ideation has demonstrated effectiveness in reducing suicidal ideation. However, suicidal ideation often is related to additional mental health problems, which should be addressed for optimal care. Yet, the effects of iCBT on related symptoms, such as depression, anxiety, and hopelessness, remain unclear., Objective: We aimed to analyze whether digital interventions targeting suicidal ideation had an effect on related mental health symptoms (depression, anxiety, and hopelessness)., Methods: We systematically searched CENTRAL, PsycInfo, Embase, and PubMed for randomized controlled trials that investigated guided or unguided iCBT for suicidal ideation or behaviors. Participants reporting baseline suicidal ideation were eligible. Individual participant data (IPD) were collected from eligible trials. We conducted a 1-stage IPD meta-analysis on the effects on depression, anxiety, and hopelessness-analyzed as 2 indices: symptom severity and treatment response., Results: We included IPD from 8 out of 9 eligible trials comprising 1980 participants with suicidal ideation. iCBT was associated with significant reductions in depression severity (b=-0.17; 95% CI -0.25 to -0.09; P<.001) and higher treatment response (ie, 50% reduction of depressive symptoms; b=0.36; 95% CI 0.12-0.60; P=.008) after treatment. We did not find significant effects on anxiety and hopelessness., Conclusions: iCBT for people with suicidal ideation revealed significant effects on depression outcomes but only minor or no effects on anxiety and hopelessness. Therefore, individuals with comorbid symptoms of anxiety or hopelessness may require additional treatment components to optimize care. Studies that monitor symptoms with higher temporal resolution and consider a broader spectrum of factors influencing suicidal ideation are needed to understand the complex interaction of suicidality and related mental health symptoms., (©Lasse B Sander, Marie Beisemann, Philipp Doebler, Hannah Moon Micklitz, Ad Kerkhof, Pim Cuijpers, Philip Batterham, Alison Calear, Helen Christensen, Eva De Jaegere, Matthias Domhardt, Annette Erlangsen, Ozlem Eylem-van Bergeijk, Ryan Hill, Charlotte Mühlmann, Marie Österle, Jeremy Pettit, Gwendolyn Portzky, Lena Steubl, Bregje van Spijker, Joseph Tighe, Aliza Werner-Seidler, Rebekka Büscher. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 26.06.2023.)

Introduction: Digital cognitive behavioral therapy (i-CBT) interventions for the treatment of depression have been extensively studied and shown to be effective in the reduction of depressive symptoms. However, little is known about their effects on suicidal thoughts and behaviors (STB). Information on the impact of digital interventions on STB are essential for patients' safety because most digital interventions are self-help interventions without direct support options in case of a suicidal crisis. Therefore, we aim to conduct a meta-analysis of individual participant data (IPDMA) to investigate the effects of i-CBT interventions for depression on STB and to explore potential effect moderators., Methods: Data will be retrieved from an established and annually updated IPD database of randomized controlled trials investigating the effectiveness of i-CBT interventions for depression in adults and adolescents. We will conduct a one-stage and a two-stage IPDMA on the effects of these interventions on STB. All types of control conditions are eligible. STB can be measured using specific scales (e.g., Beck scale suicide, BSS) or single items from depression scales (e.g., item 9 of the PHQ-9) or standardized clinical interviews. Multilevel linear regression will be used for specific scales, and multilevel logistic regression will be used for treatment response or deterioration, operationalized as a change in score by at least one quartile from baseline. Exploratory moderator analyses will be conducted at participant, study, and intervention level. Two independent reviewers will assess the risk of bias using the Cochrane Risk of Bias Tool 2., Conclusion: This IPDMA will harness the available data to assess the effects (response and deterioration) of i-CBT interventions for depression interventions on STB. Information about changes in STB is essential to estimate patients' safety when engaging in digital treatment formats., Trial Registration: We will pre-register this study with the open science framework after article acceptance to ensure consistency between online registration and the published trial protocol., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Sander et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Depression is highly prevalent among individuals with chronic back pain. Internet-based interventions can be effective in treating and preventing depression in this patient group, but it is unclear who benefits most from this intervention format., Method: In an analysis of two randomized trials ( N  = 504), we explored ways to predict heterogeneous treatment effects of an Internet-based depression intervention for patients with chronic back pain. Univariate treatment-moderator interactions were explored in a first step. Multilevel model-based recursive partitioning was then applied to develop a decision tree model predicting individualized treatment benefits., Results: The average effect on depressive symptoms was d  = -0.43 (95 % CI: -0.68 to -0.17; 9 weeks; PHQ-9). Using univariate models, only back pain medication intake was detected as an effect moderator, predicting higher effects. More complex interactions were found using recursive partitioning, resulting in a final decision tree with six terminal nodes. The model explained a large amount of variation (bootstrap-bias-corrected R 2  = 45 %), with predicted subgroup-conditional effects ranging from d i  = 0.24 to -1.31. External validation in a pilot trial among patients on sick leave ( N  = 76; R 2  = 33 %) pointed to the transportability of the model., Conclusions: The studied intervention is effective in reducing depressive symptoms, but not among all chronic back pain patients. Predictions of the multivariate tree learning model suggest a pattern in which patients with moderate depression and relatively low pain self-efficacy benefit most, while no benefits arise when patients' self-efficacy is already high. If corroborated in further studies, the developed tree algorithm could serve as a practical decision-making tool., Competing Interests: DDE reports to have received consultancy fees or served in the scientific advisory board from several companies such as Novartis, Sanofi, Lantern, Schön Kliniken, Minddistrict, and German health insurance companies (BARMER, Techniker Krankenkasse). DDE and MH are stakeholders of the Institute for Health Trainings Online (GET.ON/HelloBetter), which aims to implement scientific findings related to digital health interventions into routine care. HB reports to have received consultancy fees, fees for lectures or workshops from chambers of psychotherapists and training institutes for psychotherapists and license fees for an Internet intervention., (© 2023 The Authors.)

