BACKGROUND:Adolescent and young adult (AYA) mothers often experience unmet psychosocial needs, and those under 25 years of age are at increased risk of perinatal depression. Although home visiting programmes may be beneficial, no controlled trial has evaluated a programme co-designed with first-time AYA mothers and grounded in their lived experiences. OBJECTIVE:We evaluated the effect of the co-designed Early Partnership programme on perceived fulfilment of psychosocial needs and postnatal depressive symptoms among first-time AYA mothers. METHODS:We emulated a target trial using data from a pragmatic historically controlled study in four Tokyo municipalities. Participants were primiparous women aged 16-25 years. The intervention group included 151 participants and the control group included 158 participants. The intervention group received intensive tailored home visits by multi-professional family support workers from pregnancy to 12 months postnatally, and the historical control group received publicly funded health and social services. FINDINGS:Retention at 12 months was high in both groups (intervention group, 82.1%; control group, 82.9%). For the primary outcome analysis, the intervention group had greater improvement in perceived fulfilment of psychosocial needs at 6 months postnatally (difference in mean changes 4.16, 95% CI 1.35 to 6.97, Cohen's d 0.40, 95% CI 0.13 to 0.67) and 12 months postnatally (difference in mean changes 3.93, 95% CI 0.63 to 7.23, Cohen's d 0.39, 95% CI 0.06 to 0.72) than the control group. Postnatal depressive symptoms were lower in the intervention group at 6 months postnatally (mean difference -1.54, 95% CI -2.70 to -0.38, Cohen's d -0.34, 95% CI -0.59 to -0.08) and 12 months postnatally (mean difference -1.55, 95% CI -2.74 to -0.36, Cohen's d -0.34, 95% CI -0.61 to -0.07). Well-being also improved at each time point, but estimates were imprecise. CONCLUSIONS:The Early Partnership programme, co-designed with young mothers and delivered by multi-professional teams, was acceptable and effective in improving perceived fulfilment of psychosocial needs and postnatal depressive symptoms. CLINICAL IMPLICATIONS:These findings suggest that a person-centred and relationship-based home visiting model, delivered through a non-stigmatising design, may represent a plausible model of maternal care.

Background: Server-based screening tools impose subscription costs, while open-source alternatives require coding skills. Objectives: We developed a browser extension that provides no-code, serverless artificial intelligence (AI)-assisted title and abstract screening and examined its functionality. Methods: TiAb Review Plugin is an open-source Chrome browser extension (available at https://chromewebstore.google.com/detail/tiab-review-plugin/alejlnlfflogpnabpbplmnojgoeeabij). It uses Google Sheets as a shared database, requiring no dedicated server and enabling multi-reviewer collaboration. Users supply their own Gemini API key, stored locally and encrypted. The tool offers three screening modes: manual review, large language model (LLM) batch screening, and machine learning (ML) active learning. For ML evaluation, we re-implemented the default ASReview active learning algorithm (TF-IDF with Naive Bayes) in TypeScript to enable in-browser execution, and verified equivalence against the original Python implementation using 10-fold cross-validation on six datasets. For LLM evaluation, we compared 16 parameter configurations across two model families on a benchmark dataset, then validated the optimal configuration (Gemini 3.0 Flash, low thinking budget, TopP=0.95) with a sensitivity-oriented prompt on five public datasets (1,038 to 5,628 records, 0.5 to 2.0 percent prevalence). Results: The TypeScript classifier produced top-100 rankings 100 percent identical to the original ASReview across all six datasets. For LLM screening, recall was 94 to 100 percent with precision of 2 to 15 percent, and Work Saved over Sampling at 95 percent recall (WSS@95) ranged from 48.7 to 87.3 percent. Conclusions: We developed a functional browser extension that integrates LLM screening and ML active learning into a no-code, serverless environment, ready for practical use in systematic review screening.

