BJPsych Open

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.

Introduction: Blackpool, England's most deprived local authority, has the highest drug-related death rate in the country. People in police custody with problem substance use are a key Core20PLUS5 inclusion-health group, yet referral from the police into structured drug and alcohol treatment is fragmented and relies heavily on self-report. We evaluated the current police-to-treatment route in Blackpool and designed an evidence-informed unified pathway. Materials and Methods: A mixed-methods service evaluation and pathway-design project was conducted during a six-month General Practice / Public Health rotation. Routinely collected referral data from Horizon (the local specialist drug and alcohol service) covering the 47-month period from December 2019 to October 2023 were analysed. Findings were triangulated with national policy, the Project ADDER and Liaison and Diversion evaluations, and the international evidence on police-led pre-arrest diversion. Results: Of 5,900 total referrals into Horizon over 47 months, only 269 (4.56%) originated from the police. Police referrals accounted for fewer than 5% of monthly referrals in 30 of 47 months, for 5 to 9.9% in 16 months, and for >/= 10% in only one month (10.8%, December 2022). Blackpool recorded 76 drug-misuse deaths in 2019-21 (19.4 per 100,000, approximately four times the England rate). A six-step unified pathway is proposed: Initiate Referral (opt-out, from ADDER Police and Liaison and Diversion); Initial Assessment; Tailored Treatment Plan; Continuous Support; Collaboration and Monitoring; and Evaluation and Adjustment. Conclusions: Police contact is markedly under-used as a gateway to treatment despite Blackpool having the highest drug-related mortality in England. An opt-out, multi-agency pathway anchored in Core20PLUS5 has the potential to narrow the treatment gap, reduce re-offending, and address the structural health inequalities that drive premature mortality.

BackgroundThe etiology and nosological status of seasonal affective disorder (SAD) as a specifier of depressive episodes versus a transdiagnostic disorder are the subject of debate. In this study, we investigated the underlying etiology of SAD and dimensional seasonality by examining their association with latitude and genetic risk for a range of traits, and investigated gene-environment interactions. MethodsThis study included 12,460 adults aged 18-90 with a history of depression from the Australian Genetics of Depression Study. Regression models included predictors for latitude (distance from equator) and polygenic scores for eight traits; major depressive disorder, bipolar disorder, anxiety disorders, chronotype, sleep duration, body mass index, vitamin D levels, and educational attainment. Outcomes were SAD status and general seasonality score. ResultsSAD was positively associated with latitude (OR[95%CI] = 1.05[1.03-1.06], padjusted<0.001), and there was nominal evidence of additive and multiplicative interactions between chronotype genetic risk and latitude (OR = 0.99[0.99-0.99], padjusted=0.381; OR=0.98[0.97-0.99], padjusted=0.489). General seasonality score was associated with latitude (IRR=1.01[1.01-1.01], padjusted 0.001) and genetic risk for major depressive disorder (IRR =1.02[1.01-1.03], padjusted<0.001), bipolar disorder (IRR=1.02[1.01-1.03], padjusted=0.001), anxiety disorders (IRR=1.03[1.01-1.04], padjusted<0.001), vitamin D levels (OR=0.89[0.80-0.95], padjusted=0.048), and educational attainment (IRR=0.97[0.96-0.99], padjusted<0.001). ConclusionsThese findings enhance understanding of SAD etiology, highlighting contributions of psychiatric genetic risk and geographic measures on seasonal behavior, and support examining seasonality as a continuous dimension.

Abstract Background: Mental health services are shifting towards person-centred care based on collaboration and shared decision making. Yet evidence indicates that these approaches may not be consistently embedded in the assessment and management of risk or safety. Methods: We conducted a cross-sectional online survey to examine perceived barriers and enablers to shared decision-making in risk assessment and management with people living with severe mental illness. Questionnaire development and data analysis were guided by the Theoretical Domains Framework, a psychological framework used to identify and understand factors influencing behaviour change. Items were rated on a 5 point Likert scale. In total, 243 service users and mental health professionals completed the survey. Results: Most service users reported that risk or safety had been discussed with them, but only half felt involved in the risk assessment or management process. Two thirds reported not receiving a copy of their risk assessment or management plan. Service users strongly agreed that communication with professionals about risk and safety requires improvement, and that risk is a difficult and emotive topic to discuss. Professionals reported high motivation to involve service users but identified time constraints and service user related factors as key barriers. Principal component analysis identified four components: (1) motivation; (2) social influences and memory/decision making; (3) beliefs about consequences; and (4) team, environment and training factors. More experienced professionals reported fewer negative beliefs about consequences, such as concerns about causing distress or disengagement. Conclusion: Findings highlight the need for clearer communication, organisational support and targeted training to enhance shared decision-making in risk assessment and management practices.

