BJPsych Open

BackgroundEpidemiological data indicates that the prevalence of depression among young people (YP) is increasing. Evidence-based interventions are effective for many, but 20 to 40% fail to respond and relapse is frequent and therefore, this study placed a particular focus on second-line treatments. The modification of psychological processes that predispose treatment failure or relapse necessitates the development of specific interventions for those who need them. But their evaluation requires clear understanding of current practice to compare and demonstrate effectiveness. MethodsWe explored treatment as usual (TAU) for young people (YP) receiving support for depression in a pilot 2-site feasibility trial comparing a Mindfulness for Adolescents and Carers (MAC) against TAU in Child & Adolescent Mental Health Services (CAMHS) in the UK. We collected qualitative data via interviews with senior managers and case-managing clinicians, as well as quantitative data via Treatment Recording Sheets completed by clinicians for participating YP and a clinical service audit. We synthesised these data across the two trial sites with the intention of providing a description of TAU that could be used to design a future definitive trial of MAC. ResultsWhile there were differences in the approach and provision between the sites, it was possible to produce an understanding of the main components and processes of CAMHS TAU for young people who have depression. Typical pathways include entry/referral, screening and intake; waiting/supportive space; first-line and second-line treatment/s; discharge and re-referral; and crisis support. The most common second-line provision was care co-ordination, provided to YP in both arms of the trial. YP participating in the pilot feasibility trial received different combinations of support and those allocated to MAC received less support from CAMHS than those allocated to TAU. ConclusionsThere is significant variability in the provision of services to YP experiencing depression. Future studies should compare the treatment plus care coordination with TAU.

BackgroundPeople with severe COVID anxiety have significant fears of contagion, physiological symptoms of anxiety in response to a COVID stimuli, and employ safety behaviours which are often in excess of health guidelines and at the expense of other life priorities. The natural course of severe COVID anxiety is not known. MethodsThis prospective cohort study followed 285 people with severe COVID anxiety in United Kingdom over 18-months. Descriptive statistics and linear regression models identified factors associated with change in COVID anxiety. ResultsMost participants experienced major reductions in COVID anxiety over time (69.8% relative cohort mean decrease; p<0.001), but a quarter of people (23.7%, 95% CI 17.8 to 30.1) continued to worry about COVID every day. Increasing age, being from an ethnic background which conferred greater risk from COVID-19, and the persistence of high levels of health anxiety and depressive symptoms predicted significantly slower improvements in severe COVID anxiety adjusting for other clinical and demographic factors. ConclusionsFor most people severe COVID anxiety significantly improves with time. However established interventions treating depression or health anxiety, and targeting older people and people from at-risk minority groups who appear to recover at slower rates, might be clinically indicated in future pandemics. HighlightsO_LIMost people with severe COVID anxiety reported large improvements in symptoms 18-months later. C_LIO_LILevels of co-occurring poor mental health and social functioning also improved for most people. C_LIO_LIMore than 1 in 10 continued to have severe COVID anxiety symptoms 18 months later. C_LIO_LIAge, ethnic background, and high levels of health anxiety and depression predict slower improvements. C_LIO_LIPeople with these risk characteristics could be considered for targeted support. C_LI

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.

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.

BackgroundHealth utility data are rarely routinely collected in mental helath services. Mapping models that predict health utility from other outcome measures are typically derived from cross-sectional data but often used to predict longitudinal change. ObjectiveWe aimed to develop models to map six psychological measures to adolescent Assessment of Quality of Life - Six Dimensions (AQOL-6D) health utility for youth mental health service clients and assess the ability of mapping models to predict longitudinal change. MethodsWe recruited 1107 young people attending Australian primary mental health services, collecting data at two time points, three months apart. Five linear and three generalised linear models were explored to identify the best mapping model. Ten-fold cross-validation using R2, root mean square error (RMSE) and mean absolute error (MAE) were used to compare models and assess predictive ability of six candidate measures of psychological distress, depression and anxiety. Linear / generalised linear mixed effect models were used to construct longitudinal predictive models for AQoL-6D change. ResultsA depression measure (Patient Health Questionnaire-9) was the strongest independent predictor of health utility. Linear regression models with complementary log-log transformation of utility score were the best performing models. Between-person associations were slightly larger than within-person associations for most of the predictors. ConclusionsAdolescent AQoL-6D utility can be derived from a range of psychological distress, depression and anxiety measures. Mapping models estimated from cross-sectional data can approximate longitudinal change but may slightly bias health utility predictions. DataReplication code and model catalogues are available at: https://doi.org/10.7910/DVN/DKDIB0.