BACKGROUND:This study aimed to examine the effectiveness of smartphone-delivered cognitive behavioral therapy (CBT) in participants with subthreshold depression, considering the potential influence of physical comorbidities. METHODS:In this secondary analysis of the RESiLIENT trial, participants with subthreshold depression were randomized to various CBT interventions or control groups. Physical comorbidities were self-reported at baseline and categorized as no, past, or current. Depression severity was assessed by the Patient Health Questionnaire-9 (PHQ-9) at weeks 6 and 26. Mixed-effects models for repeated measures estimated treatment effects and tested interaction terms for comorbidity category. Latent class analysis (LCA) explored multimorbidity patterns and their impact on outcomes. RESULTS:A total of 3577 participants were analyzed (no comorbidity n = 1384; past comorbidity n = 1004; current comorbidity n = 1189). All CBT interventions improved PHQ-9 scores at week 6 across comorbidity groups. Behavioral activation (BA) combined with problem solving showed the largest effects in the no comorbidity (least-squares mean difference = -1.74, 95% confidence interval: -2.44 to -1.05) and current comorbidity groups (-1.94, -2.67 to -1.20), while BA alone was most effective in the past comorbidity group (-1.91, -2.69 to -1.14). By week 26, BA combined with cognitive restructuring maintained benefits across all groups. LCA identified five multimorbidity classes. Although the effect sizes showed small variations across subgroups, no significant effect modification by comorbidity type was found. CONCLUSIONS:Smartphone-delivered CBT effectively reduces depressive symptoms in subthreshold depression, including among individuals with physical comorbidities. Although comorbidity type did not significantly modify outcomes, the observed patterns may help inform personalized iCBT strategies.

There is a need for greater recognition of clinical psychopharmacology endpoints, including instances where specific psychotropic medications may become unnecessary, redundant, contradictory, or otherwise inappropriate and therefore merit deprescribing. To address circumstances warranting psychotropic medication deprescribing. The American Society of Clinical Psychopharmacology convened a panel of 45 international psychopharmacology experts who developed and completed a multiround Delphi survey and conducted a focused literature review between January and May of 2025, in order to identify areas of consensus or disagreement on key aspects of the deprescribing of psychotropic medications. These included collaborative risk-benefit assessments with patients; pharmacokinetic and pharmacodynamic factors; pharmacogenomics; distinguishing redundant or conflictual from complementary mechanisms of action; managing adverse effects; assuring medication adherence; drug tolerance or tachyphylaxis; medication misuse; and the psychological context and ramifications of deprescribing. Consensus was achieved on 44 of 50 final Delphi statements (88%). Panelists unanimously agreed that components of a pharmacotherapy regimen should undergo periodic review to ensure that treatments target relevant symptoms and have favorable risk-benefit ratios. Key points of consensus were that deprescribing: (1) should not occur without first assessing medication adherence; (2) merits consideration if less than partial therapeutic response is apparent, or if treatment goals have been reached and relapse prevention is not a long-term objective; (3) involves psychological ramifications that warrant attention; (4) should be followed by close clinical monitoring; and (5) risk-benefit decisions should ideally involve active patient participation within a shared decision-making model. Through this Consensus Statement, the Task Force identified circumstances in which the selective elimination of certain psychotropic medications may be clinically indicated. Empirical trials are needed to assess the implementation of deprescribing protocols and gauge their safe, effective, and acceptable outcomes.

