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Abstract Background The risk of breast cancer patients for long-term side effects of therapy such as neurotoxicity and cardiotoxicity as well as late effects regarding comorbidities varies from individual to individual. Personalised follow-up care concepts that are tailored to individual needs and the risk of recurrences, side effects and late effects are lacking in routine care in Germany. Methods We describe the methodology of BETTER-CARE, a parallel-arm cluster-randomised controlled trial conducted at 15 intervention and 15 control centres, aiming to recruit 1140 patients, and the results of the pilot phase. The needs- and risk-adapted complex intervention, based on existing development frameworks, includes a multidisciplinary network and digital platforms for symptom and need documentation and just-in-time adaptive interventions. The control group comprises usual care according to clinical guidelines. The primary outcome is health-related quality of life (EORTC QLQ-C30 global health), and secondary outcomes include treatment adherence. Results The 2-month pilot phase comprising 16 patients in one intervention and one control pilot centre demonstrated the feasibility of the BETTER-CARE approach. Discussion BETTER-CARE is a feasible intervention and study concept, investigating individualised needs- and risk-adapted breast cancer follow-up care in Germany. If successful, the approach could be implemented in German routine care. Trial registration German Clinical Trial Register DRKS00028840. Registered on April 2022.

Abstract The challenge of sustaining user engagement in eHealth interventions is a pressing issue with significant implications for the effectiveness of these digital health tools. This study investigates user engagement in a cognitive-behavioral therapy-based eHealth intervention for procrastination, using a dataset from a randomized controlled trial of 233 university students. Various machine learning models, including Decision Tree, Gradient Boosting, Logistic Regression, Random Forest, and Support Vector Machines, were employed to predict patterns of user engagement. The study adopted a two-phase analytical approach. In the first phase, all features of the dataset were included, revealing ‘total_minutes’—the total time participants spent on the intervention and the eHealth platform—as the most significant predictor of engagement. This finding emphasizes the intuitive notion that early time spent on the platform and the intervention is a strong indicator of later user engagement. However, to gain a deeper understanding of engagement beyond this predominant metric, the second phase of the analysis excluded ‘total_minutes’. This approach allowed for the exploration of the roles and interdependencies of other engagement indicators, such as ‘number_intervention_answersheets’—the number of completed lessons, ‘logins_first_4_weeks’—login frequency, and ‘number_diary_answersheets’—the number of completed diaries. The results from this phase highlighted the multifaceted nature of engagement, showing that while ‘total_minutes’ is strongly correlated with engagement, indicating that more engaged participants tend to spend more time on the intervention, the comprehensive engagement profile also depends on additional aspects like lesson completions and frequency of platform interactions.

Objective This systematic review and meta-analysis evaluates the available evidence on efficacy of social support strategies, as defined by the persuasive system design framework, in internet-based and mobile-based interventions (IMI) targeting mental health.Design Systematic review and meta-analysis.Data sources PubMed, Embase, PsycINFO and the Cochrane Central Register of Controlled Trials.Eligibility criteria for selecting studies Randomised controlled trials comparing IMI implementing a social support strategy for mental health symptoms to various control conditions. Publications up to June 2023 (date of search 6 June 2023) were considered.Data extraction and synthesis Two independent reviewers screened and extracted data in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Risk of bias was assessed with the Risk of Bias Tool V.2.0. Data were pooled based on a random-effects model.Results After screening 6484 records, a total of 45 studies met our inclusion criteria. At 96%, social support was predominantly implemented through the strategy of social facilitation, by which users recognising others using the intervention (eg, discussion forum). IMI implementing social support strategies showed moderate effect sizes of Hedges’ g=−0.34 (95% CI −0.47 to −0.21, p

BackgroundThe objective, unobtrusively collected GPS features (eg, homestay and distance) from everyday devices like smartphones may offer a promising augmentation to current assessment tools for depression. However, to date, there is no systematic and meta-analytical evidence on the associations between GPS features and depression. ObjectiveThis study aimed to investigate the between-person and within-person correlations between GPS mobility and activity features and depressive symptoms, and to critically review the quality and potential publication bias in the field. MethodsWe searched MEDLINE, PsycINFO, Embase, CENTRAL, ACM, IEEE Xplore, PubMed, and Web of Science to identify eligible articles focusing on the correlations between GPS features and depression from December 6, 2022, to March 24, 2023. Inclusion and exclusion criteria were applied in a 2-stage inclusion process conducted by 2 independent reviewers (YT and JK). To be eligible, studies needed to report correlations between wearable-based GPS variables (eg, total distance) and depression symptoms measured with a validated questionnaire. Studies with underage persons and other mental health disorders were excluded. Between- and within-person correlations were analyzed using random effects models. Study quality was determined by comparing studies against the STROBE (Strengthening the Reporting of Observational studies in Epidemiology) guidelines. Publication bias was investigated using Egger test and funnel plots. ResultsA total of k=19 studies involving N=2930 participants were included in the analysis. The mean age was 38.42 (SD 18.96) years with 59.64% (SD 22.99%) of participants being female. Significant between-person correlations between GPS features and depression were identified: distance (r=–0.25, 95% CI –0.29 to –0.21), normalized entropy (r–0.17, 95% CI –0.29 to –0.04), location variance (r–0.17, 95% CI –0.26 to –0.04), entropy (r=–0.13, 95% CI –0.23 to –0.04), number of clusters (r=–0.11, 95% CI –0.18 to –0.03), and homestay (r=0.10, 95% CI 0.00 to 0.19). Studies reporting within-correlations (k=3) were too heterogeneous to conduct meta-analysis. A deficiency in study quality and research standards was identified: all studies followed exploratory observational designs, but no study referenced or fully adhered to the international guidelines for reporting observational studies (STROBE). A total of 79% (k=15) of the studies were underpowered to detect a small correlation (r=.20). Results showed evidence for potential publication bias. ConclusionsOur results provide meta-analytical evidence for between-person correlations of GPS mobility and activity features and depression. Hence, depression diagnostics may benefit from adding GPS mobility and activity features as an integral part of future assessment and expert tools. However, confirmatory studies for between-person correlations and further research on within-person correlations are needed. In addition, the methodological quality of the evidence needs to improve. Trial RegistrationOSF Registeries cwder; https://osf.io/cwder

