Feasibility of a trauma-focused internet- and mobile-based intervention for youth with posttraumatic stress symptoms.

Background: Many youth with posttraumatic stress symptoms (PTSS) do not receive evidence-based care. Internet- and Mobile-Based Interventions (IMIs) comprising evidence-based trauma-focused components can address this gap, but research is scarce. Thus, we investigated the feasibility of a trauma-focused IMI for youth with PTSS.Methods: In a one-arm non-randomized prospective proof-of-concept study, 32 youths aged 15-21 years with clinically relevant PTSS (CATS ≥ 21) received access to a trauma-focused IMI with therapist guidance, comprising nine sessions on an eHealth platform accessible via web-browser. We used a feasibility framework assessing recruitment capability, sample characteristics, data collection, satisfaction, acceptability, study management abilities, safety aspects, and efficacy of the IMI in PTSS severity and related outcomes. Self-rated assessments took place pre-, mid-, post-intervention and at 3-month follow-up and clinician-rated assessments at baseline and post-intervention.Results: The sample mainly consisted of young adult females with interpersonal trauma and high PTSS levels (CATS, M = 31.63, SD = 7.64). The IMI sessions were found useful and comprehensible, whereas feasibility of trauma processing was perceived as difficult. Around one-third of participants (31%) completed the IMI's eight core sessions. The study completer analysis showed a significant reduction with large effects in self-rated PTSS at post-treatment [t(21) = 4.27; p < .001; d = 0.88] and follow-up [t(18) = 3.83; p = .001; d = 0.84], and clinician-rated PTSD severity at post-treatment [t(21) = 4.52; p < .001; d = 0.93]. The intention-to-treat analysis indicated significant reductions for PTSS at post-treatment and follow-up with large effect sizes (d = -0.97- -1.02). All participants experienced at least one negative effect, with the most common being the resurfacing of unpleasant memories (n = 17/22, 77%).Conclusion: The study reached highly burdened young adults. The IMI was accepted in terms of usefulness and comprehensibility but many youths did not complete all sessions. Exploration of strategies to improve adherence in trauma-focused IMIs for youth is warranted, alongside the evaluation of the IMI's efficacy in a subsequent randomized controlled trial.

Youth often lack access to evidence-based care after trauma. This study assessed the feasibility of a trauma-focused internet- and mobile-based intervention with therapist guidance.The intervention was accepted by youths, and the preliminary evaluation of participant responses suggests its efficacy.Future studies should examine strategies to improve adherence and the IMI's efficacy in a RCT.

BEST FOR CAN - bringing empirically supported treatments to children and adolescents after child abuse and neglect: update to the study protocol.

Background: The implementation trial BESTFORCAN aims to evaluate the dissemination of Trauma-Focused Behavioural Therapy (TF-CBT) for children and adolescents in Germany with posttraumatic stress symptoms (PTSS) after child abuse and neglect (CAN) with a focus on supervision.Objective: This update to the study protocol outlines changes made due to practical reasons in the course of the ongoing trial while maintaining methodological quality.Method: The amendments to the original study protocol comprise (1) a more refined operationalisation of the primary outcome sufficiently adherent TF-CBT therapy (SATT), (2) changes in the study sites and (3) additional inclusion of one post-gradual psychotherapy training institute.Discussion: The adaptions to the original study protocol ensured high methodological quality through the transparent presentation of protocol modification: ensuring the recruitment of participating psychotherapists in training by including a further post-gradual training institute as well as an adaption of the measurement of SATT with high external validity. The objectives, diagnostic set, and secondary outcomes remained unimpaired by the amendment. Therefore, we expect the trial to provide evidence for the effect of model-specific trauma-focused supervision on the implementation outcomes of TF-CBT as compared to supervision as usual.Trial registration: German Clinical Trials Register identifier: DRKS00020516..

Update to the study protocol of the trial BESTFORCAN that investigates the implementation of trauma-focused behavioural therapy for children and adolescents with posttraumatic stress symptoms following abuse with a focus on the role of supervision.Adaptions have been made regarding the specification of the definition of sufficiently adherent intervention, relocation of the data-handling centre and the recruitment of one additional psychotherapy institute.The adaptions have no impact on the objectives, diagnostic set, secondary outcomes, or processes of data handling.

Efficacy of an Internet- and Mobile-Based Intervention for Subclinical Anxiety and Depression (ICare Prevent) with Two Guidance Formats: Results from a Three-Armed Randomized Controlled Trial.

