BMJ Mental Health

Even before the pandemic, the treatment gaps in depression care were substantial, with issues ranging from rates of depression detection and intervention to a lack of follow-up after treatment initiation and access to secondary care services. The COVID-19 pandemic, which has had major effects on global healthcare systems, is almost certain to have impacted the MDD care pathway, though it is unclear what changes have manifested and what opportunities have arisen in response to COVID-19. The extent to which patients receive best-practice care is likely closely linked to clinical outcomes (and therefore disability burden) and as such, it is important to examine treatment gaps on the MDD care pathway during the pandemic. Here, we outline a protocol for a scoping review that investigates this broad topic, focusing on continuity of care and novel methods (e.g. digital approaches) used to mitigate care disruption. This scoping review protocol was designed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) standards and will culminate in a narrative synthesis of evidence.

ObjectivesThe rapid pace, high volume, and limited quality of mental health evidence that has been generated during COVID-19 poses a barrier to understanding mental health outcomes. We sought to summarize results from studies that compared mental health outcomes during COVID-19 to outcomes assessed prior to COVID-19 in the same cohort in the general population and in other groups for which data have been reported. DesignLiving systematic review. Data SourcesMEDLINE (Ovid), PsycINFO (Ovid), CINAHL (EBSCO), EMBASE (Ovid), Web of Science Core Collection: Citation Indexes, China National Knowledge Infrastructure, Wanfang, medRxiv (preprints), and Open Science Framework Preprints (preprint server aggregator). Eligibility criteria for selecting studiesFor this report, we included studies that compared general mental health, anxiety symptoms, or depression symptoms, assessed January 1, 2020 or later, to the same outcomes collected between January 1, 2018 and December 31, 2019. Any population was eligible. We required [≥] 90% of participants pre-COVID-19 and during COVID-19 to be the same or the use of statistical methods to address missing data. For population groups with continuous outcomes for at least two studies in an outcome domain, we conducted restricted maximum-likelihood random-effects meta-analyses. Worse COVID-19 mental health outcomes are reported as positive. Risk of bias of included studies was assessed using an adapted version of the Joanna Briggs Institute Checklist for Prevalence Studies. ResultsAs of April 11, 2022, we had reviewed 94,411 unique titles and abstracts and identified 137 unique eligible studies with data from 134 cohorts. Almost all studies were from high-income (105, 77%) or upper-middle income (28, 20%) countries. Among adult general population studies, we did not find changes in general mental health (standardized mean difference of change [SMDchange = 0.11, 95% CI -0.00 to 0.22) or anxiety symptoms (SMDchange = 0.05, 95% CI -0.04 to 0.13), but depression symptoms worsened minimally (SMDchange = 0.12, 95% CI 0.01 to 0.24). Among women or females, mental health symptoms worsened by minimal to small amounts in general mental health (SMDchange = 0.22, 95% CI 0.08 to 0.35), anxiety symptoms (SMDchange = 0.20, 95% CI 0.12 to 0.29), and depression symptoms (SMDchange = 0.22, 95% CI 0.05 to 0.40). Of 27 other analyses across outcome domains, among subgroups other than women or females, 5 analyses suggested minimal or small amounts of symptom worsening, and 2 suggested minimal or small symptom improvements. No other subgroup experienced statistically significant changes across outcome domains. In the 3 studies with data from March to April 2020 and later in 2020, symptoms either were unchanged from pre-COVID-19 at both time points or increased initially then returned to pre-COVID-19 levels. Heterogeneity measured by the I2 statistic was high (e.g., > 80%) for most analyses, and there was concerning risk of bias in most studies. ConclusionsHigh risk of bias in many studies and substantial heterogeneity suggest that point estimates should be interpreted cautiously. Nonetheless, there was general consistency across analyses in that most symptom change estimates were close to zero and not statistically significant, and changes that were identified were of minimal to small magnitudes. There were, however, small negative changes for women or females in all domains. It is possible that gaps in data have not allowed identification of changes in some vulnerable groups. Continued updating is needed as evidence accrues. Funding: Canadian Institutes of Health Research (CMS-171703; MS1-173070; GA4-177758; WI2-179944); McGill Interdisciplinary Initiative in Infection and Immunity Emergency COVID-19 Research Fund (R2-42). Registration: PROSPERO (CRD42020179703); registered on April 17, 2020.