BackgroundSpecialized studies have shown that smartphone-based social interaction data are predictors of depressive and anxiety symptoms. Moreover, at times during the COVID-19 pandemic, social interaction took place primarily remotely. To appropriately test these objective data for their added value for epidemiological research during the pandemic, it is necessary to include established predictors. ObjectiveUsing a comprehensive model, we investigated the extent to which smartphone-based social interaction data contribute to the prediction of depressive and anxiety symptoms, while also taking into account well-established predictors and relevant pandemic-specific factors. MethodsWe developed the Corona Health App and obtained participation from 490 Android smartphone users who agreed to allow us to collect smartphone-based social interaction data between July 2020 and February 2021. Using a cross-sectional design, we automatically collected data concerning average app use in terms of the categories video calls and telephony, messenger use, social media use, and SMS text messaging use, as well as pandemic-specific predictors and sociodemographic covariates. We statistically predicted depressive and anxiety symptoms using elastic net regression. To exclude overfitting, we used 10-fold cross-validation. ResultsThe amount of variance explained (R2) was 0.61 for the prediction of depressive symptoms and 0.57 for the prediction of anxiety symptoms. Of the smartphone-based social interaction data included, only messenger use proved to be a significant negative predictor of depressive and anxiety symptoms. Video calls were negative predictors only for depressive symptoms, and SMS text messaging use was a negative predictor only for anxiety symptoms. ConclusionsThe results show the relevance of smartphone-based social interaction data in predicting depressive and anxiety symptoms. However, even taken together in the context of a comprehensive model with well-established predictors, the data only add a small amount of value.

This systematic review aimed to synthesize evidence on predictors and moderators of treatment outcomes in internet- and mobile-based interventions (IMIs) for depression, informing personalized care. A systematic search across PubMed, PsycInfo, and Cochrane yielded 33,002 results. Two reviewers independently performed screening, data extraction, risk of bias assessment, and methodological quality evaluation. Fifty-eight single studies (m = 466 analyses) focusing on baseline-predictors (59.7 %, m = 278), process-predictors (16.5 %, m = 77), and moderators (21.9 %, m = 102), and six individual patient data meta-analyses (m = 93) were included. Only 24.0 % (m = 112/466) of analyses in single studies and 15.1 % (m = 14/93) in individual patient data meta-analyses were significant. Evidence from single studies was rated as insufficient for all variable categories with only 2 out of 40 categories showing >50 % significant results. Baseline depression severity had the strongest predictive value with higher scores linked to better outcomes followed by variables indicative for the course-of-change. Other frequently analyzed and potentially relevant variables with significant results were adherence, age, educational level, ethnicity, relationship status, treatment history, and behavioral variables. More high quality quantitative studies with sufficient power are essential to validate and expand findings, identifying predictors and moderators specifically relevant in IMIs to explain differential treatment effects.

Abstract Background Counselling adolescents with chronic medical conditions (CMCs) can be challenging regarding suitable interviewing skills and clinicians’ attitudes toward the patient. Successful communication can be a key element of treatment. Motivational Interviewing (MI) is broadly applicable in managing behavioural problems and diseases by increasing patient motivation for lifestyle changes. However, data concerning the applicability, feasibility and implementation of MI sessions in everyday practice are missing from the physicians’ point of view. Method The present study was conducted as a mixed methods design. Twenty paediatricians were randomized to a 2-day MI course followed by MI consultations. Data were collected through a questionnaire one year after MI training. Factors for effective training and possible barriers to successful use of MI were examined. Results Completed questionnaires were returned by 19 of 20 paediatricians. The paediatricians’ experiences with MI demonstrate that MI is regarded as a valuable tool when working with adolescents with CMCs. 95% of all respondents reported that they found MI education necessary for their clinical work and were using it also outside the COACH-MI study context. 73.7% percent saw potential to strengthen the connection to their patients by using MI. The doctors were already using more MI conversation techniques after a 2-day MI course. Obstacles were seen in the short training, the lack of time and missing undisturbed environment (interruptions by telephone, staff, etc.) during clinical flow. Conclusions MI techniques are not yet a regular part of medical training. However, a 2-day MI course was rated effective and provided a lasting impact by physicians caring for children and adolescents with chronic medical conditions (CMCs), although booster sessions should be offered regularly. Trial registration The study was registered in the German Clinical Trials Register (DRKS00014043) on 26/04/2018.

Abstract Background Previous studies have shown that growing up with rheumatic conditions can fuel dissatisfaction and psychological distress, which in turn affects disease self-management and treatment adherence. Primary objective of this study was to estimate the prevalence of anxiety and depression symptoms in adolescents and young adults (AYA) with juvenile idiopathic arthritis (JIA) and to identify correlates of conspicuous screening results. Methods Initiated as part of the COACH multicenter observational study, outpatients aged 12 to 21 years participating in the National Pediatric Rheumatological Database (NPRD) were prospectively screened for mental health using the Patient Health Questionnaire-9 (PHQ-9) and the Generalised Anxiety Disorder Scale-7 (GAD-7). Results Data from 1,150 adolescents with JIA (mean age 15.6 ± 2.2 years; mean disease duration 7.2 ± 4.9 years, 69% female, 43% oligoarthritis, 26% polyarthritis) were analysed. Overall, 32.7% (n = 316) of AYA showed conspicuous screening results, of whom 30.4% reported clinically relevant suicidal or self-harm thoughts. About 19% of screened patients showed moderate to severe depressive or anxious symptoms. AYA with conspicuous screening results were older (15.8 vs. 15.2 years; p