Importance:Antidepressants for moderate to severe major depressive disorder may be discontinued prematurely because the prescribed antidepressant is not always the most appropriate medication for an individual. Guidelines have recommended more precise targeting of antidepressant treatment. Objective:To evaluate the efficacy of a web-based tool to personalize antidepressant treatment. Design, Setting, and Participants:This multicenter, randomized clinical trial included persons between the ages of 18 and 74 years with major depressive disorder. The trial was conducted at 47 sites in 3 countries (Brazil, Canada, and the UK). The first participant was screened on November 29, 2022, and the last follow-up visit occurred on January 15, 2025. Intervention:A total of 540 participants were randomized (1:1) to an evidence-based clinical decision-support system (PETRUSHKA tool; n = 271) or usual care (n = 269). Main Outcomes and Measures:The primary outcome was treatment discontinuation due to any cause at 8 weeks. The secondary outcomes included treatment discontinuation up to 24 weeks due to adverse events and changes in depressive symptoms (measured with the 9-item Patient Health Questionnaire [PHQ-9]; range, 0-27; higher scores indicate more severe depression) and anxiety symptoms (measured with the 7-item Generalized Anxiety Disorder [GAD-7] questionnaire; range, 0-21; higher scores indicate more severe symptoms). Results:Of the 520 eligible participants, 493 were included in the primary analysis (median age, 35 [IQR, 25 to 48] years; 58% female; PHQ-9 mean score, 16.6 [SD, 5.1]; GAD-7 mean score, 11.5 [SD, 4.1]). At 8 weeks, 41 of 241 participants (17%) in the PETRUSHKA group discontinued the prescribed antidepressant due to any cause vs 69 of 252 (27%) in the usual care group (adjusted relative risk, 0.62 [95% CI, 0.44 to 0.88]; P = .007). At 8 weeks, 22 of 241 participants (9%) in the PETRUSHKA group discontinued the prescribed antidepressant due to adverse events vs 39 of 252 (16%) in the usual care group (adjusted relative risk, 0.59 [95% CI, 0.36 to 0.97]; P = .04). For the assessment of depressive symptoms at 24 weeks, the mean PHQ-9 score was 7.1 (SD, 5.4) in the PETRUSHKA group vs 9.2 (SD, 6.5) in the usual care group (n = 129 in each group; adjusted between-group mean difference, -1.92 [95% CI, -3.06 to -0.78]; P < .001). For the assessment of anxiety symptoms at 24 weeks, the mean GAD-7 score was 4.6 (SD, 4.1) in the PETRUSHKA group (n = 133) vs 5.8 (SD, 4.9) in the usual care group (n = 126) (adjusted between-group mean difference, -1.39 [95% CI, -2.26 to -0.52]; P = .002). Conclusions and Relevance:Compared with usual care, use of the PETRUSHKA tool increased the number of patients still taking their antidepressant at 8 weeks and improved depressive and anxiety symptoms at 24 weeks. However, lack of a double-blind design and the large amount of missing data limit the validity of these results. Trial Registration:ClinicalTrials.gov Identifier: NCT05608330.

INTRODUCTION:The global burden of depression continues to rise despite evidence that prevention is feasible and cost-effective. Building on the Resilience Enhancement with Smartphone in Living ENvironmenTs (RESiLIENT) randomised controlled trial, the Best, Efficient and Affordable Training in Resilience in Constant Evolution (BEATRICE) platform trial evaluates and optimises smartphone-delivered cognitive-behavioural therapy (CBT) for adults with no to subthreshold depression. The primary objective is to minimise the Total Burden of Depression, measured by the integral of weekly to monthly Patient Health Questionnaire-8 (PHQ-8) scores over 12 months, through a living, adaptive platform trial that sequentially tests multiple clinical questions and personalised algorithms. METHODS AND ANALYSIS:BEATRICE is a nationwide, digitally centralised, multi-arm platform trial conducted via the 'Resilience Training App'. Eligible participants are adults (aged ≥18 years) with PHQ-8 ≤14, fluent in Japanese, owning a smartphone and not currently receiving mental health treatment. Recruitment takes place through health-insurance associations, companies, municipalities and online outreach. Participants are randomised centrally to CBT skill modules-behavioural activation, assertion training, behaviour therapy for insomnia, cognitive restructuringor problem-solving-delivered alone or in combination. Assessments are open-label and completed digitally by self-reports.The initial list of clinical questions to be examined in this platform trial includes: external validity of the personalised and optimised algorithm for first-line interventions, strategies to help individuals not on track during initial weeks, second-line interventions at 6 months, development of super-personalised and optimised therapy algorithm, that is, longitudinally personalised and optimised in response to individuals' responses after the first-line assignment. The primary outcomes, sample sizes and statistical analyses differ depending on the clinical question addressed within the platform trial. ETHICS AND DISSEMINATION:Approved by the Ethics Committee of Kyoto University Graduate School of Medicine (C1733). Results will be disseminated via peer-reviewed publications, conferences and public reports. TRIAL REGISTRATION NUMBER:UMIN000058696.