Background Little is known about the provision of diagnoses to young people with mental health disorders. We investigated diagnosis provision by NHS mental health services, focusing on 17-year-olds in South London between 2009-2024, and compared with estimated disorder prevalence. Methods To examine diagnosis provision in the population, we extracted diagnosis data from records of the NHS mental healthcare provider serving South London, using the Maudsley Biomedical Research Centre Clinical Record Interactive Search application; we then compared these data with the corresponding population size, obtained from the Office for National Statistics. To assess diagnosis provision in those with mental health disorders, we compared diagnosis data with the number of young people estimated to have met criteria for a disorder, derived from epidemiological interview data collected in the Environmental Risk (E-Risk) Longitudinal Twin Study and weighted according to characteristics of 17-year-old South Londoners. To assess diagnosis provision in those with mental health disorders within health services, we compared diagnosis data with the number estimated to have met criteria for a disorder and used any health service for their mental health, again derived from weighted E-Risk Study data. Findings Of 17-year-olds from South London in 2009-2024, 4.0% (n=8,958/223,404) had a diagnosis in mental health records during the previous year. This diagnosis provision covered <1 in 16 of those estimated to have had a mental health disorder, and <1 in 4 of those estimated to have also used health services. Diagnosis provision was lower in girls than boys and in young people with Black/Asian/Mixed/Other ethnicity than those with White ethnicity, in those estimated to have had a mental health disorder and used health services. Interpretation These findings demonstrate gaps and biases in mental health diagnosis provision for young people, including within health services, and reveal the imperative need to strengthen young people's mental healthcare.

BackgroundMajor depression affects at least 10% of adults, yet evidence-based treatments have modest clinical effectiveness and acceptability. In recent years, outdoor swimming has grown increasingly popular and emerging quantitative and qualitative evidence suggests potential as an intervention for depression, however, there is yet to be a full-scale randomised controlled trial (RCT). This is a protocol to assess the safety and test the clinical- and cost-effectiveness of an 8-session outdoor swimming course (in addition to usual care) on depression symptom severity in adults experiencing major depression, in comparison to usual care alone. MethodsThis study is a pragmatic, parallel group, superiority RCT with 1:1 allocation comparing the outdoor swimming intervention (in addition to treatment as usual) with treatment as usual, aiming to recruit 480 adult participants meeting diagnostic criteria for major depression. Recruitment will take place across 21 sites with blind post treatment and follow up assessments. The primary outcome is depression symptom severity at T1 post-intervention, 12 weeks post-randomisation (the primary end point) using the Patient Health Questionnaire 9 (PHQ-9). Secondary clinical outcomes are anxiety (Generalised Anxiety Disorder 7 at T1 and T2 [38 weeks post-randomisation] and PHQ-9 at T2), mindfulness is measured as a potential mechanism at all timepoints (Five Facet Mindfulness Questionnaire 15). Health economic measures at all time points are: EQ-5D-5L, Recovering Quality of Life (ReQoL), Client Service Receipt Inventory and the Productivity Cost Questionnaire. A qualitative study will examine the experience of participants during and after the swim course. DiscussionIf the 8-session outdoor swim course is safe, clinically- and cost-effective, findings will support national implementation, offering an evidence-based intervention to those affected by depression, while potentially reducing healthcare costs. Furthermore, this may pave the way for other outdoor activities to support people with poor mental health to be developed and evaluated as interventions. Trial registrationControlled trial registration number is ISRCTN registration number 24759023. Registered on 21 February 2024 (https://www.isrctn.com/ISRCTN24759023). Administrative informationNote: Numbers enclosed in braces within this protocol correspond to SPIRIT checklist item numbers. The sequence of items has been adjusted to group related content together. (https://www.consort-spirit.org/). O_TBL View this table: org.highwire.dtl.DTLVardef@7f6ff8org.highwire.dtl.DTLVardef@900309org.highwire.dtl.DTLVardef@b75bc0org.highwire.dtl.DTLVardef@1e8d410org.highwire.dtl.DTLVardef@ba71ac_HPS_FORMAT_FIGEXP M_TBL C_TBL Plain Language Summary BackgroundDepression is very common,with at least 1 in 10 people having an episode of depression during their lifetime. Many people believe that outdoor swimming can improve depression. There is some research that suggests outdoor swimming is helpful for depression, but we do not yet have enough evidence to be sure. OUTSIDE 2 is a large research study that aims to find out whether outdoor swimming can help people with depression. AimThe aim of this study is to find out if taking part in an 8-session outdoor swimming course, along with usual care, is safe, helps improve depression, and is good value for money. We will compare people who do the swimming course (alongside their usual care) with people who only receive their usual care. In our study we will also talk to participants about their experiences. We want to understand how the outdoor swimming course affects their depression, and how the activity itself might help them feel better. Describe your research plan, includingPeople who are interested in taking part in the study can visit our website (outside2.co.uk) to read more information and sign up. Once someone agrees to join, they will be randomly placed into one of two groups available at their location to keep the study fair. One group will take part in eight one-hour outdoor swimming sessions in a small group. They will continue with their usual care for depression, which may include talking therapies, antidepressant medication, or community activities. The other group will continue with usual care only during the study. After the study ends, they will be offered the same outdoor swimming course, so no one misses out. The swimming sessions will be led by experienced swimming coaches who will help participants build confidence in the water and learn important water safety skills. During the study, all participants will complete questionnaires about their symptoms of depression, overall mental health, and use of health services. They will do these before they are put in a group, right after the swimming course or usual care period and six months later. Participants in the swimming group will also be asked to keep a diary about their experiences during the course. Researchers may visit some sessions to ask participants about how they are finding the swimming and how it affects their mood. Swim coaches will record attendance at each session and describe what activities were included. This helps the research team understand exactly what took place during each class. Knowledge mobilisationWe want to make sure that the information we learn from this study reaches many different people, not just scientists. To do this, we will share our findings in several ways. We will create a Podcast mini-series, an animated video as well as research papers. Using these different methods helps us share our findings with many groups, including adults in the community, mental health professionals, people working in the swimming industry, scientists, and policymakers. By sharing the results in several ways, more people can understand if and how outdoor swimming might support recovery from depression and mental health more broadly, and it increases the chance that the study will make a real difference, whatever it finds.