Abstract Background Studying at university is a stressful time for many, which might result in the development of mental health problems. In the first wave of Covid-19, university students in Turkey reported suffering from an elevated level of stress compared to their peers in other countries. Mindfulness-based interventions could provide the means of successfully decreasing the stress level of university students. Moreover, offering interventions via the Internet could be a scalable option to prevent and treat mental health problems, while offering time/place flexibility, anonymity, and cost-effectiveness. Method In a randomized controlled trial of parallel design, the feasibility of a culturally adapted internet- and mobile-based intervention (IMI) (StudiCareM-TR) to promote mindfulness among Turkish-speaking university students was tested. Participants (N = 58) of a public university in Istanbul were randomized into an intervention (IG) vs. waitlist control group (WL). Measurements took place at baseline (t0) and 10 weeks post-randomization (t1). Intervention adherence, acceptance, and potential negative effects were feasibility outcomes. Levels of mindfulness, perceived stress, depression, anxiety, and wellbeing were analyzed in linear regression models to assess the potential efficacy of StudiCareM-TR. All analyses were conducted with the intention-to-treat sample, adjusting for baseline values. Results Based on participants’ feedback, StudiCareM-TR was perceived as acceptable, resulted in few negative effects (n = 7), and yielded improvements in mindfulness (β = 0.70) and presenteeism (β = − 0.61) compared to WL. Secondary outcomes of depression, anxiety, stress, and wellbeing did not show significant improvements. Assessment dropout was 31% (IG: 50%: WL: 89%), and intervention dropout was 45%. Conclusions StudiCareM-TR is feasible and acceptable to use among university students in Turkey and has the potential to improve their mindfulness levels. The intervention should be further developed with a focus on engagement-facilitating features in order to reduce intervention dropouts. Trial registration ID DRKS00024557.

Introduction: Digital phenotyping can be an innovative and unobtrusive way to improve the detection of insomnia. This study explores the correlations between smartphone usage features (SUF) and insomnia symptoms and their predictive value for detecting insomnia symptoms. Methods: In an observational study of a German convenience sample, the Insomnia Severity Index (ISI) and smartphone usage data (e.g., time the screen was active, longest time the screen was inactive in the night) for the previous 7 days were obtained. SUF (e.g., min, mean) were calculated from the smartphone usage data. Correlation analyses between the ISI and SUF were conducted. For the specification of the machine learning models (ML), 80 % of the data was allocated to training, 20 % to testing, and five-fold cross-validation was used. Six algorithms (support vector machine, XGBoost, Random Forest, k-Nearest-Neighbor, Naive Bayes, and Logistic Regressions) were specified to predict ISI scores ≥15. Results: 752 participants (51.1 % female, mean ISI = 10.23, mean age = 41.92) were included in the analyses. Small correlations between some of the SUF and insomnia symptoms were found. In the ML models, sensitivity was low, ranging from 0.05 to 0.27 in the testing subsample. Random Forest and Naive Bayes were the best-performing algorithms. Yet, their AUCs (0.57, 0.58 respectively) in the testing subsample indicated a low discrimination capacity. Conclusions: Given the small magnitude of the correlations and low discrimination capacity of the ML models, SUFs, as measured in this study, do not appear to be sufficient for detecting insomnia symptoms. Further research is necessary to explore whether examining intra-individual variations and subpopulations or employing alternative smartphone sensors yields more promising outcomes.

Abstract Background The experience of benefit-finding and growth (BFG), defined as perceiving positive life changes resulting from adversity, is increasingly studied among youths with chronic health conditions (CCs). However, empirical evidence is scarce for explaining individual differences in BFG. The study aimed to test a model of BFG, including an interplay of personal and environmental factors and coping processes. Methods A sample of N = 498 youths (12–21 years) recruited from three German patient registries for CCs (type 1 diabetes: n = 388, juvenile idiopathic arthritis: n = 82, cystic fibrosis: n = 28) completed a questionnaire including self-reported optimism, social support from parents and peers, coping strategies, and BFG. The model was created to reflect the theoretical assumptions of the Life Crisis and Personal Growth model and current empirical evidence. Structural equation modeling was conducted to evaluate the incremental explanatory power of optimism, peer group integration, parental support, acceptance, cognitive reappraisal, and seeking social support over and above sociodemographic and disease-related characteristics. Results The model (CFI = 0.93; RMSEA = 0.04; SRMR = 0.05) explained 32% of the variance in BFG. Controlling for sociodemographic and disease-related characteristics, acceptance, cognitive reappraisal, and seeking social support were directly and positively linked to BFG. All tested coping strategies significantly mediated the association between optimism and BFG, whereas seeking social support significantly mediated the relation between peer group integration and BFG. Discussion The study stresses the prominent role of emotion-focused coping strategies and peer group integration in enhancing BFG in youths with CCs. Trial registration German Clinical Trials Register (DRKS), no. DRKS00025125. Registered on May 17, 2021.

Abstract Background The daily demands of type 1 diabetes management may jeopardize adolescents’ mental health. We aimed to assess anxiety and depression symptoms by broad-scale, tablet-based outpatient screening in adolescents with type 1 diabetes in Germany. Methods Adolescent patients with type 1 diabetes mellitus (n = 2,394; mean age 15.4 y [SD 2.0]; 50.7% male) were screened for anxiety (GAD-7) and depression symptoms (PHQ-9) by self-report questionnaires and linked to clinical data from the DPV patient registry. Logistic regression was used to estimate the contribution of clinical parameters to positive screening results. Results Altogether, 30.2% showed a positive screening (score ≥ 7 in either test), and 11.3% reported suicidal ideations or self-harm. Patients with anxiety and depression symptoms were older (15.7 y [CI 15.5–15.8] vs. 15.3 y [CI 15.2–15.4]; p 15 years (aOR 1.40 [1.16–1.68]; p 9% (> 75 mmol/mol; aOR 2.58 [1.83–3.64]; each p

BackgroundMental health problems are prevalent among people with diabetes, yet often under-diagnosed. Smart sensing, utilizing passively collected digital markers through digital devices, is an innovative diagnostic approach that can support mental health screening and intervention. However, the acceptance of this technology remains unclear. Grounded on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study aimed to investigate (1) the acceptance of smart sensing in a diabetes sample, (2) the determinants of acceptance, and (3) the effectiveness of an acceptance facilitating intervention (AFI).MethodsA total of N = 132 participants with diabetes were randomized to an intervention group (IG) or a control group (CG). The IG received a video-based AFI on smart sensing and the CG received an educational video on mindfulness. Acceptance and its potential determinants were assessed through an online questionnaire as a single post-measurement. The self-reported behavioral intention, interest in using a smart sensing application and installation of a smart sensing application were assessed as outcomes. The data were analyzed using latent structural equation modeling and t-tests.ResultsThe acceptance of smart sensing at baseline was average (M = 12.64, SD = 4.24) with 27.8% showing low, 40.3% moderate, and 31.9% high acceptance. Performance expectancy (γ = 0.64, p