INTRODUCTION: Limited research exists on intervention efficacy for comorbid subclinical anxiety and depressive disorders, despite their common co-occurrence. Internet- and mobile-based interventions (IMIs) are promising to reach individuals facing subclinical symptoms. OBJECTIVE: This study aimed to evaluate the efficacy of a transdiagnostic and self-tailored IMI in reducing subclinical anxiety and depressive symptom severity with either individualized (IG-IMI) or automated (AG-IMI) guidance compared to a waitlist control group with care-as-usual access (WLC). METHODS: Participants included 566 adults with subclinical anxiety (GAD-7 ≥ 5) and/or depressive (CES-D ≥16) symptoms, who did not meet criteria for a full-syndrome depressive or anxiety disorder. In a three-arm randomized clinical trial, participants were randomized to a cognitive behavioral 7-session IMI plus booster session with IG-IMI (n = 186) or AG-IMI (n = 189) or WLC (n = 191). Primary outcomes included observer-rated anxiety (HAM-A) and depressive (QIDS) symptom severity 8 weeks after randomization assessed by blinded raters via telephone. Follow-up outcomes at 6 and 12 months are reported. RESULTS: Symptom severity was significantly lower with small to medium effects in IG-IMI (anxiety: d = 0.45, depression: d = 0.43) and AG-IMI (anxiety: d = 0.31, depression: d = 0.32) compared to WLC. No significant differences emerged between guidance formats in primary outcomes. There was a significant effect in HAM-A after 6 months favoring AG-IMI. On average, participants completed 85.38% of IG-IMI and 77.38% of AG-IMI. CONCLUSIONS: A transdiagnostic, self-tailored IMI can reduce subclinical anxiety and depressive symptom severity, but 12-month long-term effects were absent. Automated guidance holds promise for enhancing the scalability of IMIs in broad prevention initiatives.

Interpersonal factors in internet-based cognitive behavioral therapy for depression: Attachment style and alliance with the program and with the therapist.

Objective This open-trial study examined effects of a culturally-adapted Hebrew version of guided internet-based cognitive behavioural therapy (ICBT) for depression. We examined therapeutic alliance with the therapist and with the programme (content) as potential predictors of outcomes. Furthermore, we examined whether anxious and avoidant attachment styles improved, although relationships were not the focus of treatment. Method: We examined alliance with therapist and alliance with programme and their time-lagged (1 week), longitudinal relationship with depression outcomes, and change in anxious and avoidant attachment during treatment. Results: Depression and insomnia improved significantly (Cohen's d: depression = 1.34, insomnia = 0.86), though dropout was relatively high (49%). Alliance with programme and with the therapist predicted adherence and dropout, whereas only alliance with therapist predicted symptom improvement. Avoidant attachment decreased over treatment whereas anxious attachment did not. Conclusion: A culturally-adapted version of ICBT for depression showed that alliance with therapist and alliance with programme both can play an important role in its effectiveness: alliance with programme and the therapist drive adherence and dropout and alliance with therapist is related to symptom improvement. Although the focus of treatment is not interpersonal, avoidant attachment style can improve following ICBT.

Effectiveness of an online recovery training for employees exposed to blurred boundaries between work and non-work: Bayesian analysis of a randomised controlled trial.

BACKGROUND: Blurred work-non-work boundaries can have negative effects on mental health, including sleep. OBJECTIVES: In a randomised control trial, we aimed to assess the effectiveness of an online recovery training programme designed to improve symptoms of insomnia in a working population exposed to blurred boundaries. METHODS: 128 participants with severe insomnia symptoms (Insomnia Severity Index ≥15) and working under blurred work and non-work conditions (segmentation supplies <2.25) were randomly assigned to either the recovery intervention or a waitlist control group (WLC). The primary outcome was insomnia severity, assessed at baseline, after 2 months (T2) and 6 months (T3). FINDINGS: A greater reduction in insomnia was observed in the intervention compared with the WLC group at both T2 (d=1.51; 95% CI=1.12 o 1.91) and T3 (d=1.63; 95% CI=1.23 to 2.03]. This was shown by Bayesian analysis of covariance (ANCOVA), whereby the ANCOVA model yielded the highest Bayes factor (BF 10=3.23×e60] and a 99.99% probability. Likewise, frequentist analysis revealed significantly reduced insomnia at both T2 and T3. Beneficial effects were found for secondary outcomes including depression, work-related rumination, and mental detachment from work. Study attrition was 16% at T2 and 44% at T3. CONCLUSIONS: The recovery training was effective in reducing insomnia symptoms, work related and general indicators of mental health in employees exposed to blurred boundaries, both at T2 and T3. CLINICAL IMPLICATIONS: In addition to demonstrating the intervention's effectiveness, this study exemplifies the utilisation of the Bayesian approach in a clinical context and shows its potential to empower recipients of interventional research by offering insights into result probabilities, enabling them to draw informed conclusions. TRIAL REGISTRATION NUMBER: German Clinical Trial Registration (DRKS): DRKS00006223, https://drks.de/search/de/trial/DRKS00006223.