BackgroundAI-powered cognitive behavioural therapy (AI-CBT) tools hold significant promise for addressing the global mental health treatment gap, yet sustained user engagement remains critically low. While patient attitudes and experiential factors have been qualitatively documented, the psychological mechanisms through which AI literacy translates into long-term engagement remain poorly understood. Existing systematic evidence highlights trust, perceived therapeutic alliance, and stigma as salient themes, but no large-scale quantitative study has modelled these as a mediated pathway. ObjectiveThis study aimed to (1) examine whether trust in AI systems and perceived therapeutic alliance mediate the relationship between AI literacy and sustained AI-CBT engagement, and (2) determine whether mental health stigma moderates these mediated pathways. MethodsA cross-sectional national online survey was conducted in the United Kingdom (N = 1,247). Eligible adults (18+) with a history of anxiety or depression who had used an AI-CBT tool in the preceding 12 months were recruited via stratified random sampling. Structural equation modelling (SEM) with moderated mediation was conducted in R (lavaan 0.6-17). Moderated mediation was evaluated using the PROCESS macro framework adapted for SEM, with 5,000 bootstrap replications for bias-corrected confidence intervals. Model fit was assessed using CFI, TLI, RMSEA, and SRMR indices. ResultsThe final SEM demonstrated excellent fit (CFI = 0.967, TLI = 0.959, RMSEA = 0.043 [90% CI: 0.036-0.051], SRMR = 0.052). AI literacy exerted a significant indirect effect on sustained engagement through trust in AI ({beta} = 0.213, SE = 0.031, p < .001) and perceived therapeutic alliance ({beta} = 0.187, SE = 0.028, p < .001). Mental health stigma significantly moderated the trust[-&gt;]engagement pathway ({Delta}R2 = 0.042, p = .003), with the indirect effect being stronger among individuals with lower stigma scores. The total indirect effect accounted for 58.4% of the total effect of AI literacy on engagement. ConclusionsAI literacy promotes sustained AI-CBT engagement primarily through its effects on trust and perceived therapeutic alliance, pathways that are attenuated by mental health stigma. These findings underscore the need for stigma-reduction interventions and AI literacy programmes as implementation strategies. Findings have direct implications for the design and deployment of AI-CBT tools across UK NHS digital mental health services.