Research QuestionTo what extent do undisclosed financial conflicts of interest (COIs) exist among physician-authors in high-impact US-based psychiatry journals? Study DesignCross-sectional ObjectivesThe study aimed to assess the prevalence and magnitude of undisclosed financial COIs within high-impact US-based psychiatry journals. The primary research question was determining the extent and distribution of financial COIs among physician-authors in these journals. DesignThis investigation analyzed financial COIs by comparing self-reported disclosures to journal(s) with payments mandatorily reported in the Open Payments database. SettingThe study was conducted across two prominent US-based psychiatry journals: the American Journal of Psychiatry (AJP) and the Journal of the American Medical Association Psychiatry (JAMA-PSY), covering original research articles published from 1 January 2020 to 31 December 2022. Participants2,872 research publications published from 1 January 2020 to 31 December 2022 were examined in AJP (n = 1,368) and JAMA-PSY (n = 1,504). Seventy-four original research articles authored by 27 physician-authors (AJP n=15, JAMA-PSY n=12) met the eligibility criteria. InterventionsNo interventions were conducted in this observational study. Primary and Secondary Outcome MeasuresPrimary outcomes included total payments received by authors within the three years prior to publication and the proportion of undisclosed payments. Secondary outcomes assessed the payment types (research vs. general payments), demographic characteristics of authors, and study types associated with undisclosed COIs. ResultsUS$4.54 million was paid to authors in the two journals, of which US$645,135 (14.2%) were undisclosed. AJP authors received US$205,943 (7.5% of total payments) in undisclosed payments, while JAMA-PSY authors received US$439,192 (24.8%). Research payments constituted 82.3% of all undisclosed payments. Total undisclosed payments among the top 10 highest-earning authors accounted for 84.8% (AJP) and 99.6% (JAMA-PSY) of all undisclosed payments to journals. Nearly all undisclosed payments, 96.2%, were made to authors conducting randomized controlled trials (RCTs). ConclusionsSubstantial undisclosed financial COIs were identified among the top 10 earners in high-impact psychiatry journals. These findings highlight potential risks to research transparency and integrity. Further research is needed to evaluate the effectiveness of disclosure policies and develop mechanisms to mitigate COIs in psychiatric research. Strengths and LimitationsO_LIThis is the first systematic study of financial conflicts of interest of physician-authors publishing original research in two of the highest impact factor psychiatry journals, the American Journal of Psychiatry and JAMA Psychiatry, suggesting relevance to influential research and clinical practice. C_LIO_LIThe study employed data from OpenPaymentsData.cms.gov, an authoritative if incomplete source for study of financial conflicts of interest. C_LIO_LIThe necessary stringency of subject eligibility criteria that make this study meaningful winnowed the domain of analysis from nearly 3,000 publications to fewer than 30 authors. C_LI

BackgroundEarly intervention following mental health symptom onset has great potential in reducing long-term burden on individuals, families and friends, and society. The main focus in service development and research has been on early intervention in psychosis, but advances have also been made for other mental health difficulties such as eating disorders, anxiety and depression. We aimed to take stock of the available evidence regarding effectiveness, implementation, and experiences of care for early intervention approaches through a systematic umbrella review. MethodsWe included systematic reviews of complex early intervention strategies including more than one component, for mental health conditions with typical onset in young people under 25. We searched 4 databases (January 2019-April 2024) and synthesised results from eligible reviews using a narrative approach. Quality was assessed using AMSTAR 2. We excluded reviews on At Risk Mental States for psychosis as this is an extensive literature that has been the sole focus of umbrella reviews. ResultsSixteen reviews were included, with ten covering early intervention for psychosis, three for eating disorders, one for bipolar disorder and two for transdiagnostic early intervention approaches. Reviews of early intervention for psychosis suggest that intensive approaches can improve recovery rates following first presentation to services, although the success of initiatives aimed at reducing duration of untreated symptoms is less consistent. We found little systematically synthesised evidence of good quality regarding other diagnoses, although some early indications of success with eating disorders were described. Stigma and lack of knowledge or support act as barriers to rapid access, while insufficient service resources and staffing were barriers to effective intervention delivery. ConclusionsDespite its high importance in reducing the global burden of mental ill-health, evidence on how to intervene early following symptom onset remains limited (as assessed via systematic reviews), especially for conditions other than psychosis. For psychosis, some approaches now warrant attention to widespread implementation. Innovative approaches for eating disorders have been developed, but there is still a pressing need for treatments supported by substantial and robust trials. Further systematic reviews would be desirable for conditions including depression and anxiety, bipolar disorder, and "personality disorder".

BackgroundDepression and anxiety are common mental health conditions in the UK. NHS Talking Therapies offers evidence-based therapies and is the largest provider of treatment, yet, only 50% of patients recover. Accurate outcome prediction could identify those at risk of poor outcomes and support more personalised care. This study aimed to develop and internally validate multivariable prediction models using routinely collected data from a large, ethnically diverse sample to enable fair, data-driven treatment decisions. MethodsData included 30,999 adults who completed high-intensity therapy at a single NHS trust between 2018 and mid-2024. Seven NHS post-treatment outcomes were modelled: reliable improvement, recovery, and reliable recovery for both depression and anxiety, and also functional impairment at the end of treatment. Predictors measured at baseline included sociodemographic and clinical characteristics. Models were developed using elastic net logistic regression and internally validated using bootstrap resampling. ResultsThe sample was predominantly female (73%) with a median age of 34; 57% identified as White and 22% as Black. Models showed moderate to good discrimination (AUC 0.63-0.77) and strong calibration. Key predictors aligned with clinical expectations, including baseline symptom severity, unemployment, benefit receipt, reporting a disability or long-term condition, psychotropic medication use among other sociodemographic factors. ConclusionsThis study highlights the potential of data-driven tools to inform clinical decisions and treatment stratification in NHS Talking Therapies. Early identification of patients less likely to benefit from standard care could support timely review, monitoring, or tailored interventions. External validation and implementation research are needed to ensure generalisability and equity in care.