Fishing for oil and meat drives irreversible defaunation of deepwater sharks and rays.

The deep ocean is the last natural biodiversity refuge from the reach of human activities. Deepwater sharks and rays are among the most sensitive marine vertebrates to overexploitation. One-third of threatened deepwater sharks are targeted, and half the species targeted for the international liver-oil trade are threatened with extinction. Steep population declines cannot be easily reversed owing to long generation lengths, low recovery potentials, and the near absence of management. Depth and spatial limits to fishing activity could improve conservation when implemented alongside catch regulations, bycatch mitigation, and international trade regulation. Deepwater sharks and rays require immediate trade and fishing regulations to prevent irreversible defaunation and promote recovery of this threatened megafauna group.

Who benefits from indirect prevention and treatment of depression using an online intervention for insomnia? Results from an individual-participant data meta-analysis.

BACKGROUND: Major depressive disorder (MDD) is highly prevalent and burdensome for individuals and society. While there are psychological interventions able to prevent and treat MDD, uptake remains low. To overcome structural and attitudinal barriers, an indirect approach of using online insomnia interventions seems promising because insomnia is less stigmatized, predicts MDD onset, is often comorbid and can outlast MDD treatment. This individual-participant-data meta-analysis evaluated the potential of the online insomnia intervention GET.ON Recovery as an indirect treatment to reduce depressive symptom severity (DSS) and potential MDD onset across a range of participant characteristics. METHODS: Efficacy on depressive symptom outcomes was evaluated using multilevel regression models controlling for baseline severity. To identify potential effect moderators, clinical, sociodemographic, and work-related variables were investigated using univariable moderation and random-forest methodology before developing a multivariable decision tree. RESULTS: IPD were obtained from four of seven eligible studies (N = 561); concentrating on workers with high work-stress. DSS was significantly lower in the intervention group both at post-assessment (d = -0.71 [95% CI-0.92 to -0.51]) and at follow-up (d = -0.84 [95% CI -1.11 to -0.57]). In the subsample (n = 121) without potential MDD at baseline, there were no significant group differences in onset of potential MDD. Moderation analyses revealed that effects on DSS differed significantly across baseline severity groups with effect sizes between d = -0.48 and -0.87 (post) and d = - 0.66 to -0.99 (follow-up), while no other sociodemographic, clinical, or work-related characteristics were significant moderators. CONCLUSIONS: An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.

Clinical and cognitive insight in panic disorder: phenomenology and treatment effects in internet cognitive behavior therapy.

Clinical observations suggest that individuals with panic disorder (PD) vary in their beliefs about the causes of their panic attacks. Some attribute these attacks to psychological factors, while others to physiological or medical factors. These beliefs also extend to whether individuals perceive panic attacks as dangerous. In other areas of psychiatric nosology, these phenomena are commonly called clinical insight (recognition of disorder and the need for treatment) and cognitive insight (the ability to reflect on one's beliefs). Despite its importance, limited research exists on insight in PD and its relation to symptoms and treatment outcomes. This study examines clinical and cognitive insight in 83 patients with PD who received internet-based cognitive behavioral therapy, investigating their relationship with symptoms, treatment outcomes, and changes in insight. We assessed patients using interview and self-report measures of insight and symptoms. Clinical and cognitive insight were correlated and both constructs improved significantly during treatment. Good clinical insight pretreatment was positively correlated with more severe pretreatment symptoms. Pretreatment clinical and cognitive insight were not correlated with symptom change or attrition. Greater change in clinical and cognitive insight was related to greater change in symptoms. The findings highlight the significance of clinical and cognitive insight in PD, and the importance of distinguishing between them. This suggests the need to develop interventions according to patients' level of insight, particularly focusing on those lacking insight. Further research is essential to advance our understanding of the relationship between insight and the phenomenology and treatment of PD.