ObjectiveTo charactertise emergency department (ED) use among young people with bipolar disorder (BD) and compare patterns to those observed in anxiety, depressive, and psychotic disorders. Design, setting and participantsData linkage study using administrative ED presentation records (January 2020 to October 2020) and a transdiagnostic youth mental health cohort of 2243 individuals aged 12-30 years in New South Wales, Australia. Main outcome measuresED presentation patterns (any presentation, frequency, and rates) and reasons for presentation (mental health-related and non-mental health-related). ResultsOf the 354 young people with BD, 309 (87.3%) presented to an ED at least once. ED presentation rates were higher for BD than for anxiety (incidence rate ratio [IRR]=1.82, p<.001) and depressive disorders (IRR=1.32, p<.001), but similar to psychotic disorders (IRR=0.91, p=.379). Differences were primarily driven by mental health-related presentations. Recurrent mental health presentations were associated with illness progression (clinical stage and functional impairment) rather than diagnosis. However, the likelihood of mental health-related presentations remained higher in BD compared with anxiety and depressive disorders after adjustment. ConclusionsYoung people with BD have high rates of ED use, comparable to those with psychotic disorders. Although mental health-related presentations are more common in BD than in anxiety and depressive disorders, recurrence is largely explained by markers of illness progression. These findings highlight the need for community-based services that provide continuous and coordinated care for young people with complex mental health needs.

BackgroundEarly Intervention for Psychosis Services (EIPS) enhance outcomes for individuals experiencing their first episode of psychosis (FEP). However, in low-resource settings, there is limited knowledge about i) the pathways patients take to access EIPS, ii) the proportion and factors associated with acceptance of referral to EIPS, and iii) if different pathways to EIPS services affect clinical outcomes. Ugandas first EIPS, the Specialised Treatment Early in Psychosis Service at Makerere University Hospital (STEP_MaKH), presents a unique opportunity to explore these important questions. AimsWe aimed to examine the pathways to EIPS, the factors associated with referral to specialised psychosis care and the impact of initial treatment-seeking behaviour on long-term symptom remission and quality of life. MethodsWe conducted a multiple-method study. Pathways to care were assessed retrospectively using the WHO Encounter Form among adults with FEP eligible for referral to STEP_MaKH. Among those who completed referral and enrolled in STEP_MaKH. Symptom severity and quality of life were followed prospectively for 12 months. Modified Poisson regression identified predictors of referral completion. Kaplan-Meier methods and Cox proportional hazards models examined time to symptom remission and time to achieving a good quality of life. ResultsOf the 187 adults with first-episode psychosis eligible for referral to STEP_MaKH, Native/religious healers (n = 86) were the predominant first point of contact. Only 56 (29.9%) accepted referral to STEP_MaKH. Participants referred from Mulago National Referral Hospital more likely to enrol than those referred from Butabika (RR = 4.7; 95% CI: 2.90-7.87). Longer delays from first treatment contact were associated with reduced likelihood of reaching STEP_MaKH (RR = 0.99 per month; p = 0.041). After enrolment, symptoms improved rapidly with 60% achieving PANSS remission by Month 1, and fewer than 10% remained non-remitted by Months 2-3. In adjusted Cox models, participants initially seen by mental health workers achieved remission more quickly than those initially seen by non-medical personnel (HR = 1.48; 95% CI: 1.05-2.10). Older age was associated with slower remission (HR = 0.94; p = 0.023). Quality of life improved over the follow-up period, with earlier attainment of good quality of life among those initially managed by mental health workers. ConclusionsPathways to care for FEP in Uganda are complex and culturally mediated, with substantial attrition before specialised early psychosis care is reached. Referral completion is strongly shaped by referral site and by delays in the care pathway. Once in specialised care, clinical outcomes improve rapidly, and initial contact with mental health workers is associated with faster symptom remission and earlier gains in quality of life. Strengthening referral systems, reducing pathway delays, and developing collaborative detection-and-referral links with community and frontline providers are key priorities for optimising early psychosis outcomes in low-resource settings.

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.