Importance: Psychological interventions are a mainstay of treatment for substance use disorders (SUDs), but their ingredients remain unknown. Objective: Identify components of evidence-based psychological interventions for a SUD class and develop a transtheoretical taxonomy. Data sources: The National Library of Medicine via PubMed, searched on 11/01/2023 (update 04/01/2025) for network meta-analyses (NMAs) published since 11/01/2018, using keywords related to substance types, psychotherapy and NMAs. Study selection: Evidence-based psychological interventions were identified from randomized controlled trials (RCTs) included in one large, recent NMA of stand-alone interventions targeting stimulant use disorders. This NMA comprised 50 RCTs comparing any structured psychosocial intervention to active control or treatment as usual for stimulant (cocaine and/or amphetamine) use disorder in adults, with 10 more RCTs identified in the search update. Two independent researchers identified all intervention arms containing structured psychological components. Data extraction and synthesis: PRISMA 2020 reporting guidelines were followed. Two researchers retrieved complete intervention descriptions (e.g., protocols, manuals) and independently and iteratively extracted components, with multiple consensus meetings for groups of 3-5 RCTs to standardize extraction and coding decisions. Components were organized into higher-order categories with shared functional characteristics and unified definitions. The taxonomy was discussed and amended in a 2.5-days expert meeting. Inter-rater reliability (Cohen’s kappa) was estimated for a random subset of 35% of intervention arms, assessed independently by two new researchers. Main outcome(s) and measure(s): Transtheoretical components and unique intervention profiles, defined as distinct combinations of these. Results: 109 psychological intervention arms yielded 1592 elements, subsequently consolidated into 25 distinct transtheoretical components. Based on this taxonomy, 109 psychological arms were condensed in 40 unique profiles. The most frequently employed components were relapse prevention (34 profiles), functional analysis (32), skill generalization (29), and therapeutic alliance (29). The least frequent components were mindfulness &amp; meditation (3) and subpopulation issues (4). Cohen’s kappa was fair (0.2-0.40) for two components, moderate (0.41-0.6) for four, and substantial (over 0.60) for eleven (remaining components had low prevalence). Conclusions and relevance: Recasting psychological interventions as unique combinations of transtheoretical components instead of trademarked protocols could revolutionize treatment evaluation and delivery and accelerate mechanisms of change identification.