A large number of mobile health applications claiming to target insomnia are available in commercial app stores. However, limited information on the quality of these mobile health applications exists. The present study aimed to systematically search the European Google Play and Apple App Store for mobile health applications targeting insomnia, and evaluate the quality, content, evidence base and potential therapeutic benefit. Eligible mobile health applications were evaluated by two independent reviewers using the Mobile Application Rating Scale-German, which ranges from 1 - inadequate to 5 - excellent. Of 2236 identified mobile health applications, 53 were included in this study. Most mobile health applications (68%) had a moderate overall quality. Concerning the four main subscales of the Mobile Application Rating Scale-German, functionality was rated highest (M = 4.01, SD = 0.52), followed by information quality (M = 3.49, SD = 0.72), aesthetics (M = 3.31, SD = 1.04) and engagement (M = 3.02, SD = 1.03). While scientific evidence was identified for 10 mobile health applications (19%), only one study employed a randomized controlled design. Fifty mobile health applications featured sleep hygiene/psychoeducation (94%), 27 cognitive therapy (51%), 26 relaxation methods (49%), 24 stimulus control (45%), 16 sleep restriction (30%) and 24 sleep diaries (45%). Mobile health applications may have the potential to improve the care of insomnia. Yet, data on the effectiveness of mobile health applications are scarce, and this study indicates a large variance in the quality of the mobile health applications. Thus, independent information platforms are needed to provide healthcare seekers and providers with reliable information on the quality and content of mobile health applications., (© 2022 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Question: Digital interventions based on cognitive-behavioural therapy (iCBT) is associated with reductions in suicidal ideation. However, fine-grained analyses of effects and potential effect-moderating variables are missing. This study aimed to investigate the effectiveness of iCBT on suicidal ideation, effect moderators, effects on suicide attempts and predictors of adherence., Study Selection and Analysis: We systematically searched CENTRAL, PsycINFO, Embase and PubMed for randomised controlled trials that investigated iCBT for suicidal ideation or behaviours. Participants reporting baseline suicidal ideation were eligible. We conducted a one-stage individual participant data (IPD) meta-analysis. Suicidal ideation was the primary outcome, analysed as three indices: severity of suicidal ideation, reliable changes and treatment response., Findings: We included IPD from nine out of ten eligible trials (2037 participants). iCBT showed significant reductions of suicidal ideation compared with control conditions across all indices (severity: b=-0.247, 95% CI -0.322 to -0.173; reliable changes: b=0.633, 95% CI 0.408 to 0.859; treatment response: b=0.606, 95% CI 0.410 to 0.801). In iCBT, the rate of reliable improvement was 40.5% (controls: 27.3%); the deterioration rate was 2.8% (controls: 5.1%). No participant-level moderator effects were identified. The effects on treatment response were higher for trials with waitlist-controls compared with active controls. There were insufficient data on suicide attempts. Human support and female gender predicted treatment adherence. The main source of potential bias was missing outcome data., Conclusions: The current evidence indicates that iCBT is effective in reducing suicidal ideation irrespective of age, gender and previous suicide attempts. Future studies should rigorously assess suicidal behaviour and drop-out reasons., Competing Interests: Competing interests: AL is employed by Lyra Health, a digital mental health company; she receives salary and stock options from Lyra Health. CRW received consulting fees from Mindstrong Health, Click Therapeutics and Behavioral Tech Research. LBS received grants from the German Research Foundation during the conduct of the study and personal fees from psychotherapy training institutes, clinic providers and the German pension fund outside the submitted work. All other authours declare no competing interests., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Suicide is a severe public health problem, resulting in a high number of attempts and deaths each year. Early detection of suicidal thoughts and behaviors (STBs) is key to preventing attempts. We discuss passive sensing of digital and behavioral markers to enhance the detection and prediction of STBs., Objective: The paper presents the protocol for a systematic review that aims to summarize existing research on passive sensing of STBs and evaluate whether the STB prediction can be improved using passive sensing compared to prior prediction models., Methods: A systematic search will be conducted in the scientific databases MEDLINE, PubMed, Embase, PsycINFO, and Web of Science. Eligible studies need to investigate any passive sensor data from smartphones or wearables to predict STBs. The predictive value of passive sensing will be the primary outcome. The practical implications and feasibility of the studies will be considered as secondary outcomes. Study quality will be assessed using the Prediction Model Risk of Bias Assessment Tool (PROBAST). If studies are sufficiently homogenous, we will conduct a meta-analysis of the predictive value of passive sensing on STBs., Results: The review process started in July 2022 with data extraction in September 2022. Results are expected in December 2022., Conclusions: Despite intensive research efforts, the ability to predict STBs is little better than chance. This systematic review will contribute to our understanding of the potential of passive sensing to improve STB prediction. Future research will be stimulated since gaps in the current literature will be identified and promising next steps toward clinical implementation will be outlined., Trial Registration: OSF Registries osf-registrations-hzxua-v1; https://osf.io/hzxua., International Registered Report Identifier (irrid): DERR1-10.2196/42146., (©Tanita Winkler, Rebekka Büscher, Mark Erik Larsen, Sam Kwon, John Torous, Joseph Firth, Lasse B Sander. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 29.11.2022.)

Background: Gastrointestinal diseases are associated with substantial cost in health care. In times of the COVID-19 pandemic and further digitalization of gastrointestinal tract health care, mobile health apps could complement routine health care. Many gastrointestinal health care apps are already available in the app stores, but the quality, data protection, and reliability often remain unclear., Objective: This systematic review aimed to evaluate the quality characteristics as well as the privacy and security measures of mobile health apps for the management of gastrointestinal diseases., Methods: A web crawler systematically searched for mobile health apps with a focus on gastrointestinal diseases. The identified mobile health apps were evaluated using the Mobile Application Rating Scale (MARS). Furthermore, app characteristics, data protection, and security measures were collected. Classic user star rating was correlated with overall mobile health app quality., Results: The overall quality of the mobile health apps (N=109) was moderate (mean 2.90, SD 0.52; on a scale ranging from 1 to 5). The quality of the subscales ranged from low (mean 1.89, SD 0.66) to good (mean 4.08, SD 0.57). The security of data transfer was ensured only by 11 (10.1%) mobile health apps. None of the mobile health apps had an evidence base. The user star rating did not correlate with the MARS overall score or with the individual subdimensions of the MARS (all P>.05)., Conclusions: Mobile health apps might have a positive impact on diagnosis, therapy, and patient guidance in gastroenterology in the future. We conclude that, to date, data security and proof of efficacy are not yet given in currently available mobile health apps., (©Eva-Maria Messner, Niklas Sturm, Yannik Terhorst, Lasse B Sander, Dana Schultchen, Alexandra Portenhauser, Simone Schmidbaur, Michael Stach, Jochen Klaus, Harald Baumeister, Benjamin M Walter. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 05.10.2022.)