IntroductionAdolescents with mental health disorders represent a vulnerable group with complex care needs, yet their and their relatives experiences in acute inpatient mental health services remain poorly understood. While patient-reported experience measures (PREMs) are increasingly recognized as essential for improving healthcare quality, validated instruments for child and adolescent mental health inpatient settings are lacking--particularly from the perspective of relatives, who are often deeply involved in care. ObjectiveThis study aims to develop and psychometrically evaluate the Relatives Experience Questionnaire for Acute Inpatient Child and Adolescent Mental Health Services (REQ-AICAMHS), the first instrument designed to capture relatives experiences in Norwegian acute inpatient mental health units for adolescents. MethodsThe REQ-AICAMHS will be developed using the Norwegian Institute of Public Healths (NIPH) standard methodology, including a literature review, expert consultation, qualitative interviews, and cognitive testing with relatives. Data will be collected digitally from relatives of all adolescents admitted to 17 acute inpatient child and adolescent mental health units across Norway. Descriptive statistics, exploratory factor analysis (EFA), and Item Response Theory (IRT) using the Generalized Partial Credit Model (GPCM) will be applied to assess data quality, factor structure, construct validity, and internal consistency. Open-ended responses will be analysed using both qualitative and machine learning methods to identify key themes and subdomains of experience. ResultsPreliminary results will include descriptive statistics of respondents, item-level analysis (missing data, ceiling effects), factor loadings and reliability coefficients (Cronbachs alpha [&ge;]0.7), inter-item and scale correlations, construct validity testing, and IRT parameters (item discrimination and threshold estimates). Findings will inform the development of a shortened version of the questionnaire for broader implementation in quality improvement initiatives.

Background Autistic people experience disproportionately high rates of co-occurring mental illness and suicide, yet mental healthcare services routinely fail to meet their needs. Patients unrecognised as autistic are at risk of ineffective or harmful treatment. Autistic psychiatrists occupy a unique position: as members of both medical and autistic communities, they offer dual insider perspectives that may directly shape patient outcomes. Despite being the second largest specialty group in Autistic Doctors International (ADI), this workforce remains largely unrecognised and underutilised. This study examines autistic psychiatrists' perspectives on mental healthcare for autistic people. Methods Loosely structured interviews were conducted with seven senior autistic psychiatrists across child and adolescent, adult, and liaison psychiatry, recruited from a psychiatry-specific subgroup of ADI. Data were analysed using reflexive thematic analysis: codes related to patient care and mental health services were extracted and analysed as a focused subset. Outcomes Nine themes were identified: autistic-to-autistic therapeutic rapport; benefit of recognition and diagnosis; early recognition and education as preventive factors; iatrogenic harm from non-recognition and systemic pathways to misdiagnosis; knowledge gaps and stereotypes; inaccessible services; resource constraints and diagnostic thresholds; autistic psychiatrists as an underutilised resource; and pathways to change. Interpretation Autistic psychiatrists' dual insider positionality affords a unique and under-acknowledged vantage point on what autistic patients experience and where mental healthcare fails them. The mental health burden autistic people carry is substantially shaped by systems not designed for them. Embedding neurodiversity-affirmative practice, closing training gaps, reforming diagnostic pathways, and recognising autistic psychiatrists as a clinical and epistemic resource offer a coherent pathway to improving mental health outcomes for autistic people.

Introduction: Youth mental health presentations are largely heterogenous, making it difficult to match individuals to the most appropriate interventions. Personalised, measurement-based care has the potential to improve clinical decision-making and support shared decision-making, but remains challenging to implement in routine practice. Advances in digital monitoring and causal modelling offer new opportunities to identify individual-level processes driving mental health difficulties and to generate personalised decision-support. This pilot study aims to evaluate the feasibility and acceptability of the Minding Your Mind computational decision-support approach, a newly developed approach integrating routine outcome monitoring, individual-level causal modelling, and personalised feedback to support shared decision-making between young people and their clinicians. Methods and analysis: The study involves two phases. Phase 1 will recruit young people aged 15-25 years and mental health clinicians to participate in workshops to co-design the decision-support approach and its implementation into routine practice. Phase 2 is a prospective, single-arm feasibility study involving young people receiving mental health care and their treating clinicians. Primary outcomes include feasibility, acceptability, appropriateness, and usability of the decision-support approach, assessed via self-report and objective process indicators. Secondary outcomes include changes in use and experiences with shared decision-making, and clinical and functional outcomes. Quantitative analyses will be primarily descriptive, with exploratory pre-post comparisons and sensitivity analyses. Qualitative interviews will explore user experiences and implementation barriers and facilitators. Ethics and dissemination: This study has been approved by the Sydney Local Health District (RPAH Zone) Human Research Ethics Committee (X25-0341). All participants will provide informed consent prior to participation. Findings will be disseminated through peer-reviewed publications, conference presentations, and accessible summaries co-developed with young people with lived experience.