ImportanceMultiple data sources suggest that COVID-19 is having adverse effects on mental health. But it is vital to understand what is causing this: worries over potential adversities due to the pandemic, or the toll of experiencing adverse events. ObjectiveTo explore the time-varying longitudinal relationship between (i) worries about adversity, and (ii) experience of adversity, and both anxiety and depression and test the moderating role of socio-economic position. DesignLongitudinal cohort study SettingCommunity study ParticipantsA well-stratified sample of UK adults recruited into the UCL COVID -19 Social Study (a panel study collecting data weekly during the Covid-19 pandemic) via a combination of convenience and targeted recruitment. The sample was weighted to population proportions of gender, age, ethnicity, education and geographical location. ExposuresWorries or experiences of adversities during the COVID-19 pandemic OutcomesAnxiety (GAD-7) and depression (PHQ-9) ResultsData were analysed from 41,909 UK adults (weighted data: 51% female, aged 18-99) followed up across 6 weeks (178,430 observations). Using fixed effects regression was used to explore within-person variation over time, cumulative number of worries and experience of adversities were both related to higher levels of anxiety and depression. Number of worries were associated more with anxiety than depression, but number of experiences were equally related to anxiety and depression. Individuals of lower socio-economic position were more negatively affected psychologically by adverse experiences. Conclusions & relevanceMeasures over the first few weeks of lockdown in the UK appear to have been insufficient at reassuring people given we are still seeing clear associations with poor mental health both for cumulative worries and also for a range of specific worries relating to finance, access to essentials, personal safety and COVID-19. Interventions are required that both seek to prevent adverse events (e.g. redundancies) and that reassure individuals and support adaptive coping strategies. Key pointsO_ST_ABSQuestionC_ST_ABSHow do worries over potential adversities due to the COVID-19 pandemic, or the toll of experiencing adverse events affect mental health? FindingsCumulative number of worries and experience of adversities were both related to higher levels of anxiety and depression during COVID-19, especially amongst individuals of lower socio-economic position. MeaningDuring a pandemic, interventions are required that both seek to prevent adverse events (e.g. redundancies) and that reassure individuals and support adaptive coping strategies.

BackgroundWe investigated the extent to which positive changes in stigma outcomes reported over the course of Time to Change were sustained by 2023, two years after the programmes end in 2021. MethodsWe used regression analyses to evaluate trends in outcomes. Measures were of stigma-related knowledge (Mental Health Knowledge Schedule (MAKS)), attitudes (Community Attitudes to the Mentally Ill scale (CAMI)), and desire for social distance (Reported and Intended Behaviour Scale (RIBS)). We also examined willingness to interact with people based on vignettes of depression and schizophrenia, and attitudes towards workplace discrimination against people with these conditions, using data from the British Social Attitudes Survey (BSAS) 2015 for comparison. FindingsReported in standard deviation units (95% confidence intervals (CI)), attitudes towards mental illness improved between 2008 and 2023 (SD=0.24, 95% CI=0.16 to 0.31), but following an increase of 9.9% between 2008-19, scores decreased by 3.3% (p=0.015). After improvements to 2019, 2023 MAKS and RIBS scores no longer differed from 2009 scores, indicating decreases since 2019 in stigma-related knowledge (MAKS scores declined 7.8% since 2019, p<0.001) and willingness to interact (RIBS scores declined by 10.2% since 2019, p<0.001). Conversely, comparison with BSAS 2015 data indicated that in 2023 respondents were more willing to interact with people with depression ({beta}=-2.69, p<0.001) and schizophrenia ({beta}=-2.70, p<0.001); and more likely to agree that people with either condition are just as likely to be promoted, and to disagree that their medical history should influence this. This change was most pronounced for schizophrenia (OR=2.52, 95% CI=2.02 to 3.14). ConclusionsThe lasting positive changes reflect support for non-discrimination and willingness to interact with someone after a sense of familiarity is evoked. Besides the end of Time to Change, interpretations for declines in other outcomes include the impacts of the covid-19 pandemic; economic stress; and reduced access to healthcare.