Introduction: The efficacy and effectiveness of digital interventions for depression are both well-established. However, precise effect size estimates for mediators transmitting the effects of digital interventions are not available; and integrative insights on the specific mechanisms of change in internet- and mobile-based interventions (IMIs)-as related to key features like delivery type, accompanying support and theoretical foundation-are largely pending., Objective: We will conduct a systematic review and individual participant data meta-analysis (IPD-MA) evaluating the mediators associated with therapeutic change in various IMIs for depression in adults., Methods: We will use three electronic databases (i.e., Embase, Medline/PubMed, PsycINFO) as well as an already established database of IPD to identify relevant published and unpublished studies. We will include (1) randomized controlled trials that examine (2) mediators of (3) guided and unguided (4) IMIs with (5) various theoretical orientations for (6) adults with (7) clinically relevant symptoms of depression (8) compared to an active or passive control condition (9) with depression symptom severity as primary outcome. Study selection, data extraction, as well as quality and risk of bias (RoB) assessment will be done independently by two reviewers. Corresponding authors of eligible primary studies will be invited to share their IPD for this meta-analytic study. In a 1-stage IPD-MA, mediation analyses (e.g., on potential mediators like self-efficacy, emotion regulation or problem solving) will be performed using a multilevel structural equation modeling approach within a random-effects framework. Indirect effects will be estimated, with multiple imputation for missing data; the overall model fit will be evaluated and statistical heterogeneity will be assessed. Furthermore, we will investigate if indirect effects are moderated by different variables on participant- (e.g., age, sex/gender, symptom severity), study- (e.g., quality, studies evaluating the temporal ordering of changes in mediators and outcomes), and intervention-level (e.g., theoretical foundation, delivery type, guidance)., Discussion: This systematic review and IPD-MA will generate comprehensive information on the differential strength of mediators and associated therapeutic processes in digital interventions for depression. The findings might contribute to the empirically-informed advancement of psychotherapeutic interventions, leading to more effective interventions and improved treatment outcomes in digital mental health. Besides, with our novel approach to mediation analyses with IPD-MA, we might also add to a methodological progression of evidence-synthesis in psychotherapy process research., Study Registration With Open Science Framework Osf: https://osf.io/md7pq/., Competing Interests: MD reports to have received fees for lectures and workshops for different psychotherapy training institutes. LS reports to have received personal fees from psychotherapy training institutes, health insurance companies, and clinic providers in the context of e-mental-health outside the submitted work. DE reports to have received consultancy fees or served in the scientific advisory board from several companies such as Novartis, Sanofi, Lantern, Schön Kliniken, Minddistrict, and German health insurance companies BARMER, Techniker Krankenkasse. DE is stakeholder of the Institute for Health Trainings Online GET.ON, which aims to implement scientific findings related to digital health interventions into routine care. HB reports to have received consultancy fees, fees for lectures or workshops from chambers of psychotherapists and training institutes for psychotherapists and license fees for an Internet-intervention. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer KM declared a past collaboration with the authors DE and EK to the handling editor., (Copyright © 2022 Domhardt, Grund, Mayer, Büscher, Ebert, Sander, Karyotaki, Cuijpers and Baumeister.)

Background: Depression is a common comorbid condition in individuals with chronic back pain (CBP), leading to poorer treatment outcomes and increased medical complications. Digital interventions have demonstrated efficacy in the prevention and treatment of depression; however, high dropout rates are a major challenge, particularly in clinical settings., Objective: This study aims to identify the predictors of dropout in a digital intervention for the treatment and prevention of depression in patients with comorbid CBP. We assessed which participant characteristics may be associated with dropout and whether intervention usage data could help improve the identification of individuals at risk of dropout early on in treatment., Methods: Data were collected from 2 large-scale randomized controlled trials in which 253 patients with a diagnosis of CBP and major depressive disorder or subclinical depressive symptoms received a digital intervention for depression. In the first analysis, participants' baseline characteristics were examined as potential predictors of dropout. In the second analysis, we assessed the extent to which dropout could be predicted from a combination of participants' baseline characteristics and intervention usage variables following the completion of the first module. Dropout was defined as completing <6 modules. Analyses were conducted using logistic regression., Results: From participants' baseline characteristics, lower level of education (odds ratio [OR] 3.33, 95% CI 1.51-7.32) and both lower and higher age (a quadratic effect; age: OR 0.62, 95% CI 0.47-0.82, and age 2 : OR 1.55, 95% CI 1.18-2.04) were significantly associated with a higher risk of dropout. In the analysis that aimed to predict dropout following completion of the first module, lower and higher age (age: OR 0.60, 95% CI 0.42-0.85; age 2 : OR 1.59, 95% CI 1.13-2.23), medium versus high social support (OR 3.03, 95% CI 1.25-7.33), and a higher number of days to module completion (OR 1.05, 95% CI 1.02-1.08) predicted a higher risk of dropout, whereas a self-reported negative event in the previous week was associated with a lower risk of dropout (OR 0.24, 95% CI 0.08-0.69). A model that combined baseline characteristics and intervention usage data generated the most accurate predictions (area under the receiver operating curve [AUC]=0.72) and was significantly more accurate than models based on baseline characteristics only (AUC=0.70) or intervention usage data only (AUC=0.61). We found no significant influence of pain, disability, or depression severity on dropout., Conclusions: Dropout can be predicted by participant baseline variables, and the inclusion of intervention usage variables may improve the prediction of dropout early on in treatment. Being able to identify individuals at high risk of dropout from digital health interventions could provide intervention developers and supporting clinicians with the ability to intervene early and prevent dropout from occurring., (©Isaac Moshe, Yannik Terhorst, Sarah Paganini, Sandra Schlicker, Laura Pulkki-Råback, Harald Baumeister, Lasse B Sander, David Daniel Ebert. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 30.08.2022.)