ObjectivesA single diagnostic code could be used to perform surveillance for opioid-associated amnestic syndrome (OAS) in healthcare datasets on a national scale. MethodsA request was submitted to search the Discharge Abstract Database (DAD) and the National Ambulatory Care Reporting System (NACRS) in Canada for the ICD-10-CA code, F11.6 (mental and behavioural disorders due to use of opioids, amnesic syndrome) during fiscal years (FY) 2010-2011 through 2022-2023. The annual total of encounters using this code was determined and crude rates per million were calculated for the Canadian population represented. ResultsNational counts from DAD and NACRS combined ranged from <5 to 14 annually. Rates per million for available years fell between 0.17 and 0.48. For available data through FY 2015-2016, the mean number of annual combined encounters nationally was 6.3; for those years after, the mean was 10. The mean rate per million was 0.23 and 0.35 for these two periods, respectively. DiscussionThis study represents the first effort to conduct surveillance for OAS on a national scale and suggests that the condition is relatively rare. Future efforts to validate the coded diagnosis of OAS with confirmed cases will help determine its value as a surveillance tool.

BACKGROUNDDepression is a disabling disorder with variable outcomes. In severe cases treatment is provided by specialist mental health care services, yet there is a lack of real-world evidence demonstrating how depression is managed within these settings, and consequently, a limited understanding of how to improve care for this population. AIMSWe examine the characteristics of patients receiving secondary mental healthcare for depressive disorders within a UK National Health Service (NHS) provider, and the treatments they receive. We investigate when patients receive treatments, and what predicts the use of specific treatments, improvement, and duration with services, with the aim of comparing real-world care to that advised by national guidelines. METHODSA retrospective cohort study was conducted using de-identified electronic patient records of patients with depression referred to Cambridgeshire and Peterborough NHS Foundation Trust (serving a population [~]0{middle dot}86 million), between January 2013 and June 2021. ANOVA models examined predictor variables of improvement and duration of care, while survival analyses explored treatment initiation rates and predictors of which treatments were used. RESULTS9,083 patients met the studys inclusion criteria. Almost half of those with depression had additional psychiatric diagnoses, reflecting the complexity of cases in secondary care. Treatment within secondary care was associated with improvements in both depressive and overall symptoms. Patients with a greater degree of psychiatric co-morbidity and those with lower socio-economic status indicators presented with greater overall illness severity at baseline, were more likely to be admitted into hospital, spent longer with services, and improved less than the average. Treatment patterns differed across age groups, sex/gender, socio-economic status, and psychiatric comorbidities. Some nationally recommended further-line treatments appeared to be under-used. CONCLUSIONSTreatment gaps in further-line treatments for depression exist, highlighting key areas for service improvement. Future work should target patients with complex needs and those who are socio-economically deprived.

BackgroundProlonged waiting times for Child and Adolescent Mental Health Services (CAMHS) leave many young people without structured support while awaiting specialist treatment. Social prescribing has been proposed as a community-based adjunct within CAMHS pathways; however, evidence regarding its safety and clinical impact remains limited. MethodsWellbeing While Waiting was a multi-site non-randomised controlled trial embedded within a hybrid type II implementation-effectiveness evaluation conducted across 11 CAMHS in England. The protocol was prospectively published prior to recruitment (BMC Psychiatry; 10.1186/s12888-023-04758-0). Between May 2023 and March 2025, 558 young people aged 11-18 years referred to CAMHS were enrolled (225 usual care; 333 social prescribing). Primary outcomes were anxiety and depression symptoms, total emotional and behavioural difficulties, and perceived stress. Secondary outcomes included resilience and wellbeing. ResultsNo intervention-related adverse events were observed. On average, participants had 5 sessions with a Link Worker. Compared with usual care, no significant differences were observed in anxiety or depression symptoms. However, participants receiving social prescribing demonstrated significant improvements in total emotional and behavioural difficulties over six months, driven by reductions in conduct difficulties, hyperactivity and peer problems. Significant improvements for those receiving social prescribing were also found for prosocial behaviour and resilience. ConclusionsWithin routine CAMHS pathways, no intervention-related adverse events were observed for social prescribing, and social prescribing was associated with improvements in behavioural and resilience-related outcomes, although not in anxiety or depressive symptoms. Findings suggest social prescribing may offer a valuable adjunct during delayed access to specialist treatment, with effects distinct from symptom-focused clinical therapies.