BackgroundThere is a growing global awareness of the psychological consequences of long Covid, supported by emerging empirical evidence. However, the mergence and long-term trajectories of psychological symptoms following the infection are still unclear. AimsTo examine when psychological symptoms first emerge following the infection with SARS-CoV-2, and the long-term trajectories of psychological symptoms comparing long and short Covid groups. MethodsWe analysed longitudinal data from the UCL Covid-19 Social Study (March 2020-November 2021). We included data from adults living in England who reported contracting SARS-CoV-2 by November 2021 (N=3,115). Of these, 15.9% reported having had long Covid (N=495). They were matched to participants who had short Covid using propensity score matching on a variety of demographic, socioeconomic and health covariates (N=962, n=13,325) and data were further analysed using growth curve modelling. ResultsDepressive and anxiety symptoms increased immediately following the onset of infection in both long and short Covid groups. But the long Covid group had substantially greater initial increases in depressive symptoms and heightened levels over 22 months follow-up. Initial increases in anxiety were not significantly different between groups, but only the short Covid group experienced an improvement in anxiety over follow-up, leading to widening differences between groups. ConclusionsThe findings shed light on the psychobiological pathways involved in the development of psychological symptoms relating to long Covid. The results highlight the need for monitoring of mental health and provision of adequate support to be interwoven with diagnosis and treatment of the physical consequences of long Covid.

There is an urgent need for services to address the social and economic adversities which contribute to the aetiology and outcomes of mental health problems. However, the implementation of interventions to do so is inconsistent, and entrenched cycles of poor mental health and social exclusion persist. We conducted a service evaluation survey of 28 staff working across community and inpatient teams, enhanced by a series of in-depth case studies, in the largest NHS mental health trust in the UK to explore how social and economic needs are currently assessed and addressed. We found that assessment for social and economic needs varied across different domains; for example, family relationships were more consistently assessed than domains such as education and income. A range of support is available and provided by a patchwork of teams, including Community Mental Health Teams, other NHS teams, Local Authority staff, and many third sector organisations. However, what support is available is severely restricted and respondents highlighted a lack of adequate support in every domain we considered - employment, education and training, social participation and connectedness, family relationships, community support, social security, debt, income, housing, and trauma and victimisation, as well as additional domains including healthy eating, sex and relationships, and activities of daily living. Nevertheless, our case studies illustrate examples of approaches to addressing social and economic needs to improve outcomes for people with mental health problems.

BackgroundCognitive function is a significant predictor of health and mortality in the population. Common mental health problems, such as depression and anxiety, are associated with both cognitive impairments and increased functional impairment. This study aimed to examine the relationship between cognition, mental health and functioning across two cohorts. MethodsParticipants were recruited from an online population cohort, HealthWise Wales (N=3,679), and a psychiatric cohort, the National Centre for Mental Health (NCMH, N=1,036), to complete a cognitive battery and the World Health Organisation Disability Assessment Schedule (WHODAS). We assessed the associations between cognitive performance and the WHODAS, as well as two measures of life functioning: current employment and cohabitation with a partner. We examined the role of current mood, education and health/lifestyle factors using linear and logistic regression. ResultsHigher cognitive performance was associated with fewer functional difficulties on the WHODAS (HealthWise Wales: B=-0.12, 95%CI[-0.15,-0.09], P<0.001; NCMH: B=-0.1, 95%CI[-0.13,-0.08], P<0.001), being in employment or education (HealthWise Wales: OR=1.22, 95%CI[1.11,1.34], P<0.001; NCMH: OR=1.31, 95%CI[1.19,1.46], P<0.001) and living with a partner (HealthWise Wales only: OR=1.19, 95%CI[1.06,1.32], P=0.003). Higher levels of depression and anxiety symptoms were consistently associated with reduced functioning across all analyses. The relationship between cognition and functioning remained significant but attenuated after accounting for these symptoms. ConclusionsCognitive function was associated with functioning in both samples. This association may be partially explained by current symptoms of depression and anxiety. Both cognitive function and common mental health problems may be potential intervention targets to alleviate daily difficulties.