Background: Depression and comorbid chronic back pain (CBP) lead to high personal and economic burden. Internet- and mobile-based interventions (IMI) might be a cost-effective adjunct to established interventions., Methods: A health economic evaluation was embedded into an observer-blinded, multicenter RCT (societal and health care perspective). We randomly assigned participants (≥18 years) with CBP and diagnosed depression from 82 orthopedic clinics across Germany to intervention (IG + treatment as usual [TAU]) or TAU control group (CG). The IG received a guided IMI. Primary outcomes were depression response and quality-adjusted life years (QALYs) at 6-months follow-up. Multiple imputation was used to address missing data. Incremental cost-effectiveness/cost-utility ratios (ICER/ICUR) and the probability of being cost-effective at different willingness-to-pay thresholds were calculated. Statistical uncertainty was estimated using bootstrapping techniques (N = 10,000)., Results: Between October 2015 and July 2017 210 participants were randomly assigned to IG (n = 105) and CG (n = 105). Depression response did not differ significantly between groups. QALYs were significantly higher in the IG compared to the CG. Taking the societal perspective and assuming a commonly used willingness-to-pay of €34,000/QALY, the intervention's likelihood of being cost-effective was 64%., Limitations: The main limitation is that the study was powered to detect clinical but not health economic differences between groups., Conclusion: The IMI is considered cost-effective (vs. CG) for individuals with depression and CBP (societal perspective). These results are promising when considering the high individual and economic burden of this patient group. Further research is needed to adequately inform political decision makers before implementation into routine care., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Mobile health apps (MHAs) may offer a mean to overcome treatment barriers in Borderline Personality Disorder (BPD) mental health care. However, MHAs for BPD on the market lack transparency and quality assessment., Methods: European app stores were systematically searched, and two independent trained reviewers extracted relevant MHAs. Employed methods and privacy and security details documentation of included MHAs were extracted. MHAs were then assessed and rated using the German version of the standardized Mobile Application Rating Scale (MARS-G). Mean values and standard deviations of all subscales (engagement, functionality, aesthetics, information, and therapeutic gain) and correlations with user ratings were calculated., Results: Of 2977 identified MHAs, 16 were included, showing average quality across the four main subscales (M = 3.25, SD = 0.68). Shortcomings were observed with regard to engagement (M = 2.87, SD = 0.99), potential therapeutic gain (M = 2.67, SD = 0.83), existing evidence base (25.0% of included MHAs were tested empirically), and documented privacy and security details. No significant correlations were found between user ratings and the overall total score of the MARS-G or MARS-G main subscales., Conclusions: Available MHAs for BPD vary in quality and evidence on their efficacy, effectiveness, and possible adverse events is scarce. More substantial efforts to ensure the quality of MHAs available for patients and a focus on transparency, particularly regarding privacy and security documentation, are necessary., (© 2022. The Author(s).)

Sleep difficulties are widespread among international students. Internet-based interventions are suggested as a low-threshold treatment option but may require cultural adaptation among culturally diverse populations. The present pilot study investigated the effectiveness and acceptance of an internet-based intervention to improve sleep difficulties in international students. A total of 81 international students of 36 nationalities were randomly assigned to the intervention (n = 41) or waitlist control group (n = 40). The intervention group received immediate access to a culturally non-adapted unguided internet-based sleep intervention consisting of three modules based on sleep hygiene and cognitive techniques to reduce rumination. At baseline, 4 and 12 weeks after randomisation, insomnia severity, measured by the Insomnia Severity Index, and secondary outcomes (sleep quality, depression, anxiety, perceived stress, well-being, presenteeism, mental health literacy) were assessed. Data were analysed using linear multi-level analyses. Additionally, satisfaction and perceived cultural appropriateness of the intervention were evaluated by international students after 4 weeks, and compared with ratings of German students, who represent the original target group. Insomnia severity improved over time in the intervention group compared to the control group, revealing a significant estimated mean difference of -5.60 (Hedges' g = 0.84, p < 0.001) after 12 weeks. Satisfaction and perceived cultural appropriateness was high and comparable to that of German students. The present study shows that a culturally non-adapted internet-based sleep intervention can be a low-threshold treatment option to help meet the high demand for mental healthcare among international students. It thus indicates that cultural adaptation might not represent a precondition for providing effective internet-based sleep interventions to this target group., (© 2021 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Health promotion interventions offer great potential in advocating a healthy lifestyle and the prevention of diseases. Some barriers to communicating health promotion to people of certain cultural groups might be overcome via the internet- and mobile-based interventions (IMI). This systematic review and meta-analysis aims to explore the effectiveness of culturally adapted IMI for health promotion interventions among culturally diverse populations. We systematically searched on Cochrane Central Register of Controlled Trials (CENTRAL), EbscoHost/MEDLINE, Ovid/Embase, EbscoHost/PsychINFO, and Web of Science databases in October 2020. Out of 9438 records, 13 randomized controlled trials (RCT) investigating culturally adapted health promotion IMI addressing healthy eating, physical activity, alcohol consumption, sexual health behavior, and smoking cessation included. From the included studies 10,747 participants were eligible. Culturally adapted IMI proved to be non-superior over active control conditions in short- (g = 0.10, [95% CI -0.19 to 0.40]) and long-term (g = 0.20, [95% CI -0.11 to 0.51]) in promoting health behavior. However, culturally adapted IMI for physical activity (k = 3, N = 296) compared to active controls yielded a beneficial effect in long-term (g = 0.48, [95%CI 0.25 to 0.71]). Adapting health promotion IMI to the cultural context of different cultural populations seems not yet to be recommendable given the substantial adaption efforts necessary and the mostly non-significant findings. However, these findings need to be seen as preliminary given the limited number of included trials with varying methodological rigor and the partly substantial between-trial heterogeneity pointing in the direction of potentially useful culturally adapted IMI which now need to be disentangled from the less promising approaches.PROSPERO registration number: 42020152939., (© 2022. The Author(s).)