BackgroundCognitive behavioral therapy for insomnia (CBT-I), pharmacotherapy and their combination are effective for insomnia. However, it remains unclear which treatment is more likely to lead to favorable long-term outcomes when used as the initial treatment. We aimed to evaluate the comparative efficacy and acceptability of CBT-I, pharmacotherapy, and their combination in the long- and short-terms among adults with insomnia disorder. MethodsWe searched PubMed, CENTRAL, PsycINFO and WHO ICTRP from database inception to Dec 27, 2023, to identify published and unpublished randomized controlled trials. We included trials in hypnotic-free adults with insomnia disorder comparing at least two of the following: CBT-I with at least one effective component (sleep restriction, stimulus control, cognitive restructuring, and third wave components), pharmacotherapy, or their combination. We assessed the confidence in evidence using CINeMA. The primary outcome was long-term remission (longest follow-up between 3 to 12 months). Secondary outcomes included all-cause dropout and self-reported sleep continuity measures at long-term follow-up, and the same outcomes at the end of the acute treatment phase. We performed frequentist random-effects network meta-analyses. We used odds ratio (OR) for dichotomous outcomes and mean difference for continuous outcomes, expressed in minutes and percent. This study is registered in PROSPERO (CRD42024505519). FindingsWe identified 13 trials, including 823 randomized participants (mean age, 47.8 years, 60% women). Results suggested that CBT-I was more beneficial than pharmacotherapy in the long-term (remission OR 1.82 [95% Confidence Interval (CI), 1.15 to 2.87; certainty of evidence: high]), while there was weaker evidence of benefit of combination against pharmacotherapy (OR 1.71 [95%CI, 0.88 to 3.30: moderate]) and no clear evidence of difference of CBT-I against combination (OR 1.07 [95%CI, 0.63 to 1.80: moderate]). CBT-I was associated with less dropouts than pharmacotherapy in the long-term. Short-term outcomes also favored CBT-I over pharmacotherapy except total sleep time. Given the average long-term remission rate in the pharmacotherapy-initiating arms of 28%, CBT-I resulted in a long-term remission rate of 41% (95% CI: 31% to 53%) and combination 40% (95% CI: 25% to 56%). InterpretationThis study found that starting with CBT-I for the treatment of adults with chronic insomnia leads to better outcomes than starting with pharmacotherapy. Combination therapy may be better than pharmacotherapy alone, but unlikely to be worth the additional burden over CBT-I alone. FundingNone.

Effective early support for children and young people is a high priority. Early intervention approaches for young people with psychosis or eating disorders have substantial supporting evidence, but well-established approaches to delivering a prompt, effective response to young people presenting with early symptoms of anxiety and depression are lacking. We conducted a systematic review of outcomes of early interventions or approaches for young people (between 11 and 25 years) with initial symptoms of depression, anxiety and other common mental health difficulties. Five bibliographic and two grey literature databases were searched for papers relating to youth, early intervention and common mental health problems. We conducted a narrative synthesis of models and assessed quality using CASP checklists. We included 38 studies (43 publications): of these, randomised controlled trials were high quality but other studies tended to lack control groups and be of lower quality. Approaches broadly aimed provide a more comprehensive and effective early response to symptom onset, with primary goals falling into one of: 1) Making care more comprehensive and joined up, 2) Increasing speed or ease of access to support, or 3) Providing targeted support for specific needs in addition to anxiety and depression. Some evidence indicates that these approaches may facilitate access and reduce waiting times in the short-term, whilst decreasing burden on other mental health or emergency services. Significant improvements in mental health and wellbeing compared to controls were also reported across most studies with comparator groups, alongside high acceptability. Overall, models of early intervention for depression and anxiety show promise in improving access, experience and outcomes of care for young people. However, high heterogeneity of interventions and outcomes measured limits certainty. More robust controlled studies are needed, alongside comprehensive details of support received by young people through the intervention, and evidence of what works for whom in which settings.

KEY POINTSO_ST_ABSQuestionC_ST_ABSDid changes in mental health symptoms from pre-COVID-19 to during the pandemic differ by sex or gender? FindingsIn this systematic review and meta-analysis study of findings from 27 unique cohorts, changes from before to during the COVID-19 pandemic in mental health symptoms, including general mental health, anxiety, depression, and stress, were not statistically significantly different by sex or gender. MeaningThere were not likely substantial sex and gender differences in mental health symptom changes during the COVID-19 pandemic. ImportanceConcerns remain about whether COVID-19 affected mental health differently across sex or gender groups. We previously reported that changes in general mental health and anxiety symptoms, but not depression or stress, worsened more for females or women than males or men, but that was based on 12 studies published up to August 2021. ObjectiveTo investigate the sex or gender differences in mental health symptoms before and during the COVID-19 pandemic with updated evidence. Data SourcesMEDLINE, PsycINFO, CINAHL, EMBASE, Web of Science, China National Knowledge Infrastructure, Wanfang, medRxiv, Open Science Framework Preprints searched to August 31, 2023. Study SelectionEligible studies included change data for general mental health, anxiety symptoms, depression symptoms, or stress from pre-to during COVID-19 by sex or gender. Two independent reviewers reviewed citations for eligibility. Data Extraction and SynthesisStandardized mean differences (SMDs) were extracted for changes of continuous outcomes and proportions for dichotomous outcomes. Two independent reviewers completed data extraction and risk of bias assessment with an adapted Joanna Briggs Institute Checklist for Prevalence Studies. Data were pooled by random-effects models. Main Outcomes and MeasuresDifference in change of SMDs and proportions between sex or gender groups pre-COVID-19 to COVID-19. ResultsWe included data from 27 unique cohorts (N = 102 to 18,127). Change differences by sex or gender were minimal and not statistically significant: general mental health (SMD changewomen-men = 0.01, 95% confidence interval [CI]:-0.07 to 0.10; proportion changewomen-men = -0.03, 95% CI: -0.08 to 0.03), anxiety (SMD changewomen-men = 0.09, 95% CI -0.04 to 0.22; proportion changewomen-men = -0.05, 95% CI: -0.20 to 0.11), depression (SMD changewomen-men = 0.10, 95% CI: -0.00 to 0.20; proportion changewomen-men = -0.13, 95% CI: -0.81 to 0.55), and stress (SMD changewomen-men = -0.08, 95% CI -0.16 to 0.01, proportion changewomen-men = 0.04, 95% CI -0.10 to 0.17). No studies reported eligible mental health outcomes for gender minorities. Conclusion and RelevanceWe found no significant sex or gender differences in mental health changes. Future research should report outcomes for gender minority groups, even if small numbers, to support evidence synthesis. RegistrationPROSPERO (CRD42020179703)