Aim Anxiety disorders in older adults are commonly underdiagnosed and undertreated, especially among minority ethnic groups. This UK multicultural qualitative study aimed to explore and compare beliefs about anxiety among self-reporting White British, South Asian, African and Caribbean older adults, using Leventhal's Common-Sense Model. Methods Individual interviews were conducted with 52 older adults who self-reported anxiety (current or past). Data were managed and analysed using the Framework Method. Professional interpreters facilitated interviews with non-English speakers. Findings The study incorporated the perspectives of 27 older adults with distressing anxiety and 25 with non-distressing anxiety. Participants' beliefs mapped onto the illness-related dimensions in Leventhal's Common-Sense Model. Beliefs about anxiety differed across and within cultural groups, with notable distinctions between participants with distressing and non-distressing anxiety. Those with distressing anxiety neither normalised anxiety nor considered it as an illness trajectory. Overall, participants had a fragmented understanding of anxiety disorders. Specific aspects of older adults' beliefs were influenced by their salient identities rather than their cultural background. Two new dimensions were identified: aggravating factors, believed to trigger or exacerbate anxiety symptoms; protective factors, believed to alleviate or prevent mental health problems. Conclusions Applying Leventhal's Common-Sense Model to anxiety has yielded new insights with significant implications for understanding potential causes of low mental health services use among older adults. Grouping people into broad categories of cultural groups disregards the diversity among individuals within the same group. Cross-cultural research should embrace this diversity and employ nuanced approaches to provide meaningful, person-centred insights into people's perceptions of illness.

Background. There is growing evidence to suggest a clinically significant overlap between autism spectrum conditions and psychotic disorders. Preliminary evidence suggest that autism diagnoses and autistic traits are associated with poorer outcomes following a first episode of psychosis. Methods. This study used data from the Cambridgeshire and Peterborough National Health Service Foundation Trust (CPFT) Research Database to examine clinical outcomes in autistic and non-autistic people following a first episode of psychosis. We describe patterns of community and inpatient service use, using descriptive statistics , Cox regression, binomial logistic regression, and negative binomial regression. Results. Data from 282 autistic and 7127 non-autistic people with psychosis were analysed. Autism was associated with greater community service use (use of mental health emergency lines, mental health detentions by police), as well as greater likelihood of psychiatric hospital admission (adjusted hazard ratio 1.34, 95% confidence interval 1.05 -1.7, p<0.05) and longer inpatient stays (median 111 versus 48 days, p<0.0001). Learning disability played a significant role in the utilisation of community and inpatient services, with lower rates of community service use but longer inpatient admissions. Conclusions. This study indicates a differing pattern of service use between autistic and non-autistic people following psychosis that warrants further research into how best to support autistic people with psychosis.

Depression is accompanied by considerable comorbidity and excess mortality. We examined multimorbidity data using the validated pharmacy-based Rx-Risk Comorbidity Index and examined healthcare costs associated with chronic illness burden in the Australian Genetics of Depression Study (AGDS). Australian Pharmaceutical Benefits Scheme (PBS) record linkage for 15,890 AGDS participants was available from 01/07/2013-31/12/2017. Forty-six health morbidities were inferred by mapping the prescription data using Anatomical Therapeutic Chemical Classification System codes and PBS Item Codes. Morbidity prevalence rates were then compared with an unselected 10% Australian representative population sample (10PCT) with PBS claims data available from 01/07/2010-31/12/2014. The average number of inferred comorbidities was higher among AGDS participants (4.6 {+/-} 2.9) than 10PCT individuals (3.0 {+/-} 3.0). Excluding depression, 89.1% of AGDS participants had one or more inferred comorbidity, most commonly pain (51.0%), inflammation/pain (40.3%), and anxiety (32.3%). In the AGDS, the number of comorbidities was higher among women compared to men and positively correlated with participant age, BMI, number of depressive episodes experienced, and annual health care costs. Compared to participants with no inferred comorbidities, the median annual health care costs were ~65% higher among those with 2-3 comorbidities. This study highlights the patterns of health morbidities experienced by individuals living with depression and shows that this chronic disease burden is significantly associated with increased health costs to the individual and the health system.