This review investigates persuasive design frameworks within eHealth, concentrating on methodologies, their prevalence in mental and behavioral health applications, and identifying current research gaps. An extensive search was conducted across 8 databases, focusing on English publications with full text available. The search prioritized primary research articles, post-2011 applications, and eHealth platforms emphasizing treatment or support. The inclusion process was iterative, involving multiple authors, and relied on detailed criteria to ensure the relevance and contemporaneity of selected works. The final review set comprised 161 articles, providing an overview of persuasive design frameworks in eHealth. The review highlights the state of the art in the domain, emphasizing the utilization and effectiveness of these frameworks in eHealth platforms. This review details the restricted adoption of persuasive design frameworks within the field of eHealth, particularly in the mental and behavioral sectors. Predominant gaps include the scarcity of comparative evaluations, the underrepresentation of tailored interventions, and the unclear influence of persuasive components on user experience. There is a notable requirement for further scrutiny and refinement of persuasive design frameworks. Addressing these concerns promises a more substantial foundation for persuasive design in eHealth, potentially enhancing user commitment and platform efficiency.

BackgroundMental health (MH) problems in youth are prevalent, burdening, and frequently persistent. Despite the existence of effective treatment, the uptake of professional help is low, particularly due to attitudinal barriers. ObjectiveThis study evaluated the effectiveness and acceptability of 2 video-based microinterventions aimed at reducing barriers to MH treatment and increasing the likelihood of seeking professional help in young people. MethodsThis study was entirely web based and open access. The interventions addressed 5 MH problems: generalized anxiety disorder, depression, bulimia, nonsuicidal self-injury, and problematic alcohol use. Intervention 1 aimed to destigmatize and improve MH literacy, whereas intervention 2 aimed to induce positive outcome expectancies regarding professional help seeking. Of the 2435 participants who commenced the study, a final sample of 1394 (57.25%) participants aged 14 to 29 years with complete data and sufficient durations of stay on the video pages were randomized in a fully automated manner to 1 of the 5 MH problems and 1 of 3 conditions (control, intervention 1, and intervention 2) in a permuted block design. After the presentation of a video vignette, no further videos were shown to the control group, whereas a second, short intervention video was presented to the intervention 1 and 2 groups. Intervention effects on self-reported potential professional help seeking (primary outcome), stigma, and attitudes toward help seeking were examined using analyses of covariance across and within the 5 MH problems. Furthermore, we assessed video acceptability. ResultsNo significant group effects on potential professional help seeking were found in the total sample (F2,1385=0.99; P=.37). However, the groups differed significantly with regard to stigma outcomes and the likelihood of seeking informal help (F2,1385=3.75; P=.02). Furthermore, separate analyses indicated substantial differences in intervention effects among the 5 MH problems. ConclusionsInterventions to promote help seeking for MH problems may require disorder-specific approaches. The study results can inform future research and public health campaigns addressing adolescents and young adults. Trial RegistrationGerman Clinical Trials Register DRKS00023110; https://drks.de/search/de/trial/DRKS00023110

ObjectiveSmart sensing has the potential to make psychotherapeutic treatments more effective. It involves the passive analysis and collection of data generated by digital devices. However, acceptance of smart sensing among psychotherapy patients remains unclear. Based on the unified theory of acceptance and use of technology (UTAUT), this study investigated (1) the acceptance toward smart sensing in a sample of psychotherapy patients (2) the effectiveness of an acceptance facilitating intervention (AFI) and (3) the determinants of acceptance.MethodsPatients (N = 116) 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 control video. An online questionnaire was used to assess acceptance of smart sensing, performance expectancy, effort expectancy, facilitating conditions and social influence. The intervention effects of the AFI on acceptance were investigated. The determinants of acceptance were analyzed with structural equation modeling (SEM).ResultsThe IG showed a moderate level of acceptance (M = 3.16, SD = 0.97), while the CG showed a low level (M = 2.76, SD = 1.0). The increase in acceptance showed a moderate effect in the intervention group (p

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.

Background: It is uncertain whether app-based interventions add value to existing mental health care. Objective: To examine the incremental effects of app-based interventions when used as adjunct to mental health interventions. Methods: We searched PubMed, PsycINFO, Scopus, Web of Science, and Cochrane Library databases on September 15th, 2023, for randomised controlled trials (RCTs) on mental health interventions with an adjunct app-based intervention compared to the same intervention-only arm for adults with mental disorders or respective clinically relevant symptomatology. We conducted meta-analyses on symptoms of different mental disorders at postintervention. PROSPERO, CRD42018098545. Results: We identified 46 RCTs (4869 participants). Thirty-two adjunctive app-based interventions passively or actively monitored symptoms and behaviour, and in 13 interventions, the monitored data were sent to a therapist. We found additive effects on symptoms of depression (g = 0.17; 95 % CI 0.02 to 0.33; k = 7 comparisons), anxiety (g = 0.80; 95 % CI 0.06 to 1.54; k = 3), mania (g = 0.2; 95 % CI 0.02 to 0.38; k = 4), smoking cessation (g = 0.43; 95 % CI 0.29 to 0.58; k = 10), and alcohol use (g = 0.23; 95 % CI 0.08 to 0.39; k = 7). No significant effects were found on symptoms of depression within a bipolar disorder (g = -0.07; 95 % CI -0.37 to 0.23, k = 4) and eating disorders (g = -0.02; 95 % CI -0.44 to 0.4, k = 3). Studies on depression, mania, smoking, and alcohol use had a low heterogeneity between the trials. For other mental disorders, only single studies were identified. Only ten studies had a low risk of bias, and 25 studies reported insufficient statistical power. Discussion: App-based interventions may be used to enhance mental health interventions to further reduce symptoms of depression, anxiety, mania, smoking, and alcohol use. However, the effects were small, except for anxiety, and limited due to study quality. Further high-quality research with larger sample sizes is warranted to better understand how app-based interventions can be most effectively combined with established interventions to improve outcomes.