Are web-based stress management interventions effective as an indirect treatment for depression? An individual participant data meta-analysis of six randomised trials.

QUESTION: Depression is highly prevalent and associated with numerous adverse consequences for both individuals and society. Due to low uptake of direct treatment, interventions that target related, but less stigmatising problems, such as perceived stress, have emerged as a new research paradigm.This individual participant data (IPD) meta-analysis examines if a web-based stress management intervention can be used as an 'indirect' treatment of depression. STUDY SELECTION AND ANALYSIS: Bayesian one-stage models were used to estimate pooled effects on depressive symptom severity, minimally important improvement and reliable deterioration. The dose-response relationship was examined using multilevel additive models, and IPD network meta-analysis was employed to estimate the effect of guidance. FINDINGS: In total, N=1235 patients suffering from clinical-level depression from K=6 randomised trials were included. Moderate-to-large effects were found on depressive symptom severity at 7 weeks post-intervention (d=-0.65; 95% credibility interval (CrI): -0.84 to -0.48) as measured with the Center for Epidemiological Studies' Depression Scale. Effects were sustained at 3-month follow-up (d=-0.74; 95% CrI: -1.01 to -0.48). Post-intervention symptom severity was linearly related to the number of completed sessions. The incremental impact of guidance was estimated at d=-0.25 (95% CrI: -1.30 to 0.82), with a 35% posterior probability that guided and unguided formats produce equivalent effects. CONCLUSIONS: Our results indicate that web-based stress management can serve as an indirect treatment, yielding effects comparable with direct interventions for depression. Further research is needed to determine if such formats can indeed increase the utilisation of evidence-based treatment, and to corroborate the favourable effects for human guidance. STUDY REGISTRATION: Open material repository: osf.io/dbjc8, osf.io/3qtbe. TRIAL REGISTRATION NUMBER: German Clinical Trial Registration (DRKS): DRKS00004749, DRKS00005112, DRKS00005384, DRKS00005687, DRKS00005699, DRKS00005990.

The Evaluation of the GET.ON Nationwide Web-Only Treatment Service for Depression- and Stress-Related Symptoms: Naturalistic Trial.

BACKGROUND: GET.ON (HelloBetter) treatment interventions have been shown to be efficacious in multiple randomized controlled trials. OBJECTIVE: This study evaluated the effectiveness of 2 GET.ON interventions, GET.ON Mood Enhancer and GET.ON Stress, in a national digital mental health service implemented across Germany. METHODS: Following an initial web-based questionnaire, participants were allocated to either intervention based on their baseline symptom severity and personal choice and received a semistandardized guided, feedback-on-demand guided, or self-guided version of the treatment. Uncontrolled routine care data from 851 participants were analyzed using a pretest-posttest design. Half of the participants (461/851, 54.2%) were allocated to the stress intervention (189/461, 41% semistandardized; 240/461, 52% feedback on demand; and 32/461, 6.9% self-guided), and almost all participants in the mood intervention (349/352, 99.2%) received semistandardized guidance. RESULTS: Results on depression-related symptom severity indicated a reduction in reported symptoms, with a large effect size of d=-0.92 (95% CI -1.21 to -0.63). Results on perceived stress and insomnia indicated a reduction in symptom severity, with large effect sizes of d=1.02 (95% CI -1.46 to -0.58) and d=-0.75 (95% CI -1.10 to -0.40), respectively. A small percentage of participants experienced deterioration in depression-related symptoms (11/289, 3.8%), perceived stress (6/296, 2%), and insomnia (5/252, 2%). After completing treatment, 51.9% (150/289) of participants showed a clinically reliable change in depression-related symptoms, whereas 20.4% (59/289) achieved a close to symptom-free status. Similar improvements were observed in perceived stress and insomnia severity. Guidance moderated the effectiveness of and adherence to the interventions in reducing depressive symptom severity. Effect sizes on depression-related symptom severity were d=-1.20 (95% CI -1.45 to -0.93) for the semistandardized group, d=-0.36 (95% CI -0.68 to -0.04) for the feedback-on-demand group, and d=-0.83 (95% CI -1.03 to -0.63) for the self-guided group. Furthermore, 47.6% (405/851) of the participants completed all modules of the intervention. Participant satisfaction was high across all patient groups and both interventions; 89.3% (242/271) of participants would recommend it to a friend in need of similar help. Limitations include the assignment to treatments and guidance formats based on symptom severity. Furthermore, part of the differences in symptom change between groups must be assumed to be due to this baseline difference in the measures. CONCLUSIONS: Future digital health implementation and routine care research should focus on monitoring symptom deterioration and other negative effects, as well as possible predictors of deterioration and the investigation of individual patient trajectories. In conclusion, this study supports the effectiveness of tailored digital mental health services in routine care for depression- and stress-related symptoms in Germany. The results highlight the importance of guidance in delivering internet-based cognitive behavioral therapy interventions and provide further evidence for its potential delivered as web-only solutions for increasing access to and use of psychological treatments.