BackgroundWhether gaps in smartphone passive-sensing data carry psychological signal -- beyond what a baseline self-report already provides -- is a recurring question in digital phenotyping that has rarely been tested with multiplicity control and cross-validation on the same cohort. ObjectiveTo test whether participant-level missingness in passive sensing and ecological momentary assessment (EMA) is an incremental predictor of depression beyond a single baseline self-report, in the canonical StudentLife cohort. MethodsExploratory re-analysis of the publicly available StudentLife dataset. The original 2014 publication reports n = 48 enrolled undergraduates; the public archive contains 59 distinct sensor-instrumented UIDs, but the additional 11 are sparse-data or PHQ-9-incomplete records and contribute nothing to the between-person analyses, which use only the 38 participants with paired pre-term and post-term Patient Health Questionnaire-9 (PHQ-9). We computed 89 participant-level missingness features from nine continuous sensor streams, five phone-activity logs and 27 EMA prompts, and evaluated them under leave-one-out cross-validation with nested-CV-tuned hyperparameters, cluster-bootstrap confidence intervals, an omnibus joint F-test, and Benjamini-Hochberg multiplicity control. ResultsA pre-term PHQ-9 baseline alone explained 59% of out-of-sample variance in post-term scores (n = 32; 95% cluster-bootstrap CI [0.22, 0.81]). Tuned regularized linear models trained on missingness alone reached only the cohort-mean baseline; adding missingness to pre PHQ-9 did not improve performance. The omnibus joint F-test of all nine continuous-stream missingness rates against post-term PHQ-9, adjusted for pre-term PHQ-9, was non-significant (F (9, 27) = 0.43, P = 0.91). No individual feature survived multiplicity correction. A separate within-person day-level analysis (2,186 person-days) yielded a small valence-specific prospective effect (r = +0.082, 95% CI [+0.011, +0.162]) opposite in direction to the withdrawal hypothesis. ConclusionIn this cohort, smartphone-data missingness did not add incremental predictive value beyond a single baseline PHQ-9. The analysis is exploratory and StudentLife-specific; it should not be read as evidence that missingness is never informative. Plain-language summaryMany studies use the gaps in someones smartphone data -- missing GPS readings, missed survey prompts, fewer phone interactions -- as a possible warning sign of depression. This re-analysis tested that idea on a widely used public dataset from a class of 48 college students. After accounting for each students depression score at the start of the term, the gaps in their phone data added no useful information about their depression score at the end of the term. The result is specific to this dataset and does not mean that smartphone gaps are never informative, but it shows that such claims need careful baseline comparisons. Key PointsO_ST_ABSQuestionC_ST_ABSIs smartphone-data missingness an incremental depression biomarker beyond a single baseline self-report? FindingsIn an exploratory re-analysis of the StudentLife cohort (38 participants with paired PHQ-9 scores), missingness features did not improve prediction of post-term PHQ-9 beyond pre-term PHQ-9 under leave-one-out cross-validation, nested-CV-tuned models, an omnibus joint F-test, or multiplicity-controlled univariate screens. MeaningSmartphone-data missingness should not be interpreted as a psychological signal in absence of baseline-controlled, cross-validated, multiplicity-aware evidence. The result is specific to a high-functioning undergraduate cohort over a ten-week term and requires replication.

Background: While growing enthusiasm for the therapeutic potential of classic psychedelics has led to a rise in non-clinical use, attention to persisting adverse effects has emerged with delay. A subset of individuals reports persisting complications such as hallucinogen persisting perception disorder (HPPD), depersonalization/derealization disorder (DDD), anxiety and depression. Yet few medical services are equipped to address these complications. Aims: This qualitative study examines how societal, medical, and media discourses shape the experiences of individuals with persisting psychedelic-related complications, focusing on help-seeking trajectories. Methods: Thirteen semi-structured interviews with adults experiencing persisting psychedelic-related psychological symptoms (four women, nine men, age 19-49 years; HPPD (n = 10), DDD (n = 6), depression (n = 1), and anxiety (n = 1)) were conducted within a larger study on these complications. Data were analysed using reflexive thematic analysis. Reporting followed the COREQ guidelines. Results: Three interrelated themes emerged: (1) The dissonance between expectation and harm - idealised media and scientific portrayals of psychedelics shaped initial use and complicated recognition of adverse outcomes; (2) Stigma, silence, and self-blame - prohibitionist discourse and internalised shame significantly inhibited help-seeking; and (3) Between systemic absence and self-organised support - participants encountered clinical unpreparedness and epistemic dismissal, which often led them to rely on online peer communities and self-management strategies. Positive clinical encounters, characterised by professional expertise and nonjudgmental engagement, were experienced as helpful. Conclusions: Adequate clinical and conceptual frameworks for persisting psychedelic-related complications are lacking. An interdisciplinary, experience-informed approach integrating realistic risk communication, clinician training, and destigmatisation is required to support affected individuals.