Abstract Background Adolescents and young adults (AYA) with a chronic somatic disease (CD) have a 3-fold higher risk of post-traumatic stress disorder (PTSD) than healthy controls. In addition, elevated post-traumatic stress symptoms (PTSS) have a negative impact on CD severity, treatment adherence, health problems and functional impairment. However, a more detailed understanding of this comorbidity is lacking. Methods AYA with type 1 diabetes mellitus, juvenile idiopathic arthritis or cystic fibrosis (12–21 years of age) and elevated anxiety and/or depression symptoms, as well as their reference persons (≥ 18 years of age), completed online questionnaires in self- or observer report. The most stressful event related to the CD was reported descriptively. Questionnaires were used to assess PTSS, anxious and depressive symptoms, actual overall health, coping, personal growth and social support. Qualitative content analysis, linear regression models and correlations were used for mixed methods analysis. Results According to the reports of n = 235 AYA (mean age 15.61; 73% girls) and n = 70 reference persons, four categories were identified as the most stressful events due to CD: (1) psychological burden (40% of AYA / 50% of reference persons); (2) CD self-management (32% / 43%); (3) social burden (30% / 27%); and (4) physical impairment (23% / 16%). 37% of AYA reported clinically relevant PTSS due to CD. The best predictors of PTSS severity were anxious-depressive symptoms, emotional coping, personal growth and current overall health (F(4, 224) = 59.404, R² = 0.515, p

IntroductionMost university students with mental disorders remain untreated. Evaluating the acceptance of intervention targets in mental health treatment, promotion, and prevention, as well as mental health service delivery modes is crucial for reducing potential barriers, increasing healthcare utilization, and efficiently allocating resources in healthcare services.AimThe study aimed to evaluate the acceptance of various intervention targets and delivery modes of mental health care services in German first-year university students.MethodsIn total, 1,376 first-year students from two German universities from the 2017–2018 multi-center cross-sectional cohort of the StudiCare project, the German arm of the World Mental Health International College Student Survey initiative, completed a web-based survey assessing their mental health. Mental disorder status was based on self-reported data fulfilling the DSM-IV criteria. We report frequencies of accepted delivery modes [categories: group or in-person therapy with on or off campus services, self-help internet- or mobile-based intervention (IMI) with or without coaching, or a combination of a in-person and IMI (blended)]. In a multinomial logistic regression, we estimate correlates of the preference for in-person vs. IMI vs. a combination of both modes (blended) modalities. Additionally, we report frequencies of intervention targets (disorder specific: e.g., social phobia, depressive mood; study-related: test anxiety, procrastination; general well-being: sleep quality, resilience) their association with mental disorders and sex, and optimal combinations of treatment targets for each mental illness.ResultsGerman university students' acceptance is high for in-person (71%–76%), moderate for internet- and mobile-based (45%–55%), and low for group delivery modes (31%–36%). In-person treatment (72%) was preferred over IMI (19%) and blended modalities (9%). Having a mental disorder [odds ratio (OR): 1.56], believing that digital treatments are effective (OR: 3.2), and showing no intention to use services (OR: 2.8) were associated with a preference for IMI compared to in-person modes. Students with prior treatment experience preferred in-person modes (OR: 0.46). In general, treatment targets acceptance was higher among female students and students with mental disorders. However, this was not true for targets with the highest (i.e., procrastination) and the lowest (i.e., substance-use disorder) acceptance. If only two intervention targets were offered, a combination of study-related targets (i.e., procrastination, stress, time management) would reach 85%–88% of the students.ConclusionIn-person services are preferred, yet half of the students consider using IMI, preferably aiming for a combination of at least two study-related intervention targets. Student mental health care services should offer a combination of accepted targets in different delivery modes to maximize service utilization.

Low-threshold and remotely delivered preventive interventions, like telephone coaching, are warranted for farmers who experience multiple risk factors for depression, live in underserved areas, and show low help-seeking behavior. Factors facilitating uptake and actual use of effective remote interventions are important to reduce depression disease burden. This study aimed at identifying factors that potentially can influence acceptance of and satisfaction with a telephone coaching in this occupational group.Semi-structured interviews were based on the ‘Unified Theory of Acceptance and Use of Technology’, the ‘Evaluation’, and ‘Discrepancy’ models for satisfaction. Interviews were conducted with 20 of 66 invited participants of a 6-months telephone coaching during an effectiveness or implementation study. Audio-recorded interviews were transcribed and analyzed (deductive-inductive qualitative content analysis). Independent coding by two persons resulted in good agreement (Κ = 0.80). Participants validated results via questionnaire.Overall, 32 supporting (SF) and 14 hindering factors (HF) for acceptance and satisfaction were identified and organized into five dimensions: Coaching result (SF = 9, HF = 3), coach (SF = 9, HF = 1), organization (SF = 5, HF = 2), the telephone as communication medium (SF = 4, HF = 5) and participant characteristics (SF = 5, HF = 3). Most named SFs were ‘Flexible appointment arrangement’ (n = 19/95 %) and ‘low effort’ (n = 17/85 %), while most reported HFs were ‘lack of visual cues’ (n = 12/60 %) and ‘social/professional involvement restricts change process’ (n = 10/50 %).The perceived changes initiated by coaching, a low effort through telephone conduct, and the indicated personalization were identified as important influencing factors on acceptance and satisfaction based on interviewees' statements. Both may be further enhanced by offering choice and advice for delivery formats (e.g., video-calls) and training of coaches in farm-related issues. Study registration: German Clinical Trial Registrations: DRKS00017078 and DRKS00015655.

BackgroundDigital 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. ObjectiveTherefore, 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. MethodsFirst, 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. ResultsThe 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. ConclusionsThis 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.

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 R2 = 45 %), with predicted subgroup-conditional effects ranging from di = 0.24 to −1.31. External validation in a pilot trial among patients on sick leave (N = 76; R2 = 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.