This study evaluates diabetes self-management mobile health applications available from European app stores with respect to quality, concordance with recommended self-management tasks and implementation of persuasive system design principles. The European Play Store and Apple App Store were systematically searched and relevant apps were tested. Two raters independently assessed app quality using the Mobile Application Rating Scale and conducted a content analysis of provided persuasive system design principles and self-management tasks. A total of 2,269 mobile health applications were identified and 120 could be included in the evaluation. The overall quality was rated as moderate M = 3.20 (SD = 0.39, min = 2.31, max = 4.62), with shortcomings in the subcategories of engagement (M = 2.80, SD = 0.67) and information quality (M = 2.26, SD = 0.48). Scientific evidence is available for 8% of the apps. The reviewed apps implemented a median of three persuasive system design principles (range 0-15) and targeted a median of 4.5 (range 1-8) self-management tasks, however, with a lack of information about psychosocial coping strategies. Most available diabetes self-management apps lack a scientific evidence base. Persuasive system design features are underrepresented and may form a promising tool to improve app quality. Furthermore, the interaction of physical and behavioral health should be improved in existing diabetes self-management mobile health applications., (© 2022. The Author(s).)

Refugees are exposed to multiple stressors affecting their mental health. Given various barriers to mental healthcare in the arrival countries, innovative healthcare solutions are needed. One such solution could be to offer low-threshold treatments, for example by culturally adapting treatments, providing them in a scalable format, and addressing transdiagnostic symptoms. This pilot trial examined the feasibility, acceptance, and preliminary effectiveness of a culturally adapted digital sleep intervention for refugees. Sixty-six refugees participated, with 68.2% of them seeking psychological help for the first time. Only three participants did not show clinically significant insomnia severity, 93.9% reported past traumatic experiences. Participants were randomly assigned to the intervention group (IG) or the waitlist control group (CG). Insomnia severity, measured by the Insomnia Severity Index, and secondary outcomes (sleep quality, fear of sleep, fatigue, depression, wellbeing, mental health literacy) were assessed at baseline, 1 and 3 months after randomization. The self-help intervention included four modules on sleep hygiene, rumination, and information on mental health conditions associated with sleep disturbances. 66.7% of the IG completed all modules. Satisfaction with the intervention and its perceived cultural appropriateness were high. Linear multilevel analyses revealed a small, non-significant intervention effect on insomnia severity of Hedge's g = 0.28 at 3-months follow-up, comparing the IG to the CG [ F 2, 60 = 0.88, p = 0.421]. This non-confirmatory pilot trial suggests that low-threshold, viable access to mental healthcare can be offered to multiple burdened refugees by culturally adapting an intervention, providing it in a scalable format, and addressing a transdiagnostic symptom., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Spanhel, Hovestadt, Lehr, Spiegelhalder, Baumeister, Bengel and Sander.)

Background: Mindfulness-based interventions show positive effects on physical and mental health. For a better integration of mindfulness techniques in daily life, the use of apps may be promising. However, only a few studies have examined the quality of mindfulness apps using a validated standardized instrument. This review aims to evaluate the content, quality, and privacy features of mindfulness-focused apps from European commercial app stores., Methods: An automated search engine (webcrawler) was used to identify mindfulness-focused apps in the European Apple App- and Google Play store. Content, quality, and privacy features were evaluated by two independent reviewers using the Mobile Application Rating Scale (MARS). The MARS assesses the subscales engagement, functionality, aesthetics, and information quality., Results: Out of 605 identified apps, 192 met the inclusion criteria. The overall quality was moderate (M = 3.66, SD = 0.48). Seven apps were tested in a randomized controlled trial (RCT). Most of the apps showed a lack of data security and no privacy policy. The five apps with the highest ratings are from a credible source, include a privacy policy, and are also based on standardized mindfulness and behavior change techniques., Conclusions: The plethora of often low-quality apps in commercial app stores makes it difficult for users to identify a suitable app. Above that, the lack of scientific verification of effectiveness and shortcomings in privacy protection and security poses potential risks. So far, the potential of mindfulness-focused apps is not exploited in commercial app stores., (© 2020. The Author(s).)

Competing Interests: Die Autor*innen geben an, dass kein Interessenskonflikt besteht.

For patients with coronary heart disease (CHD) lifestyle changes and disease management are key aspects of treatment that could be facilitated by mobile health applications (MHA). However, the quality and functions of MHA for CHD are largely unknown, since reviews are missing. Therefore, this study assessed the general characteristics, quality, and functions of MHA for CHD. Hereby, the Google Play and Apple App stores were systematically searched using a web crawler. The general characteristics and quality of MHA were rated with the Mobile Application Rating Scale (MARS) by two independent raters. From 3078 identified MHA, 38 met the pre-defined criteria and were included in the assessment. Most MHA were affiliated with commercial companies (52.63%) and lacked an evidence-base. An overall average quality of MHA ( M = 3.38, SD = 0.36) was found with deficiencies in information quality and engagement. The most common functions were provision of information and CHD risk score calculators. Further functions included reminders (e.g., for medication or exercises), feedback, and health management support. Most MHA (81.58%) had one or two functions and MHA with more features had mostly higher MARS ratings. In summary, this review demonstrated that a number of potentially helpful MHA for patients with CHD are commercially available. However, there is a lack of scientific evidence documenting their usability and clinical potential. Since it is difficult for patients and healthcare providers to find suitable and high-quality MHA, databases with professionally reviewed MHA are required.

Background: The access to empirically-supported treatments for common mental disorders in children and adolescents is often limited. Mental health apps might extend service supplies, as they are deemed to be cost-efficient, scalable and appealing for youth. However, little is known about the quality of available apps. Therefore, we aimed to systematically evaluate current mobile-based interventions for pediatric anxiety, depression and posttraumatic stress disorder (PTSD)., Methods: Systematic searches were conducted in Google Play Store and Apple App Store to identify relevant apps. To be eligible for inclusion, apps needed to be: (1) designed to target either anxiety, depression or PTSD in youth (0-18 years); (2) developed for children, adolescents or caregivers; (3) provided in English or German; (4) operative after download. The quality of eligible apps was assessed with two standardized rating systems (i.e., Mobile App Rating Scale (MARS) and ENLIGHT) independently by two reviewers., Results: Overall, the searches revealed 3806 apps, with 15 mental health apps (0.39%) fulfilling our inclusion criteria. The mean overall scores suggested a moderate app quality (MARS: M = 3.59, SD = 0.50; ENLIGHT: M = 3.22, SD = 0.73). Moreover, only one app was evaluated in an RCT. The correlation of both rating scales was high (r = .936; p < .001), whereas no significant correlations were found between rating scales and user ratings (p > .05)., Conclusions: Our results point to a rather poor overall app quality, and indicate an absence of scientific-driven development and lack of methodologically sound evaluation of apps. Thus, future high-quality research is required, both in terms of theoretically informed intervention development and assessment of mental health apps in RCTs. Furthermore, institutionalized best-practices that provide central information on different aspects of apps (e.g., effectiveness, safety, and data security) for patients, caregivers, stakeholders and mental health professionals are urgently needed., (© 2021. The Author(s).)