BackgroundTo investigate factors associated with anxiety, depression, and self-reported general health during "lockdown" due to COVID-19 in the UK. MethodsOnline cross-sectional survey of a nationally-representative sample of 2240 participants living in the UK aged 18 years or over (data collected 6-7 May 2020). Participants were recruited from YouGovs online research panel. OutcomesIn this sample, 21{middle dot}9% (n=458, 95% CI [20{middle dot}1% to 23{middle dot}7%]) reported probable anxiety (scored three or over on the GAD-2); while 23{middle dot}5% (n=494, 95% CI [21{middle dot}7% to 25{middle dot}3]) reported probable depression (scored three or over on the PHQ-2). Poorer mental health was associated with greater financial hardship during the lockdown, thinking that you would lose contact with friends or family if you followed Government measures, more conflict with household members during the lockdown, less sense of community with people in your neighbourhood, and lower perceived effectiveness of Government measures. Females and those who were younger were likely to report higher levels of anxiety and depression. The majority of participants reported their general health as "good" (as measured by the first item of the SF-36). Poorer self-reported general health was associated with psychological distress, greater worry about COVID-19 and markers of inequality. InterpretationRates of self-reported anxiety and depression in the UK during the lockdown were greater than population norms. Reducing financial hardship, promoting social connectedness, and increasing solidarity with neighbours and household members may help ease rifts within the community which are associated with distress, thereby improving mental health. Reducing inequality may also improve general health. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSO_LIQuarantine is associated with adverse psychological outcomes. C_LIO_LIPsychological distress during quarantine is associated with greater financial loss, greater perceived susceptibility to and severity of the illness, and greater frustration and boredom during quarantine. C_LIO_LIMeasures put in place to prevent the spread of COVID-19 have highlighted existing inequalities in society, disproportionally affecting younger people, those in lower-income households, and Black and minority ethnic groups. C_LIO_LIResearch in the UK and other countries indicates that rates of anxiety and depression during restrictions of movement such as "lockdown" measures are higher than population norms. C_LI Added value of this studyO_LIIn this study, 22% of the sample reported anxiety, while 24% reported depression. Normative data indicate that these rates are usually approximately 5% and 7% respectively. C_LIO_LIFactors associated with psychological distress included greater financial hardship, poorer social connectedness, greater conflict within the household and the wider neighbourhood, being female and of younger age. C_LIO_LISelf-reported general health in the sample was "good" on average. Factors associated with poorer self-reported general health included markers of inequality and greater worry about COVID-19. C_LI Implications of all the available evidenceO_LIDecreasing the financial impact of measures put in place to prevent the spread of COVID-19 may help improve mental health. C_LIO_LIInterventions promoting social connectedness in isolated young people and measures that increase household and neighbourhood solidarity may help improve mental health. C_LI

BackgroundPeer support roles in mental health services are rapidly increasing in the UK and internationally. However, there is wide variation in these roles and limited research exploring the ways in which Peer Support Workers (PSWs) are currently working. We aimed to explore: 1) the distinctive features of PSWs approaches in mental healthcare; 2) the values underpinning the role and 3) the perceived impact of the role. MethodsWe conducted semi-structured qualitative interviews with paid mental health PSWs working across a range of settings. We took a co-produced, participatory approach: interviews were carried out by researchers with lived experience of mental health conditions and data were analysed using collaborative methods, guided by general principles of thematic analysis. ResultsWe interviewed 35 PSWs. Overarching themes identified from iterative analysis included: 1) The centrality of an individualised, flexible, approach, facilitating recovery through sharing lived experiences and building connection. PSWs advocated for service-user needs and most worked in non-clinical ways, offering holistic, recovery-orientated support. Tensions could arise with more clinical approaches. 2) Underpinning values included: i) Recovery is possible: bringing hope, role-modelling and encouraging change, ii) Mutuality: sharing lived experiences to bring empathy and build connection, iii) Person-centred approach: adapting ways of working to the individual, iv) Empowering instead of fixing service users. 3) the role had benefits for participants own recovery, although its emotional demands could lead to burnout. Participants thought that peer support helped service users feel understood, leading to greater openness and facilitating recovery, although some felt that it may not be right for everyone. Participants felt that PSWs could bring systemic improvements to services and use their lived experience to help teams -meet service user needs. ConclusionPSWs work in a range of ways, but, a unifying feature is a flexible, person-centred approach, facilitating recovery through shared lived experience. A range of potential benefits of peer work were identified for PSWs and for service users, as well as reports of positive systemic change. These could be facilitated by recovery-orientated models in services, space for shared learning with PSWs, and flexibility to incorporate PSWs unique ways of working.