BackgroundAlcohol consumption is a major global contributor to morbidity and mortality and is a well-established risk factor for multiple cancers. Acetaldehyde, a toxic metabolite of ethanol, is a causal factor in alcohol-related esophageal cancer. A substantial proportion of the Japanese population carries the aldehyde dehydrogenase 2*2 (ALDH2*2) allele, which impairs ALDH2 enzymatic activity and increases acetaldehyde exposure, thereby elevating esophageal cancer risk. Among individuals with the ALDH2*2 allele, cancer risk demonstrates a clear dose-response relationship with alcohol consumption, with relative risks reported to be up to four times the relative risk, compared to non-carriers.ObjectivesThis project aims to evaluate the efficacy of an unguided, web-based brief intervention (BI) incorporating genetic cancer-risk education to reduce alcohol consumption in a randomized controlled trial.MethodsParticipants will be recruited online between March and July 2026 through a Japanese research panel company. Eligibility will include moderate alcohol use and probable ALDH2*2 allele status. Participants will be randomized to either an experimental condition or a sham educational control. The experimental group will receive an unguided, web-based, brief video intervention providing information on genetic cancer risks associated with alcohol consumption and the benefits of reducing drinking. The primary outcome will be mean past-4-week alcohol quantity at the 3-month endpoint. Secondary outcomes will include alcohol use in grams, alcohol-related severity, motivation to change, health-knowledge retention, participant satisfaction, and quality of life. Assessments will occur at baseline and at 1, 2, and 3 months post-randomization via a secure web portal.DiscussionThis intervention is expected to reduce unhealthy alcohol use at low implementation cost by leveraging personalized genetic risk information as a motivational mechanism in the general population. Additional between-group differences are anticipated across secondary alcohol-related outcomes. Trial Registration: This trial registered on 11/28/2025 in the University Hospital Medical Information Network Clinical Trials Registry (UMIN000058012).

Irritable bowel syndrome (IBS) may significantly impair the quality of life (QoL) of affected individuals and carries substantial socio-economic consequences. Cognitive-behavioural therapy (CBT) is recommended as one treatment option for IBS. However, its widespread use is limited by a shortage of qualified therapists, insufficient facilities, and the burden of hospital visits. Internet-based CBT (iCBT) has the potential to overcome these challenges. We aim to evaluate the efficacy and cost-effectiveness of iCBT for treating drug-refractory IBS through rigorous methodology. This is a single-blind, multicentre, randomised controlled trial. We will recruit adults (≥ 18 years) with moderate-to-severe drug-refractory IBS (target sample size: 132, allowing for an estimated 20

Importance: Psychological interventions are a mainstay of treatment for substance use disorders (SUDs), but their ingredients remain unknown. Objective: Identify components of evidence-based psychological interventions for a SUD class and develop a transtheoretical taxonomy. Data sources: The National Library of Medicine via PubMed, searched on 11/01/2023 (update 04/01/2025) for network meta-analyses (NMAs) published since 11/01/2018, using keywords related to substance types, psychotherapy and NMAs. Study selection: Evidence-based psychological interventions were identified from randomized controlled trials (RCTs) included in one large, recent NMA of stand-alone interventions targeting one type of SUD. This NMA comprised 50 RCTs comparing any structured psychosocial intervention to active control or treatment as usual for stimulant (cocaine and/or amphetamine) use disorder in adults, with 10 more RCTs identified in the search update. Two independent researchers identified all intervention arms containing structured psychological components. Data extraction and synthesis: PRISMA 2020 reporting guidelines were followed. Two researchers retrieved complete intervention descriptions (e.g., protocols, manuals) and independently and iteratively extracted components, with multiple consensus meetings for groups of 3-5 RCTs to standardize extraction and coding decisions. Components were organized into higher-order categories with shared functional characteristics and unified definitions. The taxonomy was discussed and amended in a 2.5-days expert meeting. Inter-rater reliability (Cohen’s kappa) was estimated for a random subset of 35% of intervention arms, assessed independently by two new researchers. Main outcome(s) and measure(s): Transtheoretical components and unique intervention profiles, defined as distinct combinations of these. Results: 109 psychological intervention arms yielded 1592 elements, subsequently consolidated into 25 distinct transtheoretical components. Based on this taxonomy, 109 psychological arms were condensed in 40 unique profiles. The most frequently employed components were relapse prevention (34 profiles), functional analysis (32), skill generalization (29), and therapeutic alliance (29). The least frequent components were mindfulness &amp; meditation (3) and subpopulation issues (4). Cohen’s kappa was fair (0.2-0.40) for two components, moderate (0.41-0.6) for four, and substantial (over 0.60) for eleven (remaining components had low prevalence). Conclusions and relevance: Recasting psychological interventions as unique combinations of transtheoretical components instead of trademarked protocols could revolutionize treatment evaluation and delivery and accelerate mechanisms of change identification.