Background: The NHS Improving Access to Psychological Therapies (IAPT) programme, now rebranded as NHS Talking Therapies, faces persistent capacity constraints with average wait times exceeding 90 days for cognitive behavioral therapy (CBT) in many Clinical Commissioning Group areas. AI-powered CBT platforms have been introduced as a digital adjunct within stepped care, yet longitudinal evidence on anxiety symptom trajectories and their predictors in routine NHS settings remains limited. Objective: To model individual anxiety symptom trajectories among patients referred to an AI-powered CBT platform within NHS primary care, identify distinct trajectory classes, and examine patient-level and practice-level predictors of differential treatment response using multilevel growth curve modeling. Methods: A prospective cohort study was conducted using linked clinical and administrative data from 6,284 patients (aged 18-65) referred to the CalmLogic AI-CBT platform across 187 general practices in four NHS England Integrated Care Systems (ICSs) between April 2023 and September 2025. Patients completed GAD-7 assessments at baseline, 4 weeks, 8 weeks, 12 weeks, and 24 weeks. Three-level growth curve models (assessments nested within patients nested within practices) with random intercepts and random slopes were fitted. Growth mixture modeling (GMM) was subsequently applied to identify latent trajectory classes. Predictors were examined at Level 2 (patient demographics, baseline severity, comorbidities, digital literacy, engagement intensity) and Level 3 (practice deprivation index, list size, urban/rural classification, and IAPT wait time). Results: The unconditional growth model revealed a significant average linear decline in GAD-7 scores of -0.94 points per month (p < .001), with substantial between-patient variation in both intercepts (variance = 14.82, p < .001) and slopes (variance = 0.38, p < .001). Significant between-practice variation accounted for 8.7% of intercept variance (ICC = 0.087). Growth mixture modeling identified four distinct trajectory classes: Rapid Responders (28.4%, steep early decline stabilising by week 8); Gradual Improvers (34.1%, steady linear decline through 24 weeks); Partial Responders (22.8%, modest early improvement followed by a plateau at clinically significant levels); and Non-Responders (14.7%, minimal change or slight deterioration). Higher baseline severity, female gender, and greater module completion predicted membership in the Rapid Responder class. Practice-level IAPT wait times exceeding 90 days independently predicted faster improvement trajectories (coefficient = -0.31, p = .003), suggesting that AI-CBT has its greatest incremental value in capacity-constrained areas. Patients in the most deprived quintile showed slower trajectories (coefficient = 0.22, p = .011) despite equivalent engagement levels, indicating a deprivation-related treatment response gap. Conclusions: AI-powered CBT platforms integrated within NHS primary care produce significant anxiety symptom reduction on average, but treatment response is heterogeneous, with four distinct trajectory classes identified. The finding that longer IAPT wait times predict better AI-CBT outcomes supports the platform's positioning as a scalable bridge intervention for capacity-constrained services. The deprivation-related response gap warrants targeted support strategies for patients in the most disadvantaged communities.

ObjectiveTo explain discrepant findings for fluoxetines efficacy in three influential network meta-analyses (NMAs) of treatments for pediatric depression, which led to conflicting clinical recommendations. DesignCritical appraisal and re-analysis of three published NMAs. Data sourcesNMAs published in two Lancet journals and in Cochrane, together with the trial datasets reported therein. Data synthesisWe compared efficacy estimates for fluoxetine versus placebo across NMAs. We identified and assessed an outlying trial included only in the Lancet NMAs using the INSPECT-SR instrument, and re-analysed the NMAs with and without this trial. ResultsThe larger effects reported in the Lancet NMAs (SMD -0.51, 95% CrI -0.99 to -0.03; and -0.51, -0.84 to -0.18) were driven by an inconsistent fluoxetine-placebo-nortriptyline loop, which the original NMA authors could not explain. We identified the cause of the inconsistency as a small outlier trial of fluoxetine versus nortriptyline that reported an implausibly large effect size (SMD > 4) favouring fluoxetine, and which was not included in the Cochrane NMA. Excluding this trial from the Lancet NMA datasets resolved the inconsistency and yielded efficacy estimates for fluoxetine that closely matched the Cochrane NMA (SMD -0.20, 95%CI -0.28 to -0.11). The outlier trial also showed multiple methodological concerns suggesting low trustworthiness. ConclusionDiscrepancies between the three NMAs were explained by the indirect influence of a single small trial with extreme and unreliable results. Removing this trial reconciled the Lancet NMAs with the Cochrane NMA, yielding a more reliable estimate of fluoxetine efficacy versus placebo. It also resolved the inconsistency. This case illustrates how inclusion of a single small problematic trial can substantially distort the clinically important results of NMAs. Our findings may alter the clinical risk/benefit assessment of fluoxetine for this indication. Other: No specific funding was involved in the study. KEY MESSAGES What is already known on this topic[bullet] Three network meta-analyses frequently inform clinical guideline recommendations for the use of fluoxetine to treat depression in children and adolescents. [bullet]However, these studies have discrepant findings for fluoxetine versus placebo, with the two earlier NMAs reporting an SMD approximately -0.5, and the other reporting a mean difference equivalent to an SMD of approximately -0.2. [bullet]Such discrepancies require investigation because network meta-analyses should be reproducible syntheses of the available evidence and different results may have different clinical implications. [bullet]Outlying or problematic trials in meta-analyses can distort results. What this study adds[bullet] We identified that the cause of the discrepant findings was the indirect influence of a single small study of fluoxetine versus nortriptyline that reported an unusually large effect size favouring fluoxetine. This study was not included in the more recent NMA, which excluded studies of tricyclic antidepressants. In addition to the extreme effect size, this study has other concerning features that call into question its credibility. [bullet]Our findings demonstrate how significantly a single small study with outlying results can impact the clinically important findings of NMAs. While it is known that meta-analyses can be affected by the inclusion of retracted studies, less is known about the impact of single unretracted studies with extreme findings and other concerning features. [bullet]Our experience demonstrates that researchers seeking to critically appraise studies with concerning features, and the evidence syntheses that include them, may face barriers when raising their concerns with study authors and journal editors. How this study might affect research, practice, or policy[bullet] Our findings may alter the clinical risk/benefit assessment of fluoxetine for this indication. [bullet]Our findings show how evidence from small studies with outlying results can influence the most clinically important findings of NMAs, and highlight the need for NMA methodology to include assessment for outliers and for the credibility of individual trial results.