ObjectivePsychiatric conditions arise from a complex interplay of genetics and environment. Many people struggle to interpret genetic risk, leading to distress and inadequately informed decisions. Mental health professionals are often the first point of contact for patients with questions about psychiatric genetic risk. We aimed to uncover UK-based psychiatric professionals knowledge and perceptions of psychiatric genetic risk, comparing those with and without a medical degree to identify training gaps. MethodsHealthcare professionals (n=152) were recruited via email and social media. An online survey assessed: 1) genetic knowledge using the 6-item International Genetic Literacy and Attitudes Survey (iGLAS), 2) confidence discussing genetic and environmental risk, 3) perceived contributions of genetic and environmental factors to psychiatric conditions, and 4) how often patients and relatives ask questions about genetic or environmental risk. We compared those with a medical degree (n=56) to those without (n=96) via linear regressions. ResultsOne-quarter indicated patients always or often asked about genetic risk for their psychiatric condition. Whilst participants genetic knowledge was good (mean iGLAS score=4.36 out of 6), 10% believed at least one psychiatric condition was caused by only environmental or only genetic factors. Only 30% feel confident discussing genetic risk with patients and their relatives. Participants with a medical degree demonstrated significantly greater genetic knowledge (mean iGLAS score=5.02, SD=0.91) than those without (mean=3.97, SD=1.31; {beta}=1.05, 95% CI=0.64, 1.47, p<0.001), and were more confident discussing genetic risk ({beta}=0.60, 95% CI=0.20, 1.01, p=0.004), however this latter finding was non- significant after controlling for sex. Confidence discussing environmental risk was not linked to training background. ConclusionsPatients and their relatives are curious about genetic risk, yet professionals confidence discussing this was low, especially among those without medical degrees. We highlight a specific training gap related to genetics and support calls for accessible psychiatric genetics education for mental health professionals.

Using data from the Attitudes to Mental Illness (AMI) survey, we previously reported positive change in mental health stigma in England between 2008-2019. However, following the conclusion of the Time to Change campaign in 2021, 2023 data revealed a deterioration in several stigma-related attitudes. This report presents AMI survey 2024 results, examining changes over the past year. Regression analyses assessed stigma-related knowledge (Mental Health Knowledge Schedule (MAKS)), attitudes (Community Attitudes toward the Mentally Ill scale (CAMI)) and behavioural intent (Reported and Intended Behaviour Scale (RIBS-IB)), along with willingness to interact based on vignettes of depression and schizophrenia. The proportion of respondents achieving 2023-level MAKS and CAMI scores declined significantly (by 3.5%, p=0.028; and 7.0%, p<0.001), while RIBS-IB scores showed a non-significant decrease. Vignette responses remained stable, but there are signs of increasing desire for social distance. This report explores potential drivers of these trends.

BackgroundMultimorbidity, the co-occurrence of two or more conditions within an individual, is a growing challenge for health and care delivery as well as for research. Combinations of physical and mental health conditions are highlighted as particularly important. The aim of this study was to investigate associations between physical multimorbidity and subsequent depression. Methods and FindingsWe performed a clustering analysis upon physical morbidity data for UK Biobank participants aged 37-73 years at baseline data collection between 2006-2010. Of 502,353 participants, 142,005 had linked general practice data with at least one physical condition at baseline. Following stratification by sex (77,785 women; 64,220 men), we used four clustering methods (agglomerative hierarchical clustering, latent class analysis, k-medoids and k-modes) and selected the best-performing method based on clustering metrics. We used Fishers Exact test to determine significant over-/under-representation of conditions within each cluster. Amongst people with no prior depression, we used survival analysis to estimate associations between cluster-membership and time to subsequent depression diagnosis. The k-modes models consistently performed best, and the over-/under-represented conditions in the resultant clusters reflected known associations. For example, clusters containing an overrepresentation of cardiometabolic conditions were amongst the largest clusters in the whole cohort (15.5% of participants, 19.7% of women, 24.2% of men). Cluster associations with depression varied from hazard ratio (HR) 1.29 (95% confidence interval (CI) 0.85-1.98) to HR 2.67 (95% CI 2.24-3.17), but almost all clusters showed a higher association with depression than those without physical conditions. ConclusionsWe found that certain groups of physical multimorbidity may be associated with a higher risk of subsequent depression. However, our findings invite further investigation into other factors, like social ones, which may link physical multimorbidity with depression.