Abstract Background Evidence syntheses can support early-stage research by identifying and prioritising promising new directions. Combining human and animal evidence can provide insights that neither source alone can offer, particularly for emerging interventions, therapeutic targets and mechanisms of action. Involving people with lived experience (PWLE) can further improve the relevance and interpretability of evidence. However, integrating human and animal studies within a living, co-produced process raises methodological, translational, and epistemological challenges. Methods We describe a framework for co-producing research questions, conducting living systematic reviews of human and animal studies, synthesising and appraising each evidence thesis, and using structured triangulation to inform research prioritisation. The framework was developed within the Global Alliance for Living Evidence on aNxiety, depressiOn and pSychosis (GALENOS) by methodologists, statisticians, domain experts, and PWLE. The GALENOS framework builds on established best practices in systematic reviews, co-production methods, and emerging automation approaches, while introducing targeted methodological developments that integrate these components into structured Summary of Evidence Tables (SETs) designed for evidence triangulation. It further advances concepts of triangulation by providing the GALENOS Approach to Triangulating Evidence (GATE): a structured approach for integrating human and animal evidence within SETs to support research prioritisation and translational decision-making. Examples from GALENOS living systematic reviews, including those on TAAR1 agonists for psychosis and on pro-dopaminergic interventions for anhedonia, illustrate how the framework is applied in practice. Conclusions The GALENOS framework shows how living, co-produced, and triangulated evidence can support early-phase research and strengthen research prioritisation. By combining source-specific synthesis with transparent appraisal and structured triangulation, the approach can help identify which findings are robust, which uncertainties matter most and which future studies are most likely to advance mental health science.

BACKGROUND:Evaluating adherence to PRISMA 2020 guideline remains a burden in the peer review process. However, there is a lack of shareable benchmarks for evaluating large language model (LLM) performance in this task. METHODS:We constructed a copyright-aware benchmark of 108 Creative Commons-licensed systematic reviews. We first conducted parameter optimization using five SRs from the Suda dataset, then compared five checklist input formats (Markdown, JSON, XML, plain text, and manuscript-only control) using ten development-phase LLMs on ten further SRs from the Suda dataset, and finally validated the locked Markdown pipeline using nineteen LLMs on ten SRs from the Tsuge dataset as additional frontier models became available during the study period. RESULTS:Supplying structured PRISMA 2020 checklists yielded 78.7-79.7% accuracy versus 45.2% for manuscript-only input, with paired aggregate analyses showing that structured formats outperformed manuscript-only input while structured formats did not differ significantly from one another. In the validation sample, accuracy ranged from 68.5% to 86.0% with distinct sensitivity-specificity trade-offs. Using Qwen3-Max on the full dataset (n = 120), we achieved 95.1% sensitivity and 49.3% specificity. DISCUSSION:Structured checklist provision substantially improves LLM-based PRISMA assessment. However, given the observed proportion of false positives, human expert verification remains essential before editorial decisions.

INTRODUCTION:Perinatal depression poses substantial risks to both mothers and their offspring. Given its chronic and recurrent nature, developing effective prevention strategies is crucial. Internet-based cognitive-behavioural therapy (iCBT) has shown promise. However, the efficacy of specific CBT skills and the influence of individual differences remain unclear. METHODS AND ANALYSIS:This protocol describes two harmonised multicentre, open-label, six-arm randomised controlled trials. Across both trials, a total of 2400 pregnant women between 10 and 20 weeks of gestation will be enrolled. After completing psychoeducation (PE), participants will be randomised to either the control condition (PE only) or one of five CBT programmes: behavioural activation (BA), assertion training, BA+cognitive restructuring, BA + problem solving or BA + behaviour therapy for insomnia. The objectives of the study are: (1) to ascertain that the iCBT approach is effective in perinatal depression, (2) to identify active CBT skills for perinatal women and (3) to examine interactions between these CBT skills and individuals' baseline characteristics to find personalised and optimised therapy for individual women. The primary outcome is the point prevalence of depression at 1 month postpartum, defined as scoring of 9 or higher on the Edinburgh Postnatal Depression Scale. ETHICS AND DISSEMINATION:The study has been approved by the Kyoto University Graduate School of Medicine Ethics Committee (C1710) and Nagoya City University Certified Review Board (2024A007). Anonymised study results will be presented at conferences and published by the investigators in peer-reviewed journals. TRIAL REGISTRATION NUMBER:jRCTs042240162 (hospital-based, on-site trial) and jRCT1050250074 (nationwide online trial).