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., (© 2021. The Author(s).)

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).

People with suicidal ideation and non-suicidal self-injury (NSSI) behavior face numerous barriers to help-seeking, which worsened during the COVID-19 pandemic. Mobile health applications (MHA) are discussed as one solution to improve healthcare. However, the commercial app markets are growing unregulated and rapidly, leading to an inscrutable market. This study evaluates the quality, features, functions, and prevention strategies of MHA for people with suicidal ideation and NSSI. An automatic search engine identified MHA for suicidal behavior and NSSI in the European commercial app stores. MHA quality and general characteristics were assessed using the Mobile Application Rating Scale (MARS). MHA of high quality (top 25%) were examined in detail and checked for consistency with established suicide prevention strategies. Of 10,274 identified apps, 179 MHA met the predefined inclusion criteria. Average MHA quality was moderate (M = 3.56, SD = 0.40 ) . Most MHA provided emergency contact, but lacked security features. High-quality MHA were broadly consistent with the best-practice guidelines. The search revealed apps containing potentially harmful and triggering content, and no randomized controlled trial of any included MHA was found. Despite a large heterogeneity in the quality of MHA, high-quality MHA for suicidal behavior and NSSI are available in European commercial app stores. However, a lack of a scientific evidence base poses potential threats to users., Competing Interests: LS, E-MM, HB, and YT developed and run the German Mobile Health App Database (MHAD) project. The MHAD is a self-funded project at Ulm University without commercial interests. HB, LS, and E-MM received payments for talks and workshops in the context of e-mental-health. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Sander, Lemor, Van der Sloot, De Jaegere, Büscher, Messner, Baumeister and Terhorst.)

Background: Physical inactivity is a major contributor to the development and persistence of chronic diseases. Mobile health apps that foster physical activity have the potential to assist in behavior change. However, the quality of the mobile health apps available in app stores is hard to assess for making informed decisions by end users and health care providers., Objective: This study aimed at systematically reviewing and analyzing the content and quality of physical activity apps available in the 2 major app stores (Google Play and App Store) by using the German version of the Mobile App Rating Scale (MARS-G). Moreover, the privacy and security measures were assessed., Methods: A web crawler was used to systematically search for apps promoting physical activity in the Google Play store and App Store. Two independent raters used the MARS-G to assess app quality. Further, app characteristics, content and functions, and privacy and security measures were assessed. The correlation between user star ratings and MARS was calculated. Exploratory regression analysis was conducted to determine relevant predictors for the overall quality of physical activity apps., Results: Of the 2231 identified apps, 312 met the inclusion criteria. The results indicated that the overall quality was moderate (mean 3.60 [SD 0.59], range 1-4.75). The scores of the subscales, that is, information (mean 3.24 [SD 0.56], range 1.17-4.4), engagement (mean 3.19 [SD 0.82], range 1.2-5), aesthetics (mean 3.65 [SD 0.79], range 1-5), and functionality (mean 4.35 [SD 0.58], range 1.88-5) were obtained. An efficacy study could not be identified for any of the included apps. The features of data security and privacy were mainly not applied. Average user ratings showed significant small correlations with the MARS ratings (r=0.22, 95% CI 0.08-0.35; P<.001). The amount of content and number of functions were predictive of the overall quality of these physical activity apps, whereas app store and price were not., Conclusions: Apps for physical activity showed a broad range of quality ratings, with moderate overall quality ratings. Given the present privacy, security, and evidence concerns inherent to most rated apps, their medical use is questionable. There is a need for open-source databases of expert quality ratings to foster informed health care decisions by users and health care providers., (©Sarah Paganini, Yannik Terhorst, Lasse Bosse Sander, Selma Catic, Sümeyye Balci, Ann-Marie Küchler, Dana Schultchen, Katrin Plaumann, Sarah Sturmbauer, Lena Violetta Krämer, Jiaxi Lin, Ramona Wurst, Rüdiger Pryss, Harald Baumeister, Eva-Maria Messner. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 09.06.2021.)

Background and Objective: Pain spans a broad spectrum of diseases and types that are highly prevalent and cause substantial disease burden for individuals and society. Up to 40% of people affected by pain receive no or inadequate treatment. Providing a scalable, time-, and location-independent way for pain diagnostic, management, prevention and treatment mobile health applications (MHA) might be a promising approach to improve health care for pain. However, the commercial app market is rapidly growing and unregulated, resulting in an opaque market. Studies investigating the content, privacy and security features, quality and scientific evidence of the available apps are highly needed, to guide patients and clinicians to high quality MHA.Contributing to this challenge, the present study investigates the content, quality, and privacy features of pain apps available in the European app stores., Methods: An automated search engine was used to identify pain apps in the European Google Play and Apple App store. Pain apps were screened and checked for systematic criteria (pain-relatedness, functionality, availability, independent usability, English or German). Content, quality and privacy features were assessed by two independent reviewers using the German Mobile Application Rating Scale (MARS-G). The MARS-G assesses quality on four objectives (engagement, functionality, aesthetics, information quality) and two subjective scales (perceived impact, subjective quality)., Results: Out of 1034 identified pain apps 218 were included. Pain apps covered eight different pain types. Content included basic information, advice, assessment and tracking, and stand-alone interventions. The overall quality of the pain apps was average M = 3.13 (SD = 0.56, min = 1, max = 4.69). The effectiveness of less than 1% of the included pain apps was evaluated in a randomized controlled trial. Major problems with data privacy were present: 59% provided no imprint, 70% had no visible privacy policy., Conclusion: A multitude of pain apps is available. Most MHA lack scientific evaluation and have serious privacy issues, posing a potential threat to users. Further research on evidence and improvements privacy and security are needed. Overall, the potential of pain apps is not exploited., Competing Interests: EMM, YT, LS, HB developed and run the German Mobile Health App Database project. The MHAD is a self-funded project at Ulm University with no commercial interests. HB, LS and EMM received payments for talks and workshops in the context of e-mental-health. All other authors declare no conflict of interest., (© 2021 The Authors. Published by Elsevier B.V.)