Abstract Given the limited availability and accessibility of onsite cognitive behavioral therapy for insomnia (CBT-I), other CBT-I settings, such as internet-delivered CBT-I (iCBT-I), have been proposed. The primary aim of the study was to compare the efficacy of available CBT-I settings on insomnia severity. A systematic review and frequentist network meta-analysis of available CBT-I settings was performed. PsycINFO, PsycARTICLES, MEDLINE, PubMed, and CINAHL were searched for randomized controlled trials (RCTs) investigating any CBT-I settings in adults with insomnia disorder. The systematic literature search (3851 references) resulted in 52 RCTs. For the primary outcome insomnia severity, all examined CBT-I settings except smartphone-delivered CBT-I yielded significant effects when compared to WL. Large standardized mean differences were found for individual onsite CBT-I (− 1.27;95%CI − 1.70, − 0.84), group-delivered CBT-I (− 1.00;95%CI − 1.42. − 0.59), telehealth (− 1.28;95%CI − 2.06, − 0.50), and guided bibliotherapy (− 0.99;95%CI − 1.67, − 0.32). Both guided iCBT-I (− 0.71;95%CI − 1.18, − 0.24) and unguided iCBT-I (− 0.78;95%CI − 1.18, − 0.38) yielded medium effect sizes. The results underline that health care systems should intensify their efforts to provide synchronously-delivered CBT-I (individual onsite, group-delivered, and telehealth), and particularly individual onsite CBT-I, given its solid evidence base. Medium to large effect sizes for iCBT-I and guided bibliotherapy indicate that self-help settings may be a viable alternative when synchronously-delivered CBT-I is not available.

Abstract Mental comorbidities in patients with type 1 diabetes mellitus (T1D) are common, and can have a negative impact on acute blood glucose levels and long-term metabolic control. Information on the association of T1D and comorbid posttraumatic stress disorder (PTSD) with diabetes-related outcomes is limited. The aim was to examine the associations between a clinical diagnosis of PTSD and diabetes-related outcomes in patients with T1D. Patients with T1D and comorbid documented PTSD from the DPV database (n = 179) were compared to a group with T1D without PTSD (n = 895), and compared to a group with T1D without comorbid mental disorder (n = 895) by matching demographics (age, gender, duration of diabetes, therapy and migration background) 1:5. Clinical diabetes-related outcomes {body mass index (BMI), hemoglobin A1c (hbA1c), daily insulin dose, diabetic ketoacidosis (DKA), hypoglycemia, number of hospital admissions, number of hospital days} were analyzed, stratified by age groups (≤ 25 years vs. > 25 years). Patients with comorbid PTSD aged ≤ 25 years compared with patients without PTSD or patients without mental disorders had significantly higher HbA1c (8.71 vs. 8.30 or 8.24%), higher number of hospital admissions (0.94 vs. 0.44 or 0.32 per year) and higher rates of DKA (0.10 vs. 0.02 or 0.01 events/year). Patients with comorbid PTSD aged ≤ 25 years compared with patients without PTSD had significantly higher BMI (0.85 vs. 0.59) and longer hospital stays (15.89 vs.11.58 days) than patients without PTSD. Patients with PTSD > 25 years compared with patients without PTSD or without any mental comorbidities had significantly fewer hospital admissions (0.49 vs. 0.77 or 0.69), but a longer hospital length of stay (20.35 vs. 11.58 or 1.09 days). We found that PTSD in younger patients with T1D is significantly related to diabetes outcome. In adult patients with T1D, comorbid PTSD is associated with fewer, but longer hospitalizations. Awareness of PTSD in the care of patients with T1D should be raised and psychological intervention should be provided when necessary.

BackgroundChronic stress poses risks for physical and mental well-being. Stress management interventions have been shown to be effective, and stress management apps (SMAs) might help to transfer strategies into everyday life. ObjectiveThis review aims to provide a comprehensive overview of the quality and characteristics of SMAs to give potential users or health professionals a guideline when searching for SMAs in common app stores. MethodsSMAs were identified with a systematic search in the European Google Play Store and Apple App Store. SMAs were screened and checked according to the inclusion criteria. General characteristics and quality were assessed by 2 independent raters using the German Mobile Application Rating Scale (MARS-G). The MARS-G assesses quality (range 1 to 5) on the following four dimensions: (1) engagement, (2) functionality, (3) esthetics, and (4) information. In addition, the theory-based stress management strategies, evidence base, long-term availability, and common characteristics of the 5 top-rated SMAs were assessed and derived. ResultsOf 2044 identified apps, 121 SMAs were included. Frequently implemented strategies (also in the 5 top-rated SMAs) were psychoeducation, breathing, and mindfulness, as well as the use of monitoring and reminder functions. Of the 121 SMAs, 111 (91.7%) provided a privacy policy, but only 44 (36.4%) required an active confirmation of informed consent. Data sharing with third parties was disclosed in only 14.0% (17/121) of the SMAs. The average quality of the included apps was above the cutoff score of 3.5 (mean 3.59, SD 0.50). The MARS-G dimensions yielded values above this cutoff score (functionality: mean 4.14, SD 0.47; esthetics: mean 3.76, SD 0.73) and below this score (information: mean 3.42, SD 0.46; engagement: mean 3.05, SD 0.78). Most theory-based stress management strategies were regenerative stress management strategies. The evidence base for 9.1% (11/121) of the SMAs could be identified, indicating significant group differences in several variables (eg, stress or depressive symptoms) in favor of SMAs. Moreover, 38.0% (46/121) of the SMAs were no longer available after a 2-year period. ConclusionsThe moderate information quality, scarce evidence base, constraints in data privacy and security features, and high volatility of SMAs pose challenges for users, health professionals, and researchers. However, owing to the scalability of SMAs and the few but promising results regarding their effectiveness, they have a high potential to reach and help a broad audience. For a holistic stress management approach, SMAs could benefit from a broader repertoire of strategies, such as more instrumental and mental stress management strategies. The common characteristics of SMAs with top-rated quality can be used as guidance for potential users and health professionals, but owing to the high volatility of SMAs, enhanced evaluation frameworks are needed.

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.