BackgroundHealthcare workers experience disproportionately high rates of depression, anxiety, and post-traumatic stress compared with the general population. Within the NHS, work-related stress and mental health-related sickness absence has increased over the past decade, a trend intensified by COVID-19. Mental health support offers are patchy across the UK, and the evidence base around interventions is scarce. The Staff Mental Health Service (SMHS) provides rapid, confidential support for NHS staff across Cambridgeshire and Peterborough. In this study, we report an economic evaluation of this dedicated service. AimsTo assess costs and patient outcomes associated with SMHS treatment, compared with local NHS Talking Therapies (TT) support. MethodA model-based cost-consequence analysis comparing two treatment pathways: SMHS or TT, versus TT only. Routinely collected service data and survey responses informed a decision-tree model estimating costs (2022/23 {pound}GBP), clinical outcomes (PHQ-9 and GAD-7 scores), and quality-adjusted life years (QALYs). Additional analyses examined service waiting times and productivity losses. ResultsCosts per patient were slightly higher for SMHS or TT ({pound}614 versus {pound}553), resulting in an incremental cost-effectiveness ratio of {pound}7,126/QALY. Treatment at either SMHS or TT yielded greater improvements in mental health outcomes than TT alone, with mean score reductions of 4.2 versus 2.8 (PHQ-9), and 4.6 versus 2.7 (GAD-7). Median waiting times were substantially shorter at SMHS versus TT from referral to assessment (14 versus 17 days), referral to treatment (22 versus 51 days), and assessment to first treatment (7 versus 30 days; all p<0.001). Productivity losses during waiting periods were lower for SMHS, with an estimated value of {pound}2,018 per patient. ConclusionsThe SMHS offers a clinically effective and cost-effective model of support for NHS staff, delivering greater improvements in mental health symptoms, substantially shorter waiting times, and reduced productivity losses at only modest additional cost compared with TT. These findings provide early evidence that specialist services for healthcare workers represent good value for money and support continued investment in specialist staff mental health provision within the NHS.

BackgroundPrevalence of Treatment-Resistant Depression (TRD) varied widely across studies due to heterogeneous definitions. Several treatment strategies exist to manage patients with TRD but evidence from real-world data is scarce. Investigating their use in real-life settings is important to understand national prescribing practices and to refine prevalence estimation. MethodAll adult patients ([&ge;] 18 years) with a TRD episode for the year 2019 were identified in a sample of four French regions accounting for 27% of national individuals. After exclusion of patients with psychotic or bipolar disorders, Parkinsons disease, and dementia, TRD was defined by i/ 3 successive sequences of different antidepressants (AD), or ii/ the dispensing of several different AD together, or iii/ an AD with a potentiator (lithium, antiepileptic drugs, or antipsychotic drugs) over the same treatment period. The prevalence rate was estimated for the year 2019 and treatment patterns were described by treatment class and molecule. ResultsFor the year 2019, 66,810 patients were identified with TRD, accounting for 23.9% of all patients treated for depression. The mean age was 56 years ({+/-}15.9) with 63.7% of women. Standardized prevalence of TRD was estimated at 35.1 per 10 000 patients, and 25.8 per 10,000 patients when excluding patients probably treated for another primary diagnosis than depression. Association of an AD with an antipsychotic was the most frequently used strategy, with SSRIs and second-generation antipsychotics being the most often prescribed. ConclusionThis study provides robust population-based estimates of the prevalence of TRD in the French population. Description of treatment patterns highlight the widespread use of second-generation antipsychotics as potentiator of antidepressants.