Additive effects of adjunctive app-based interventions for mental disorders - A systematic review and meta-analysis of randomised controlled trials.

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.

Predicting effects of a digital stress intervention for patients with depressive symptoms: Development and validation of meta-analytic prognostic models using individual participant data.

OBJECTIVE: Digital stress interventions could be helpful as an "indirect" treatment for depression, but it remains unclear for whom this is a viable option. In this study, we developed models predicting individualized benefits of a digital stress intervention on depressive symptoms at 6-month follow-up. METHOD: Data of N = 1,525 patients with depressive symptoms (Center for Epidemiological Studies' Depression Scale, CES-D ≥ 16) from k = 6 randomized trials (digital stress intervention vs. waitlist) were collected. Prognostic models were developed using multilevel least absolute shrinkage and selection operator and boosting algorithms, and were validated using bootstrap bias correction and internal-external cross-validation. Subsequently, expected effects among those with and without a treatment recommendation were estimated based on clinically derived treatment assignment cut points. RESULTS: Performances ranged from R² = 21.0%-23.4%, decreasing only slightly after model optimism correction (R² = 17.0%-19.6%). Predictions were greatly improved by including an interim assessment of depressive symptoms (optimism-corrected R2 = 32.6%-35.6%). Using a minimally important difference of d = -0.24 as assignment cut point, approximately 84.6%-93.3% of patients are helped by this type of intervention, while the remaining 6.7%-15.4% would experience clinically negligible benefits (δ^ = -0.02 to -0.19). Using reliable change as cut point, a smaller subset (39.3%-46.2%) with substantial expected benefits (δ^ = -0.68) receives a treatment recommendation. CONCLUSIONS: Meta-analytic prognostic models applied to individual participant data can be used to predict differential benefits of a digital stress intervention as an indirect treatment for depression. While most patients seem to benefit, the developed models could be helpful as a screening tool to identify those for whom a more intensive depression treatment is needed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Validation of the German Normalisation Process Theory Measure G-NoMAD: translation, adaptation, and pilot testing.

BACKGROUND: Implementing evidence-based healthcare practices (EBPs) is a complex endeavour and often lags behind research-informed decision processes. Understanding and systematically improving implementation using implementation theory can help bridge the gap between research findings and practice. This study aims to translate, pilot, and validate a German version of the English NoMAD questionnaire (G-NoMAD), an instrument derived from the Normalisation Process Theory, to explore the implementation of EBPs. METHODS: Survey data has been collected in four German research projects and subsequently combined into a validation data set. Two versions of the G-NoMAD existed, independently translated from the original English version by two research groups. A measurement invariance analysis was conducted, comparing latent scale structures between groups of respondents to both versions. After determining the baseline model, the questionnaire was tested for different degrees of invariance (configural, metric, scalar, and uniqueness) across samples. A confirmatory factor analysis for three models (a four-factor, a unidimensional, and a hierarchical model) was used to examine the theoretical structure of the G-NoMAD. Finally, psychometric results were discussed in a consensus meeting, and the final instructions, items, and scale format were consented to. RESULTS: A total of 539 health care professionals completed the questionnaire. The results of the measurement invariance analysis showed configural, partial metric, and partial scalar invariance indicating that the questionnaire versions are comparable. Internal consistency ranged from acceptable to good (0.79 ≤ α ≤ 0.85) per subscale. Both the four factor and the hierarchical model achieved a better fit than the unidimensional model, with indices from acceptable (SRMR = 0.08) to good (CFI = 0.97; TLI = 0.96). However, the RMSEA values were only close to acceptable (four-factor model: χ2164 = 1029.84, RMSEA = 0.10; hierarchical model: χ2166 = 1073.43, RMSEA = 0.10). CONCLUSIONS: The G-NoMAD provides a reliable and promising tool to measure the degree of normalisation among individuals involved in implementation activities. Since the fit was similar in the four-factor and the hierarchical model, priority should be given to the practical relevance of the hierarchical model, including a total score and four subscale scores. The findings of this study support the further usage of the G-NoMAD in German implementation settings. TRIAL REGISTRATION: Both the AdAM project (No. NCT03430336, 06/02/2018) and the EU-project ImpleMentAll (No. NCT03652883, 29/08/2018) were registered on ClinicalTrials.gov. The ImplementIT study was registered at the German Clinical Trial Registration (No. DRKS00017078, 18/04/2019). The G-NoMAD validation study was registered at the Open Science Framework (No7u9ab, 17/04/2023).