Background: Through the increasingly aging population, the health care system is confronted with various challenges such as expanding health care costs. To manage these challenges, mobile apps may represent a cost-effective and low-threshold approach to support older adults., Objective: This systematic review aimed to evaluate the quality, characteristics, as well as privacy and security measures of mobile apps for older adults in the European commercial app stores., Methods: In the European Google Play and App Store, a web crawler systematically searched for mobile apps for older adults. The identified mobile apps were evaluated by two independent reviewers using the German version of the Mobile Application Rating Scale. A correlation between the user star rating and overall rating was calculated. An exploratory regression analysis was conducted to determine whether the obligation to pay fees predicted overall quality., Results: In total, 83 of 1217 identified mobile apps were included in the analysis. Generally, the mobile apps for older adults were of moderate quality (mean 3.22 [SD 0.68]). Four mobile apps (5%) were evidence-based; 49% (41/83) had no security measures. The user star rating correlated significantly positively with the overall rating (r=.30, P=.01). Obligation to pay fees could not predict overall quality., Conclusions: There is an extensive quality range within mobile apps for older adults, indicating deficits in terms of information quality, data protection, and security precautions, as well as a lack of evidence-based approaches. Central databases are needed to identify high-quality mobile apps., (©Alexandra A Portenhauser, Yannik Terhorst, Dana Schultchen, Lasse B Sander, Michael D Denkinger, Michael Stach, Natalie Waldherr, Dhayana Dallmeier, Harald Baumeister, Eva-Maria Messner. Originally published in JMIR Aging (http://aging.jmir.org), 19.02.2021.)

Background: Depression and anxiety are leading causes of disability worldwide but often remain undetected and untreated. Smartphone and wearable devices may offer a unique source of data to detect moment by moment changes in risk factors associated with mental disorders that overcome many of the limitations of traditional screening methods. Objective: The current study aimed to explore the extent to which data from smartphone and wearable devices could predict symptoms of depression and anxiety. Methods: A total of N = 60 adults (ages 24-68) who owned an Apple iPhone and Oura Ring were recruited online over a 2-week period. At the beginning of the study, participants installed the Delphi data acquisition app on their smartphone. The app continuously monitored participants' location (using GPS) and smartphone usage behavior (total usage time and frequency of use). The Oura Ring provided measures related to activity (step count and metabolic equivalent for task), sleep (total sleep time, sleep onset latency, wake after sleep onset and time in bed) and heart rate variability (HRV). In addition, participants were prompted to report their daily mood (valence and arousal). Participants completed self-reported assessments of depression, anxiety and stress (DASS-21) at baseline, midpoint and the end of the study. Results: Multilevel models demonstrated a significant negative association between the variability of locations visited and symptoms of depression (beta = -0.21, p = 0.037) and significant positive associations between total sleep time and depression (beta = 0.24, p = 0.023), time in bed and depression (beta = 0.26, p = 0.020), wake after sleep onset and anxiety (beta = 0.23, p = 0.035) and HRV and anxiety (beta = 0.26, p = 0.035). A combined model of smartphone and wearable features and self-reported mood provided the strongest prediction of depression. Conclusion: The current findings demonstrate that wearable devices may provide valuable sources of data in predicting symptoms of depression and anxiety, most notably data related to common measures of sleep., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Moshe, Terhorst, Opoku Asare, Sander, Ferreira, Baumeister, Mohr and Pulkki-Råback.)

Introduction: There is neither strong evidence on effective treatments for patients with chronic back pain (CBP) and depressive disorder nor sufficiently available mental health care offers., Objective: The aim is to assess the effectiveness of internet- and mobile-based interventions (IMI) as a scalable approach for treating depression in a routine care setting., Methods: This is an observer-masked, multicenter, pragmatic randomized controlled trial with a randomization ratio of 1:1.Patients with CBP and diagnosed depressive disorder (mild to moderate severity) were recruited from 82 orthopedic rehabilitation clinics across Germany. The intervention group (IG) received a guided depression IMI tailored to CBP next to treatment-as-usual (TAU; including medication), while the control group (CG) received TAU. The primary outcome was observer-masked clinician-rated Hamilton depression severity (9-week follow-up). The secondary outcomes were: further depression outcomes, pain-related outcomes, health-related quality of life, and work capacity. Biostatistician blinded analyses using regression models were conducted by intention-to-treat and per protocol analysis., Results: Between October 2015 and July 2017, we randomly assigned 210 participants (IG, n = 105; CG, n = 105), mostly with only a mild pain intensity but substantial pain disability. No statistically significant difference in depression severity between IG and CG was observed at the 9-week follow-up (β = -0.19, 95% CI -0.43 to 0.05). Explorative secondary depression (4/9) and pain-related (4/6) outcomes were in part significant (p < 0.05). Health-related quality of life was significantly higher in the IG. No differences were found in work capacity., Conclusion: The results indicate that an IMI for patients with CBP and depression in a routine care setting has limited impact on depression. Benefits in pain and health-related outcomes suggest that an IMI might still be a useful measure to improve routine care., (© 2020 S. Karger AG, Basel.)