IMPORTANCEKetamine-Assisted Psychotherapy (KAP) is an emerging treatment option to alleviate treatment resistant affective disorders, but its long term effectiveness remains unclear. OBJECTIVETo examine the treatment effects of KAP on anxiety, depression, and post traumatic stress disorder (PTSD) at 1, 3, and 6 months post treatment. DESIGN, SETTING, AND PARTICIPANTSThis retrospective single-arm effectiveness trial included self-reported outcomes from 1806 adults with a history of depression, anxiety, or PTSD who had not responded to prior treatment interventions and received KAP administered across 11 Field Trip Health clinics in North America between March 13, 2020 and June 16, 2022. INTERVENTIONKAP consisting of 4-6 guided ketamine sessions (administered via intramuscular injection or sublingual lozenge) with psychotherapy-only visits after doses 1 and 2 and then after every 2 subsequent doses. Mean number of doses administered was 4, SD=3, and mean number of psychotherapy sessions was 3, SD=2. MAIN OUTCOMES AND MEASURESPrimary outcomes were changes in depression, anxiety, and PTSD at 3 months relative to baseline, assessed respectively using the 9-item Patient Health Questionnaire (PHQ-9), the 7-item Generalized Anxiety Disorder measure (GAD-7), and the 6-item PTSD Checklist (PCL-6). Secondary outcomes were changes at 1 and 6 months relative to baseline. RESULTSLarge treatment effects were detected at 3 months (ds=0.75-0.86) that were sustained at 6 months (ds=0.61-0.73). Case reductions (identified based on cut-off values) ranged from 39-41% at 3 months and 29-37% at 6 months. 50-75% reported a minimal clinically important difference at 3 months and 48-70% at 6 months. CONCLUSIONS AND RELEVANCEKAP produced sustained reductions in anxiety, depression, and PTSD, with symptom improvement lasting well beyond the duration of dosing sessions. These effects extended to as much as 5 months after the last KAP session. Given the growing mental health care crises and the need for effective therapies and models of care, especially for intractable psychiatric mood related disorders, these data would support the consideration of KAP as a viable alternative. Further prospective clinical research should be undertaken to provide further evidence on the safety and effectiveness of ketamine within a psychotherapeutic context. TRIAL REGISTRATIONClinicaltrials.gov Identifier NCT05604794 Key Points QuestionWhat are the lasting effects of Ketamine-Assisted Psychotherapy on psychological distress? FindingsIn this retrospective single-arm effectiveness trial that included 1806 adults, there were large effect sizes at 3 months on depression, anxiety, and post traumatic stress (ds=0.75-0.86) that were sustained at 6 months. MeaningThese findings suggest that Ketamine-Assisted Psychotherapy is an effective treatment option with substantial clinical benefits detected up to half a year.

BackgroundFollowing the COVID-19 pandemic, computer-based self-help platforms for eating disorders (EDs) became increasingly prevalent as a tool to effectively prevent and treat ED symptoms and related behaviours. This systematic review explored the clinical effectiveness of computer-based self-help platforms for EDs. MethodsFrom inception to the 31st of May 2024, a systematic search of Ovid MEDLINE, Embase, Global Health, and APA PsycInfo was conducted. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Outcome quality assessments were conducted according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE). Results14 RCTs, with a total of 4195 participants, were included. 4 studies explored the effectiveness as primary prevention, 7 as secondary prevention, and 3 as tertiary intervention. The gathered literature demonstrated computer-based self-help platforms as clinically effective in reducing ED core symptoms and related behaviours, with psychoeducation, cognitive behavioural, and dissonance-based approaches being the most prevalent approaches. ConclusionsComputer-based self-help platforms are effective in the short-term reduction of ED symptoms and associated behaviours and should be implemented in the early stages of a tiered healthcare system for ED treatments. Trial RegistrationProspero (CRD42024520866).

BackgroundThe effectiveness of Digital Cognitive Behavioural Therapy (dCBT) smartphone applications for reducing depressive symptoms in adolescents remain unclear. MethodsAn online three-arm, parallel-group randomised controlled trial evaluated the effectiveness of a CBT smartphone application (ClearlyMe(R)) for reducing depressive symptoms in adolescents with outcomes assessed at baseline, post intervention (primary endpoint: 6-weeks post baseline) and follow-up (secondary endpoint: 4-months post baseline). The University of New South Wales Human Research Ethics Committee provided ethical approval. Youth were eligible if they were aged 12 to 17 years, in Australia, had mild to moderate depressive symptoms as measured by the adolescent Patient Health Questionnaire-9 (PHQ-A), were not receiving treatment or experiencing recent or severe suicidality, had access to a smartphone, and parental consent. Participants were randomised to self-directed ClearlyMe(R), ClearlyMe(R) with SMS-guided support, or the attention-matched control. Participants were not directly informed of their allocation. The statistician was blinded for analysis. The primary outcome was PHQ-A change post intervention. Intention-to-treat analyses used mixed models for repeated measures. The trial was prospectively registered on the Australian New Zealand Clinical Trials Registry (ACTRN12622000131752). Outcomes569 adolescents (Mean age: 15.89, SD: 1.26, 74.2% female) were included in the analyses. The self-directed and guided conditions showed significantly greater reductions in depressive symptoms post intervention than the control (self-directed: Cohens d=0.35, mean differential decline 1.77; 95%CI: 0.56 - 2.98; P=.004; guided: d=0.33, mean differential decline: 1.31; 95%CI: 0.12 - 2.49; P=.030). The effects of self-directed and guided were comparable. Effects were also more robust and substantially larger post intervention among adolescents with probable MDD at baseline. Secondary outcomes showed similar patterns of change, although no differential effects for anxiety. There were no differences between the conditions at follow-up for any outcomes. Risk of adverse events was almost double in controls compared to self-directed (IRR: 1.73, 95%CI: 1.15 - 2.62, P=.009) and guided (IRR: 1.98 (95%CI: 1.27 - 3.08, P=.002). InterpretationClearlyMe(R), self-directed or with SMS-guided support, was effective for the short-term reduction of depressive symptoms in adolescents who have mild to moderate depression and are not receiving any other treatment. FundingThe Goodman Foundation and the Australian National Health and Medical Research Council Investigator Grants (MRF1197249, GNT2008839, GNT115614).