BackgroundEvidence suggests that people with severe mental illness (SMI) are at an increased risk of infection mortality compared to the general population. Little is known about how this risk might differ across infection types, and the potential impact of sociodemographic and clinical factors. We investigated associations between SMI and infection mortality in a population-based cohort, examining variation by infection type and potential moderating factors. Study designThis retrospective matched cohort study used national primary care data from the Clinical Practice Research Datalink (CPRD) from 1 January 2000 to 31 December 2019 linked with Office of National Statistics (ONS) mortality data. Competing risks regression and cause-specific hazard models assessed risk of infection mortality in people with SMI versus non-SMI controls. We examined risk across different infection types and assessed the impact of sociodemographic and clinical factors. Study resultsOur cohort comprised 84,494 people with SMI matched on age, gender, and GP practice with 84,494 non-SMI controls. Fully adjusted models showed that people with SMI were more likely to die from any infection compared to non-SMI controls (adjusted hazards ratio (aHR)=1.58, 95% confidence intervals (CI)=1.44 to 1.74). Infection-specific analyses revealed increased risk of death from respiratory (aHR=1.69, 95% CI=1.51 to 1.89), gastrointestinal (aHR=2.01, 95% CI=1.16 to 3.48), and renal/urinary (aHR=1.70, 95% CI=1.32 to 2.19) infections in the SMI group. ConclusionsPeople with SMI are at increased risk of infection mortality, especially from respiratory, gastrointestinal, and renal/urinary infections. We recommend prioritising this group for preventative measures including influenza and pneumococcal vaccines.

BackgroundDepressive and anxiety disorders are the most common mental health conditions. In the United Kingdom (UK), NHS Talking Therapies for anxiety and depression (TTad) has provided evidence-based interventions for these conditions since 2008, although treatment outcomes are often suboptimal. Loneliness, consistently linked with poorer mental health outcomes, remains unexplored in this context. We investigated the views of NHS TTad therapists about the nature and origins of loneliness amongst their clients. MethodsWe conducted semi-structured qualitative interviews with 19 NHS TTad therapists, purposively sampled across job roles, experience levels, and service locations. Recruitment was via professional networks and online platforms. Interviews were conducted online, and data were analysed using thematic analysis with both inductive and deductive approaches. FindingsFour key themes emerged from analysis: (1) Life-transitions, (2) Mental health conditions, (3) Barriers to connection, (4) Stigma. NHS TTad therapists described loneliness experienced amongst their clients as arising from both external factors (e.g., relocation, financial difficulties) and internal psychological processes (e.g., low self-esteem, mental health conditions). Therapists believed that loneliness was experienced even when clients had social contacts, due to barriers like cultural differences and mental health symptoms. Therapists also observed some demographic variability in the experience of loneliness amongst clients (e.g., across age, gender, mental health diagnosis). Societal factors including stigma surrounding mental health and loneliness were viewed as further contributing to clients loneliness experiences and help-seeking behaviours. ConclusionsNHS TTad therapists perceived loneliness as a common experience amongst their clients, linked to life transitions, mental health symptoms, structural, cultural, and psychological barriers to connection. These findings highlighted the importance of recognising loneliness as a relevant factor in therapy and of developing strategies to identify and address it within, or outside of NHS TTad services. Future research should also examine the impact of social media, gender, and public stigma on loneliness. Addressing these factors at societal and policy levels is essential to reduce stigma and improve support for individuals experiencing loneliness.