BACKGROUND:Evidence regarding schizophrenia relapse following acute electroconvulsive therapy (ECT) is sparse compared with that for depression, and we have no clear consensus on relapse proportions. We aimed to provide longitudinal information on schizophrenia relapse following acute ECT. STUDY DESIGN:This systematic review and meta-analysis included randomised controlled trials (RCTs) and observational studies on post-acute ECT relapse and rehospitalization for schizophrenia and related disorders. For the primary outcome, we calculated the post-acute ECT pooled relapse estimates at each timepoint (3, 6, 12, and 24 months post-acute ECT) using a random effects model. For subgroup analyses, we investigated post-acute ECT relapse proportions by the type of maintenance therapy. STUDY RESULTS:Among a total of 6413 records, 29 studies (3876 patients) met our inclusion criteria. The risk of bias was consistently low for all included RCTs (4 studies), although it ranged from low to high for observational studies (25 studies). Pooled estimates of relapse proportions among patients with schizophrenia responding to acute ECT were 24% (95% CI: 15-35), 37% (27-47), 41% (34-49), and 55% (40-69) at 3, 6, 12, and 24 months, respectively. When continuation/maintenance ECT was added to antipsychotics post-acute ECT, the 6-month relapse proportion was 20% (11-32). CONCLUSION:Relapse occurred mostly within 6 months post-acute ECT for schizophrenia, particularly within the first 3 months. Relapse proportions plateaued after 6 months, although more than half of all patients could be expected to relapse within 2 years. Further high-quality research is needed to optimise post-acute ECT treatment strategies in patients with schizophrenia.

Background Smartphone-based cognitive behavioral therapy (CBT) programs offer accessible interventions for subthreshold depression, yet engagement needed for meaningful benefit remains unclear. We examined how lesson and worksheet engagement relate to depressive symptom improvements in a behavioral activation (BA) intervention, accounting for time-varying confounders.Methods This secondary analysis included 298 adults assigned to the BA arm of the RESiLIENT trial, a randomized controlled trial in Japan. Lesson and worksheet completion were treated as time-varying exposures, each yielding four engagement patterns: minimal (Few-Few), early (Many-Few), late (Few-Many), and consistently high (Many-Many). Outcomes were depressive symptom changes measured by the Patient Health Questionnaire-9 (PHQ-9) at weeks 6 and 26. We applied the parametric g-formula to estimate counterfactual PHQ-9 changes under each pattern, adjusting for baseline and time-varying confounders.Results Early lesson engagement during weeks 0-3 was associated with larger PHQ-9 reductions at both weeks 6 and 26, even when later engagement declined (Many-Few vs. Few-Few: week 6: -1.47 [95% CI -2.52 to -0.53]; week 26: -1.27 [-2.53 to -0.17]). In contrast, higher worksheet engagement was linked to improved PHQ-9 at week 6, with maximal benefit among consistently high engagers (Many-Many vs. Few-Few: -1.25 [-2.17 to -0.44]) and late engagers (Few-Many vs. Few-Few: -1.18 [-2.20 to -0.08]), but not persist to week 26.Conclusions Greater engagement with smartphone-delivered BA is associated with larger symptom reductions. Early lesson engagement drives sustained benefit, whereas worksheet engagement did not persist. These findings may guide digital CBT design by emphasizing early lesson completion alongside concurrent skill practice.