Background and aimsInternet use disorder (IUD), characterized as the inability to control one’s internet use, is associated with reduced quality of life and mental health comorbidities such as depression, substance abuse, or anxiety. Evidence-based treatment options are scarce due to the novelty of the diagnosis. Internet- and mobile-based interventions (IMI) may be an effective means to deliver psychological treatment to individuals with IUD as they address affected individuals in their online setting. This study presents a newly developed IMI for IUD disclosing treatment satisfaction and preliminary effects by exemplifying with a case report.MethodsThe case of a female participant with IUD, characterized by an excessive use of social media, is analyzed. The case report follows the CARE guidelines and presents qualitative and quantitative outcomes regarding potential symptom reduction measured by the Internet Addiction Test (IAT) and Compulsive Internet Use Scale (CIUS), treatment satisfaction measured by the Client Satisfaction Questionnaire (CSQ) and feasibility by analyzing participant’s written feedback during treatment.ResultsThe case report shows that internet- and mobile-based interventions may be feasible in supporting an individual in reducing symptoms of IUD as well as depressive symptoms, anxiety and procrastination behavior. Treatment satisfaction was reported as good.Discussion and conclusionsThis case report illustrates that IMIs can have the potential to be an easily accessible and possibly effective treatment option for IUD. Case studies on IMIs may provide insights into important mechanisms for symptom change. Further studies are needed to expand our understanding of this diverse disorder to provide adequate treatment.Clinical Trial Registrationhttps://clinicaltrials.gov/,DRKS00015314.

BackgroundAccurate 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.MethodsThe 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.ResultsThe 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

[Background] Student mobility across borders poses challenges to health systems at the university and country levels. International students suffer from stress more than their local peers, however, do not seek help or underutilize existing help offers. Some barriers to help-seeking among international students are insufficient information regarding the health offers, stigma, and language, which might be overcome via culturally adapted internet and mobile-based interventions (IMI). [Method] A randomized controlled feasibility trial with a parallel design assessed the feasibility and potential efficacy of an online mindfulness intervention adapted for international university students. Participants were randomized into either an adapted online mindfulness intervention (StudiCareM-E) (IG, n = 20) or a waitlist control group (WL, n = 20). Participants were assessed at baseline (t0) and eight-week post-randomization (t1). The feasibility of StudiCareM-E was evaluated regarding intervention adherence, client satisfaction, and potential negative effects. The potential efficacy of StudiCareM-E was measured by means of the level of mindfulness, perceived stress, depression, anxiety, presenteeism, and wellbeing. Efficacy outcomes were evaluated with regression models on the intention-to-treat (ITT) sample (n = 40), adjusting for the baseline values. [Results] Participants’ formative feedback suggested improvements in the content of the IMI. There were no crucial negative effects compared to WL. Assessment dropout was 35% (IG: 50%: WL: 20%), and intervention dropout was 60%. StudiCareM-E yielded significant improvements in mindfulness (β = .34), well-being (β = .37), and anxiety (β = -.42) compared to WL. [Conclusion] StudiCareM-E might be used among culturally diverse international student populations to improve their well-being. Future studies might carefully inspect the extent of the adaptation needs of their target group and design their interventions accordingly.

BackgroundExisting evidence suggests internet- and mobile-based interventions (IMIs) improve depressive symptoms in college students effectively. However, there is far less knowledge about the potential mechanisms of change of mindfulness-based IMIs, which could contribute to optimizing target groups and interventions. Hence, within this secondary analysis of data from a randomized controlled trial (RCT), potential moderators and mediators of the effectiveness of the IMI StudiCare Mindfulness were investigated.MethodsModeration and mediation analyses were based on secondary data from a RCT that examined the effectiveness of the 7-module IMI StudiCare Mindfulness in a sample of college students (intervention group: n = 217; waitlist control group: n = 127). Assessments were collected before (t0; baseline), 4 weeks after (t1; during intervention), and 8 weeks after (t2; post-intervention) randomization. Longitudinal mediation analyses using structural equation modeling were employed, with depressive symptom severity as the dependent variable. For moderation analyses, bilinear interaction models were calculated with depressive symptom severity and mindfulness at t2 as dependent variables. All data-analyses were performed on an intention-to-treat basis.ResultsMediation analyses showed a significant, full mediation of the intervention effect on depressive symptom severity through mindfulness (indirect effect, a*b = 0.153, p

IntroductionDuring the COVID-19 pandemic, questions about both consequences and helpful strategies to maintain quality of life (QoL) have become increasingly important. Thus, the aim of this study was to investigate the distribution of coping factors during the COVID-19 pandemic, their associations with QoL and the moderating role of certain sociodemographic characteristics.MethodsAnalyses were based on cross-sectional self-reports from German adult participants (N = 2,137, 18–84 years, 52.1% female) of the CORONA HEALTH APP Study from July 2020 to July 2021. Multivariate regression analyses were used to predict (a) coping factors assessed with the Brief COPE and (b) QoL assessed with the WHOQOL-BREF while taking measurement time, central sociodemographic, and health characteristics into account.ResultsDuring the COVID-19 pandemic, German adults mostly pursued problem- and meaning-focused coping factors and showed a relatively good QoL [Mean values (M) from 57.2 to 73.6, standard deviations (SD) = 16.3−22.6], except for the social domain (M = 57.2, SD = 22.6), and with a decreasing trend over time (β from −0.06 to −0.11, ps < 0.01). Whereas, escape-avoidance coping was negatively related to all QoL domains (β = −0.35, p < 0.001 for psychological, β = −0.22, p < 0.001 for physical, β = −0.13, p = 0.045 for social, β = −0.49, p < 0.001 for environmental QoL), support- and meaning-focused coping showed positive associations with various QoL domains (β from 0.19 to 0.45, ps < 0.01). The results also suggested differences in the pursuit of coping factors as well as in the strength of associations with QoL by sociodemographic characteristics. Escape-avoidance-focused coping was negatively associated with QoL levels in older and less educated adults (simple slopes differed at ps < 0.001), in particular.ConclusionsThe results demonstrated what types of coping may be helpful to avoid QoL deterioration (i.e., support- and meaning-focused coping) and provide implications for future universal or targeted health promotion (i.e., older or less educated adults who lack social or instrumental support) and preparedness in the face of unknown challenging societal situations similar to that of the COVID-19 pandemic. Cross-sectional trends of enhanced use of escape-avoidance-focused coping and QoL deterioration point toward a need for increased attention from public health and policy.

Abstract 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.