Optimizing the predictive power of depression screenings using machine learning.

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 AUCQIDS-16 = 0.94, AUCHAM-D-17 = 0.88, and AUCPHQ-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.

An Online Mindfulness Intervention for International Students: A Randomized Controlled Feasibility Trial.

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 (ß = .34), well-being (ß = .37), and anxiety (ß = -.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.

How to promote usage of telehealth interventions for farmers' mental health? A qualitative study on supporting and hindering aspects for acceptance and satisfaction with a personalized telephone coaching for depression prevention.

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.

Predicting heterogeneous treatment effects of an Internet-based depression intervention for patients with chronic back pain: Secondary analysis of two randomized controlled trials.

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.

Internet-Based Treatment of Body Dysmorphic Disorder: Feasibility, Evaluation, and Self-Report Data.

ABSTRACT: Initial findings indicate the effectiveness of internet-based interventions for body dysmorphic disorder (BDD). In order to substantiate these findings, a seven-module guided internet-based intervention was created and examined. We report the mixed data of participants with clinical and subclinical BDD of the treatment group (n = 18). We investigated the feasibility, the quality of the program content, the design and usability, and its effects on symptom severity and related psychopathology. Adherence to the intervention was low and dropout rate high (55.6%). The program content, perceived website usability, and visual aesthetic were rated high. Credibility and expectancy were on a medium level. Satisfaction with appearance improved significantly in the intention-to-treat analysis (d = 0.58). In sum, symptom-related outcomes and program evaluation showed a positive trend albeit the study conduction was difficult. Future programs should investigate the role of additional motivation strategies and more flexible support addressing the known treatment barriers.

Evaluation of randomized controlled trials: a primer and tutorial for mental health researchers.

BACKGROUND: Considered one of the highest levels of evidence, results of randomized controlled trials (RCTs) remain an essential building block in mental health research. They are frequently used to confirm that an intervention "works" and to guide treatment decisions. Given their importance in the field, it is concerning that the quality of many RCT evaluations in mental health research remains poor. Common errors range from inadequate missing data handling and inappropriate analyses (e.g., baseline randomization tests or analyses of within-group changes) to unduly interpretations of trial results and insufficient reporting. These deficiencies pose a threat to the robustness of mental health research and its impact on patient care. Many of these issues may be avoided in the future if mental health researchers are provided with a better understanding of what constitutes a high-quality RCT evaluation. METHODS: In this primer article, we give an introduction to core concepts and caveats of clinical trial evaluations in mental health research. We also show how to implement current best practices using open-source statistical software. RESULTS: Drawing on Rubin's potential outcome framework, we describe that RCTs put us in a privileged position to study causality by ensuring that the potential outcomes of the randomized groups become exchangeable. We discuss how missing data can threaten the validity of our results if dropouts systematically differ from non-dropouts, introduce trial estimands as a way to co-align analyses with the goals of the evaluation, and explain how to set up an appropriate analysis model to test the treatment effect at one or several assessment points. A novice-friendly tutorial is provided alongside this primer. It lays out concepts in greater detail and showcases how to implement techniques using the statistical software R, based on a real-world RCT dataset. DISCUSSION: Many problems of RCTs already arise at the design stage, and we examine some avoidable and unavoidable "weak spots" of this design in mental health research. For instance, we discuss how lack of prospective registration can give way to issues like outcome switching and selective reporting, how allegiance biases can inflate effect estimates, review recommendations and challenges in blinding patients in mental health RCTs, and describe problems arising from underpowered trials. Lastly, we discuss why not all randomized trials necessarily have a limited external validity and examine how RCTs relate to ongoing efforts to personalize mental health care.

Case report for an internet- and mobile-based intervention for internet use disorder.

Background and aims: Internet 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. Methods: The 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. Results: The 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 conclusions: This 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 Registration: https://clinicaltrials.gov/,DRKS00015314.