BackgroundPeople with severe mental illnesses (SMIs) are three times more likely to smoke than the wider population, contributing to widening health inequalities. Here we report the long term [3 year] outcomes for the SCIMITAR+ trial (ISRCTN72955454), which compared usual care to a bespoke smoking cessation package. MethodsWe recruited 526 heavy smokers with bipolar illness or schizophrenia who were randomly allocated to a bespoke smoking cessation intervention (n=265) or to usual care (n=261) between October 2015 and December 2016. We measured long-term quitting by carbon monoxide-verified smoking status at 3 years post randomisation, and a range of secondary outcomes. Results261 of the original 526 were followed up. 209 participants (80.1% of followed-up; 39.7% of randomised) could be defined as a smoker or non-smoker for the 36-month primary analysis. Forty-three participants (16.5% of 261) were determined to be a non-smoker via self-reporting and CO confirmation; 21 in the intervention arm (16.3% of 129; 19.6% of those who provided both self-reported and CO measure) and 22 in the control arm (16.7% of 132; 21.6% of those who provided both self-reported and CO measure) - adjusted OR of 0.89 (95% CI 0.45, 1.77, p = 0.74). For secondary outcomes, there was no sustained between group difference in reduction in nicotine dependence (measured using the Fagerstrom Test for Nicotine Dependence) or motivation to quit. Some short-term improvements in physical health (measured by the Short Form 12) were present at 36 months. ConclusionsA bespoke intervention represents the model for care for mental health services in the UK, but long term quit rates cannot be assumed. Sustained attention to smoking and relapse is likely to be needed to ensure that short term gains are maintained. The certainty of these results is tempered by loss to follow up and low statistical power. FundingThis study was funded by NIHR Health Technology Assessment Programme (Project number 11/136/52) Plain English SummarySmoking rates are very high amongst people who use mental health services. This makes a significant contribution to health inequalities and reduced life expectancy. Earlier research has shown that smoking cessation services are effective when the specific needs of people with mental ill health are taken into account. This forms the basis of guidelines issued by the National Institute for Health and Care Excellence. In this study we looked at the longer-term impact of an intervention to help people to quit smoking. At three years under half of the people who took part in the original study were able to provide information on their use of tobacco. The rates of smoking were similar between people who received the intervention three years ago, and those who received only usual care. Since we already know that the intervention is effective in helping people to quit in the short term, it would be prudent to ensure that people continue to be offered care to help them to quit if they are at risk of relapse. The longer-term impact of a brief intervention on longer term quit rates cannot be assumed, since the strength of this conclusion is limited because we were only able to follow up under half of the people who took part in the study. Further research is needed into the optimum way in which the health benefits of quitting can be sustained in the longer term.

BackgroundRemote measurement technologies (RMT), such as smartphones and wearables, allow data collection from an individual in real-time during their day-to-day life, from which their mood, physiology, behaviour, and environment can be inferred. As such, RMT could monitor and detect changes relevant to depression for objective screening, symptom management, relapse-prevention, and personalised interventions. Whilst RMT for depression in young people has been previously reviewed, technological capability and digital mental health literature steeply increase each year but with limited scrutiny of the realist and ethical considerations likely to impact the benefits, implementation, and overall potential of RMT in the real-world. MethodsA realist review of RMT for depression in young people aged 14 - 24 years was conducted in collaboration with two young, lived experience co-researchers from The McPin Foundation Young Peoples Network (YPN) and in accordance with the Realist and Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) for quality and publication. Iterative searches across 10 electronic databases and 7 sources of grey literature, fine-tuning of selection-criteria, data extraction and evidence synthesis with insights from the wider YPN members allowed gradual refinement of an initial framework into a realist intervention theory. ResultsOf 6118 records identified, 104 were included in evidence synthesis. What does and does not work? Smartphones were most preferred, with both passive and active data collection for a holistic approach but a balance between data quality, intrusiveness, and data privacy. From the evidence currently available, depression was best detected by changes in sleep, mobility, smartphone use, social communication, and self- or- parent-reported mood. This had some uses in screening, self-monitoring, and feedback to the healthcare professional but not in relapse-prevention and personalised interventions, where significantly more research is required. How and why? The impact of RMT as an intervention itself on depression outcomes remained unclear but self-monitoring and feedback improved emotional self-awareness, therapeutic relationship, and help-seeking behaviours. For whom? With limited standardisation and investigation of the impact of depression on adherence rates, there may be an overestimation of how much young people are likely to use RMT in the real-world. However, they were most likely to benefit those interested in and motivated by the data-driven nature, who have lower depression severity, no co-morbidities where self-monitoring could cause harm, and the presence of changeable behaviours. In what contexts? RMT facilitated monitoring during transition to university, known to be associated with worsening depression in young people; however, there were significant challenges in health care and school settings. Adaptability was important, such that RMT were culturally compelling and accurate for the local context. Overall, there were many gaps in the evidence and common methodological issues across the literature. ConclusionsFrom the evidence base and lived experience insights, realist and ethical considerations were highlighted, as well as the remaining gaps in evidence and methodological issues common across the literature. For RMT to be the scalable solution for depression in young people rather than a case of overplayed potential, several important recommendations for future research and practice were made.

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.