ImportanceAI-enabled features may improve the effectiveness of routine mental health care, yet large-scale real-world evidence remains limited. ObjectiveTo evaluate whether access to AI-enabled continuous care features embedded within routine psychotherapy delivery is associated with improved treatment engagement and clinical outcomes under real-world conditions. DesignPreregistered cluster-level, matched, quasi-experimental study using a real-world rollout of AI-enabled continuous care features compared with psychotherapy alone (intention-to-treat framework). SettingAn employer-sponsored behavioral health program providing outpatient psychotherapy for employees and dependents. ParticipantsAdults initiating a new episode of psychotherapy from 25 employers with access to continuous care features and 75 matched employers without access. Treatment engagement was assessed over 7 weeks (n=26,208), and clinical outcomes were evaluated for up to 180 days (n=5,518). ExposureEmployer-level access to AI-enabled continuous care features supporting engagement and continuity before and between psychotherapy sessions, compared with psychotherapy alone. Main OutcomesEarly treatment engagement (number of psychotherapy sessions attended and time to second session) and changes in depressive and anxiety symptom severity measured using the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7). ResultsCompared with matched controls receiving psychotherapy alone, the intervention group attended 5% more psychotherapy sessions during the first 7 weeks (rate ratio, 1.05 [1.01, 1.10]) and completed their second session sooner (mean difference, -0.62 days [-1.05, -0.18]). Both groups demonstrated substantial symptom improvement over time; however, access to continuous care features was associated with additional improvement in depressive symptoms (d=0.16) and anxiety symptoms (d=0.15) at the median duration of care (day 44). These effects translated into clinically meaningful differences in reliable improvement by the median duration of care (NNT=25 for both outcomes). Conclusions and RelevanceIn this real-world evaluation, access to AI-enabled continuous care features embedded within routine psychotherapy delivery was associated with greater early engagement and a higher likelihood of reliable symptom improvement beyond psychotherapy alone. These findings suggest that augmenting routine psychotherapy with AI-enabled continuous care can meaningfully shift recovery trajectories during a standard treatment episode, strengthening early treatment momentum and improving outcomes at scale. Key PointsO_ST_ABSQuestionC_ST_ABSIs access to AI-enabled continuous care features embedded within routine psychotherapy delivery associated with improved treatment engagement and clinical outcomes under real-world conditions? FindingsIn this cluster-level, matched, quasi-experimental study of adults receiving psychotherapy within an employer-sponsored behavioral health program, access to AI-enabled continuous care features was associated with significantly greater early treatment engagement and faster improvement in depressive and anxiety symptoms compared with psychotherapy alone. MeaningAI-enabled support features may incrementally enhance the delivery and effectiveness of established psychotherapies when implemented as complements to routine care at scale.

ObjectiveThe aim of this paper is to evaluate the effectiveness of enhanced cognitive behavioral therapy (CBT-E) adapted to be delivered via telehealth in a real-world, clinic treatment setting by a multi-disciplinary team for adults with an eating disorder. MethodA retrospective analysis of treatment outcomes was conducted on adult patients (18+) who received adapted CBT-E, a transdiagnostic treatment approach specifically modified for the treatment of eating disorders. Outcome included weight and eating disorder, depression, and anxiety symptoms. Survival analyses were used to assess length of stay, weight restoration and alleviation of eating disorder, depression, and anxiety symptoms; multilevel models assessed outcome trajectories over treatment time. ResultsThe patient sample (n = 1,718) was predominantly white (73%), cisgender women (86%), with a mean age of 30 (SD = 12). Diagnoses included anorexia nervosa (AN, 56%), binge-eating disorder (BED, 24%), bulimia nervosa (BN, 7%), and other specified feeding and eating disorder (OSFED, 11%). Approximately 51% of patients with weight restoration targets achieved weight restoration (95% of their target weight) by week 40 of treatment. By week 40 in treatment, 49% of patients reached subclinical levels on the EDE-Q, 58% on the PHQ-8, and 56% on the GAD-7. DiscussionAdapted CBT-E delivered via telehealth by a multi-disciplinary team is effective in improving transdiagnostic eating disorder symptoms, depression, and anxiety in an outpatient setting. Outcomes were consistent across diagnoses, demonstrating the feasibility and effectiveness of virtual CBT-E. However, variability in treatment length makes direct comparison with clinical trial end-of-treatment outcomes challenging. Public Health SignificanceThis study shows that virtually-delivered CBT-E effectively treats eating disorders by improving symptoms and accessibility to treatment. Expanding virtual treatment can significantly reduce barriers to care, reaching more individuals and lessening the public health impact of these disorders.