BackgroundMajor depressive disorder (MDD), a leading cause of disability worldwide, exhibits substantial heterogeneity in treatment outcomes. Patients who do not respond to standard antidepressant therapy account for the majority of MDDs disease burden. Risk factors have been implicated in treatment response, including genes impacting on how antidepressants are metabolised. Yet, despite its clinical importance, risk factors for treatment-resistant depression (TRD) remain unexplored in low- and middle-income countries (LMIC). We used data from the DIVERGE study on MDD to investigate the risk factors of TRD in Pakistan. MethodsDIVERGE is a genetic epidemiological study that recruited adult MDD patients ([&ge;]18 years) between Sep 27,2021 to Jun 30, 2025, from psychiatric care facilities across Pakistan. Detailed phenotypic information was collected by trained interviewers and blood samples taken. Infinium Global Diversity Array with Enhanced PGx-8 from Illumina was used for genotyping followed by DRAGEN calling to infer metaboliser phenotypes for Cytochrome P450 (CYP) enzyme genes. We defined TRD as minimal to no improvement after [&ge;]12 weeks of adherent antidepressant therapy. We conducted multi-level logistic regression to test the association of demographic, clinical and pharmacogenetic variables with TRD. FindingsAmong 3,677 eligible patients, polypharmacy was rampant; 86% were prescribed another psychotropic drug along with an antidepressant. Psychological therapies were uncommon (6%) while 49% of patients had previously visited to a religious leader/faith healer in relation to their mental health problems. TRD was experienced by 34% (95%CI: 32-36%) patients. The TRD group was characterised by more psychotic symptoms and suicidal behaviour (OR=1.39, 95%CI=1.04-1.84, p=0.02; OR=1.03, 95%CI=1.01-1.05, p=0.005). Social support (OR=0.55, 95%CI=0.44-0.69, p=1.4x10-7) and parents being first cousins (OR=0.81, 95%CI=0.69-0.96, p=0.01) were associated with lower odds of TRD. In 1,085 patients with CYP enzyme data, poor (OR=1.85, 95%CI=1.11-3.07, p=0.01) and ultra-rapid (OR=3.11, 95%CI=1.59-6.12, p=0.0009) metabolizers for CYP2C19 had increased risk of TRD compared with normal metabolisers. InterpretationThere was an excessive use of polypharmacy in the treatment of depression while psychological therapies were uncommon highlighting the need for more evidence-based practice. This first large study of MDD from Pakistan uncovered the importance of culture-specific forms of social support in preventing TRD, highlighting opportunities for interventions in low-income settings. Pharmacogenetic markers can be leveraged to predict TRD.

Background High Intensity Use of urgent medical services by patients is widely recognised in urgent and emergency care. Studies of high intensity use of the emergency department have consistently shown features of complex systems behaviour in addition to highly heterogeneous individual patient characteristics. There have been no comparable studies of prehospital care use. Methods We examined the use of prehospital urgent and emergency services (NHS 111 and ambulance dispatch) using routinely collected data from regional service in the UK (population 5 million). We used a complex systems perspective, to examine (1) distribution of contacts per individual; (2) the temporal stability of service use by individuals and at the whole-system level (3) the distribution of bursts of contacts. Results We analysed data from 847555 individuals who contacted NHS111 and 389550 who contacted the ambulance dispatch service. 35120 (4.2%) individuals who contacted NHS111 had 5 or more contacts with the service over the two-year period and accounted for 290625 (20.1%) of contacts. 16755 (4.3%) individuals had 5 or more ambulance dispatch contact days and accounted for 169085 (25.8%) of contacts. The distribution of contacts per individual showed a monotonic distribution between 5 and over 100 contacts that was heavy tailed and compatible with a power law distribution. At any level of use, patients with one or more mental health related contacts had a greater likelihood of further contact than those without. Conclusion Prehospital emergency service use shows multiple statistical features typical of a complex system. Interventions to manage demand need to consider both individual high intensity users (particularly in relation to their mental health) and the behaviour of the whole system.