Background: Mobile health apps (MHA) have the potential to improve health care. The commercial MHA market is rapidly growing, but the content and quality of available MHA are unknown. Instruments for the assessment of the quality and content of MHA are highly needed. The Mobile Application Rating Scale (MARS) is one of the most widely used tools to evaluate the quality of MHA. Only few validation studies investigated its metric quality. No study has evaluated the construct validity and concurrent validity., Objective: This study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS., Methods: Data was pooled from 15 international app quality reviews to evaluate the metric properties of the MARS. The MARS measures app quality across four dimensions: engagement, functionality, aesthetics and information quality. Construct validity was evaluated by assessing related competing confirmatory models by confirmatory factor analysis (CFA). Non-centrality (RMSEA), incremental (CFI, TLI) and residual (SRMR) fit indices were used to evaluate the goodness of fit. As a measure of concurrent validity, the correlations to another quality assessment tool (ENLIGHT) were investigated. Reliability was determined using Omega. Objectivity was assessed by intra-class correlation., Results: In total, MARS ratings from 1,299 MHA covering 15 different health domains were included. Confirmatory factor analysis confirmed a bifactor model with a general factor and a factor for each dimension (RMSEA = 0.074, TLI = 0.922, CFI = 0.940, SRMR = 0.059). Reliability was good to excellent (Omega 0.79 to 0.93). Objectivity was high (ICC = 0.82). MARS correlated with ENLIGHT (ps<.05)., Conclusion: The metric evaluation of the MARS demonstrated its suitability for the quality assessment. As such, the MARS could be used to make the quality of MHA transparent to health care stakeholders and patients. Future studies could extend the present findings by investigating the re-test reliability and predictive validity of the MARS., Competing Interests: EMM, YT, LS, HB developed and run the German Mobile Health App Database project (MHAD). The MHAD is a self-funded project at Ulm University with no commercial interests. LS, HB and EMM received payments for talks and workshops in the context of e-mental-health. This does not alter our adherence to PLOS ONE policies on sharing data and materials. All other authors declare no conflicts of interest.

Importance: Depression is a frequent comorbid condition in patients with persistent back pain and is associated with substantial adverse consequences, including the risk of developing opioid use disorders. Shifting the focus from depression treatment to preventing depression might be a viable way to reduce the disease burden., Objective: To evaluate the effectiveness of a web-based self-help intervention to reduce the incidence of major depressive episode (MDE) in patients with persistent back pain., Design, Setting, and Participants: Prevention of Depression in Back Pain Patients (PROD-BP) was a pragmatic, observer-blinded randomized clinical trial with a parallel design conducted in Germany. Eligible adults with a diagnosis of persistent back pain and subclinical depressive symptoms, but who were depression free, were recruited either on-site or after discharge from 82 orthopedic clinics between October 1, 2015, and July 31, 2017. All analyses were conducted according to the intention-to-treat principle from October 31, 2018, to April 30, 2019., Interventions: The intervention group received an e-coach-guided, web-based self-help intervention that was based on cognitive behavioral therapy and tailored to the needs of patients with persistent back pain. The intervention included 6 obligatory modules and 3 optional modules to be completed by participants as well as feedback from e-coaches. Both the intervention and control groups had unrestricted access to treatment as usual., Main Outcomes and Measures: Primary outcome was time to onset of an MDE over a 12-month period as assessed by blinded diagnostic raters using the Structured Clinical Interview for DSM-5. Secondary outcomes included depression severity, quality of life, pain intensity, pain-related disability, pain self-efficacy, work capacity, and user satisfaction assessed with a variety of instruments., Results: A total of 295 participants (mean [SD] age, 52.8 [7.7] years; 184 women [62.4%]) were recruited and randomized to either the intervention group (n = 149) or control group (n = 146). The intervention reduced the risk of MDE onset by 52% (hazard ratio, 0.48; 95% CI, 0.28-0.81; P < .001). Twenty-one participants (14.1%) in the intervention group and 41 participants (28.1%) in the control group experienced an MDE over the 12-month period. The number needed to treat to prevent 1 new case of MDE was 2.84 (95% CI, 1.79-9.44)., Conclusions and Relevance: Results of this trial showed that among patients with persistent back pain, depression can be prevented by a guided web-based self-help intervention in addition to treatment as usual. This finding suggests that using a scalable digital approach to integrate psychological treatment into routine pain management is feasible., Trial Registration: German Clinical Trials Register Identifier: DRKS00007960.

Background: Internet- and mobile-based interventions (IMI) are an effective and scalable low-threshold solution to reach people who are undersupplied by current healthcare. Adapting interventions to the cultural and ethnic background of the target group enhances their acceptance and effectiveness. However, no systematic approach to cultural adaptation of IMI has been established so far. Therefore, this review aims to summarise components and procedures commonly used in the cultural adaptation of IMI for mental disorders, as well as the current evidence base on whether such a cultural adaptation leads to an increased acceptance, adherence, and effectiveness of IMI for mental disorders., Methods: A systematic literature search will be performed using the following databases: MEDLINE, Embase, PsycINFO, CENTRAL, and WoS. The search term will include keywords related to cultural adaptation, IMI, and mental disorders/disturbances. Two independent reviewers will evaluate studies against inclusion and exclusion criteria and extract study and intervention characteristics, details on the cultural adaptation approach, and outcome data. Quality of evidence will be assessed using the Quality Assessment Tool for Reviewing Studies with Diverse Designs, and results will be synthesised qualitatively., Discussion: Providing adequate mental healthcare regardless of cultural backgrounds is a major global health challenge. The planned systematic review will lay the foundation for the further development of the cultural adaptation of IMI for mental disorders by summarising the current state and providing recommendations for future research., Systematic Review Registration: PROSPERO CRD42019142320.

Internet- and mobile-based cognitive behavioral therapy (iCBT) might reduce suicidal ideation. However, recent meta-analyses found small effect sizes, and it remains unclear whether specific subgroups of participants experience beneficial or harmful effects. This is the study protocol for an individual participant meta-analysis (IPD-MA) aiming to determine the effectiveness of iCBT on suicidal ideation and identify moderators. We will systematically search CENTRAL, PsycINFO, Embase, and Pubmed for randomized controlled trials examining guided or self-guided iCBT for suicidality. All types of control conditions are eligible. Participants experiencing suicidal ideation will be included irrespective of age, diagnoses, or co-interventions. We will conduct a one-stage IPD-MA with suicidal ideation as the primary outcome, using a continuous measure, reliable improvement and deterioration, and response rate. Moderator analyses will be performed on participant-, study-, and intervention-level. Two independent reviewers will assess risk of bias and the quality of evidence using Cochrane's Risk of Bias Tool 2 and GRADE. This review was registered with OSF and is currently in progress. The IPD-MA will provide effect estimates while considering covariates and will offer novel insights into differential effects on a participant level. This will help to develop more effective, safe, and tailored digital treatment options for suicidal individuals.

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., (© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.)