INTRODUCTION:Social functioning is a key component of recovery in depression, yet most research on first-line treatments focuses on symptom reduction, and comparative evidence on social functioning is limited. We aimed to evaluate the comparative effects of psychotherapy, antidepressant medication, and their combination on social functioning in adults with major depression. METHODS:We conducted a systematic review and network meta-analysis of randomized controlled trials up to May 1, 2025. Eligible trials compared psychotherapy, antidepressant medication, combined treatment, and control conditions (placebo, care as usual, waitlist, or no/minimal treatment) in adults with major depression. Effects were calculated as standardized mean differences (SMDs) in social functioning instruments (e.g., Sheehan Disability Scale) at posttreatment (mean 12 weeks) and follow-up (mean 32 weeks). Random effects models were used. We assessed risk of bias and conducted sensitivity analyses. Certainty of evidence was evaluated using CINeMA. RESULTS:Of 490 identified trials, 94 (19%; 23,874 participants) reported social functioning and were included. All active treatments outperformed control conditions. Effects varied substantially by control condition type, with waitlist comparisons yielding the largest estimates and comparisons against placebo or care as usual yielding more conservative effects. Combined psychotherapy and pharmacotherapy showed the largest effects versus placebo at posttreatment (SMD 0.75, 95% CI: 0.57-0.94) and follow-up (1.08, 0.62-1.54). Psychotherapy and pharmacotherapy did not differ at posttreatment (SMD 0.10, 95% CI: -0.05 to 0.25) or follow-up (0.27, 95% CI: 0.00-0.54). Certainty of the evidence ranged from moderate to low. CONCLUSION:First-line depression treatments support not only symptom reduction but also meaningful participation in daily life. However, only one-fifth of trials assessed this outcome, highlighting the need to better integrate patient-valued outcomes into future trials.

BACKGROUND:More effective and better tolerated treatments are urgently needed for people with mental health disorders, such as anxiety, depression and psychosis. However, the rate of translation of positive results from early phase studies into clinically validated treatments remains painstakingly slow. The scientific literature on mental health preclinical and early interventions is burgeoning at pace, making it difficult for researchers, practitioners and policymakers to identify and track new developments. OBJECTIVE:As part of the Wellcome-funded Global Alliance of Living Evidence for aNxiety, depressiOn and pSychosis project, we aimed to develop and evaluate an automated approach to track the evolution of mental health research over time, detect emerging trends and suggest open questions. METHODS:Our approach used topic modelling, large language models and time-series forecasting in combination. We applied our approach to a corpus of 182 747 titles and abstracts extracted from the OpenAlex database for 2015-2025. Using topic modelling to identify topics and then tracking topic mentions over time, we built a time series predictive model and predicted 'trendiness' based on sustained increased mentions above baseline expected from model predictions. We evaluated our approach retrospectively using a blinded expert study of a randomly selected sample of trending and not trending topics. Finally, we developed a novel topic-augmented generation approach to suggest open questions in trendy topics and evaluated the approach by comparison to baseline-generated questions without topic augmentation. FINDINGS:Our approach detected 973 topics and predicted 165 (17%) of those as trending. Key topics that the model predicted as trending included 'ketamine for treatment-resistant depression', 'student mental health in academia' and 'COVID-19 psychosis'. We found that domain experts largely agreed with the model's predictions of trendiness. Topic-augmented generated questions were more specific than baseline generated questions. CONCLUSIONS:Our approach enables identification of new developments and open questions. Future work will improve temporal pattern tracking and use full texts. CLINICAL IMPLICATIONS:Our approach can support all stakeholders to gain an overview of the published literature, assess temporal patterns, identify trends and rank open questions.