Abstract 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

Abstract Background Previous evidence has suggested that physically inactive individuals and extensive media users are at high risk for experiencing depressive symptoms. We examined personality traits and perceived social support as potential moderators of this association. Personality and perceived social support were included as two of the most frequently considered variables when determining predispositioning factors for media use phenomena also discussed in relation to physical activity. Methods We analysed cross-sectional data from 1402 adults (18–31 years old) who participated in a national health survey in Germany (KiGGS, Study on the health of children and adolescents in Germany, wave 2). The data included one-week accelerometer assessments as objective indicators of physical activity, self-reported media use, depressive symptoms, perceived social support and Big 5 personality traits. An elastic net regression model was fit with depressive symptoms as outcome. Ten-fold cross-validation was implemented. Results Amongst the main effects, we found that high media use was positively correlated with depressive symptoms, whereas physical activity was not correlated. Looking at support and individual differences as moderators, revealed that PC use was more strongly correlated with depressive symptoms in cases of low levels of perceived social support. Positive associations of social media use with depressive symptoms were more pronounced, whereas negative associations of moderate to vigorous physical activity with depressive symptoms were less pronounced in extraverts than they were in introverts. Conclusions Results highlight the importance of considering individual factors for deriving more valid recommendations on protective health behaviours.

IntroductionDigital 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.MethodsData 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.ConclusionThis 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 registrationWe will pre-register this study with the open science framework after article acceptance to ensure consistency between online registration and the published trial protocol.

IntroductionDepression has a significant impact on individuals and society, which is why preventive measures are important. Farmers represent an occupational group exposed to many risk factors for depression. The potential of guided, tailored internet-based interventions and a personalized telephone coaching is evaluated in a German project of the Social Insurance for Agriculture, Forestry and Horticulture (SVLFG). While user outcomes are promising, not much is known about actual routine care use and implementation of the two digital health interventions. This study evaluates the implementation from the perspective of social insurance employees to understand determinants influencing the uptake and implementation of digital interventions to prevent depression in farmers.MethodsThe data collection and analysis are based on the Consolidated Framework for Implementation Research (CFIR). Health care workers (n = 86) and implementers (n = 7) completed online surveys and/or participated in focus groups. The surveys consisted of validated questionnaires used in implementation research, adapted items from the CFIR guide or from other CFIR studies. In addition, we used reporting data to map implementation based on selected CFIR constructs.ResultsWithin the five CFIR dimensions, many facilitating factors emerged in relation to intervention characteristics (e.g., relative advantage compared to existing services, evidence and quality) and the inner setting of the SVLFG (e.g., tension for change, compatibility with values and existing working processes). In addition, barriers to implementation were identified in relation to the outer setting (patient needs and resources), inner setting (e.g., available resources, access to knowledge and information) and characteristics of individuals (e.g., self-efficacy). With regard to the implementation process, facilitating factors (formal implementation leaders) as well as hindering factors (reflecting and evaluating) were identified.DiscussionThe findings shed light on the implementation of two digital prevention services in an agricultural setting. While both offerings seem to be widely accepted by health care workers, the results also point to revealed barriers and contribute to recommendations for further service implementation. For instance, special attention should be given to “patient needs and resources” by raising awareness of mental health issues among the target population as well as barriers regarding the inner setting.Clinical Trial RegistrationGerman Clinical Trial Registration: [DRKS00017078]. Registered on 18.04.2019

IntroductionComprehensive evidence on prevalence and incidence of post-traumatic stress disorder (PTSD) and symptoms (PTSS) in people with chronic somatic diseases (CD) is lacking.ObjectiveTo systematically and meta-analytically examine prevalence and incidence of PTSD and PTSS in people with CD compared with people without CD.MethodsMEDLINE, Embase, and PsycINFO were searched from inception (1946) to June 2020. Studies reporting point, 12-month, lifetime prevalence, or 12-month incidence of PTSD and PTSS in people with CD were selected and reviewed in accordance with PRISMA guidelines by two independent reviewers. Risk of bias was assessed by a combination of the Newcastle-Ottawa Scale and recommendations of the Cochrane Collaboration for non-comparative studies. Pooled estimates were calculated using random effects meta-analyses. Between-study heterogeneity was assessed using the I2 statistic.ResultsData were extracted from studies reporting on point prevalence (k = 60; n = 21,213), 12-month prevalence (k = 3; n = 913), and lifetime prevalence (k = 6; n = 826). 12-month incidence estimates were not available. The pooled estimate for the point prevalence of PTSD (k = 41) across CD was 12.7% (95% CI, 8.6 to 18.4%) and 19.6% regarding PTSS (13.2 to 28.1%; k = 24). Individuals with cerebrovascular disorder (k = 4) showed the highest pooled point prevalence for PTSD (23.6%, 95% CI, 16.8 to 32.0%), those with cardiovascular diseases the lowest (6.6%, 1.9 to 20.9%; k = 5). The pooled 12-month prevalence of PTSD (k = 3) was 8.8% (95% CI, 5.5 to 13.5%) and the lifetime prevalence (k = 6) was 12.1% (7.6 to 18.5%). Pooled estimates of PTSD prevalence in people with compared to those without CD showed an odds ratio of 9.96 (95% CI, 2.55 to 38.94; k = 5).ConclusionPost-traumatic stress disorder and PTSS are common and substantially higher in people with compared to those without CD. Earlier detection and treatment of this comorbidity might improve mental and physical health, reduce the incidence of further diseases, and reduce mortality.Clinical trial registrationhttps://osf.io/9xvgz, identifier 9xvgz.

In the course of the recognition of mental health as an essential component of population health, the Robert Koch Institute has begun developing a Mental Health Surveillance (MHS) system for Germany. MHS aims to continuously report data for relevant mental health indicators, thus creating a basis for evidence-based planning and evaluation of public health measures. In order to develop a set of indicators for the adult population, potential indicators were identified through a systematic literature review and selected in a consensus process by international and national experts and stakeholders. The final set comprises 60 indicators which, together, represent a multidimensional public health framework for mental health across four fields of action. For the fifth field of action ‘Mental health promotion and prevention’ indicators still need to be developed. The methodology piloted proved to be practicable. Strengths and limitations will be discussed regarding the search and definition of indicators, the scope of the indicator set as well as the participatory decision-making process. Next steps in setting up the MHS will be the operationalisation of the single indicators and their extension to also cover children and adolescents. Given assured data availability, the MHS will contribute to broadening our knowledge on population mental health, supporting a targeted promotion of mental health and reducing the disease burden in persons with mental disorders.