A clinical tool to estimate the risk of treatment-resistant schizophrenia (TRS) in people with first-episode psychosis (FEP) would inform early detection of TRS and overcome the delay of up to 5 years in starting TRS medication.

To develop and evaluate a model that could predict the risk of TRS in routine clinical practice.

We used data from two UK-based FEP cohorts (GAP and AESOP-10) to develop and internally validate a prognostic model that supports identification of patients at high-risk of TRS soon after FEP diagnosis. Using sociodemographic and clinical predictors, a model for predicting risk of TRS was developed based on penalised logistic regression, with missing data handled using multiple imputation. Internal validation was undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. Interviews and focus groups with clinicians were conducted to establish clinically relevant risk thresholds and understand the acceptability and perceived utility of the model.

We included seven factors in the prediction model that are predominantly assessed in clinical practice in patients with FEP. The model predicted treatment resistance among the 1081 patients with reasonable accuracy; the model's C-statistic was 0.727 (95% CI 0.723–0.732) prior to shrinkage and 0.687 after adjustment for optimism. Calibration was good (expected/observed ratio: 0.999; calibration-in-the-large: 0.000584) after adjustment for optimism.

We developed and internally validated a prediction model with reasonably good predictive metrics. Clinicians, patients and carers were involved in the development process. External validation of the tool is needed followed by co-design methodology to support implementation in early intervention services.

Anxiety disorders are a major public health burden with limited treatment options.

We investigated the long-term safety and efficacy of lysergic acid diethylamide (LSD)-assisted therapy in patients with anxiety with or without life-threatening illness.

This study was an a priori-planned long-term follow-up of an investigator-initiated, two-centre trial that used a double-blind, placebo-controlled, two-period, random-order, crossover design with two sessions with either oral LSD (200 μg) or placebo per period. Participants (n = 39) were followed up 1 year after the end-of-study visit to assess symptoms of anxiety, depression and long-term effects of psychedelics using Spielberger's State-Trait Anxiety Inventory–Global (STAI-G), the Beck Depression Inventory (BDI), the Persisting Effects Questionnaire and measures of personality traits using the NEO-Five-Factor Inventory.

Participants reported a sustained reduction of STAI-G scores compared with baseline (least square means (95% CI) = −21.6 (−32.7, −10.4), d = 1.04, P < 0.001, for those who received LSD in the first period (94 weeks after the last LSD treatment) and −16.5 (−26.2, −6.8), d = 1.02, P < 0.05, for those who received LSD in the second period (68 weeks after the last LSD treatment)). Similar effects were observed for comorbid depression with change from baseline BDI scores of −8.1 (−13.2, −3.1), d = 0.71, P < 0.01, and −8.9 (−12.9, −4.9), d = 1.21, P < 0.01, for the LSD-first and placebo-first groups, respectively. Personality trait neuroticism decreased (P < 0.0001) and trait extraversion increased (P < 0.01) compared with study inclusion. Individuals attributed positive long-term effects to the psychedelic experience.

Patients reported sustained long-term effects of LSD-assisted therapy for anxiety.

The longitudinal course of late-life depression remains under-studied.

To describe transitions along the depression continuum in old age and to identify factors associated with specific transition patterns.

We analysed 15-year longitudinal data on 2745 dementia-free persons aged 60+ from the population-based Swedish National Study on Aging and Care in Kungsholmen. Depression (minor and major) was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision; subsyndromal depression (SSD) was operationalised as the presence of ≥2 symptoms without depression. Multistate survival models were used to map depression transitions, including death, and to examine the association of psychosocial (social network, connection and support), lifestyle (smoking, alcohol consumption and physical activity) and clinical (somatic disease count) factors with transition patterns.

Over the follow-up, 19.1% had ≥1 transitions across depressive states, while 6.5% had ≥2. Each additional somatic disease was associated with a higher hazard of progression from no depression (No Dep) to SSD (hazard ratio 1.09; 1.07–1.10) and depression (Dep) (hazard ratio 1.06; 1.04–1.08), but also with a lower recovery (HRSSD−No Dep 0.95; 0.93–0.97 [where ‘HR’ refers to ‘hazard ratio’]; HRDep−No Dep 0.96; 0.93–0.99). Physical activity was associated with an increased hazard of recovery to no depression from SSD (hazard ratio 1.49; 1.28–1.73) and depression (hazard ratio 1.20; 1.00–1.44), while a richer social network was associated with both higher recovery from (HRSSD−No Dep 1.44; 1.26–1.66; HRDep−No Dep 1.51; 1.34–1.71) and lower progression hazards to a worse depressive state (HRNo Dep−SSD 0.81; 0.70–0.94; HRNo Dep−Dep 0.58; 0.46–0.73; HRSSD−Dep 0.66; 0.44–0.98).

Older people may present with heterogeneous depressive trajectories. Targeting the accumulation of somatic diseases and enhancing social interactions may be appropriate for both depression prevention and burden reduction, while promoting physical activity may primarily benefit recovery from depressive disorders.

Dementia is a common and progressive condition whose prevalence is growing worldwide. It is challenging for healthcare systems to provide continuity in clinical services for all patients from diagnosis to death.

To test whether individuals who are most likely to need enhanced care later in the disease course can be identified at the point of diagnosis, thus allowing the targeted intervention.

We used clinical information collected routinely in de-identified electronic patient records from two UK National Health Service (NHS) trusts to identify at diagnosis which individuals were at increased risk of needing enhanced care (psychiatric in-patient or intensive (crisis) community care).

We examined the records of a total of 25 326 patients with dementia. A minority (16% in the Cambridgeshire trust and 2.4% in the London trust) needed enhanced care. Patients who needed enhanced care differed from those who did not in age, cognitive test scores and Health of the Nation Outcome Scale scores. Logistic regression discriminated risk, with an area under the receiver operating characteristic curve (AUROC) of up to 0.78 after 1 year and 0.74 after 4 years. We were able to confirm the validity of the approach in two trusts that differed widely in the populations they serve.

It is possible to identify, at the time of diagnosis of dementia, individuals most likely to need enhanced care later in the disease course. This permits the development of targeted clinical interventions for this high-risk group.

Despite the recognised importance of mental disorders and social disconnectedness for mortality, few studies have examined their co-occurrence.

To examine the interaction between mental disorders and three distinct aspects of social disconnectedness on mortality, while taking into account sex, age and characteristics of the mental disorder.

This cohort study included participants from the Danish National Health Survey in 2013 and 2017 who were followed until 2021. Survey data on social disconnectedness (loneliness, social isolation and low social support) were linked with register data on hospital-diagnosed mental disorders and mortality. Poisson regression was applied to estimate independent and joint associations with mortality, interaction contrasts and attributable proportions.

A total of 162 497 individuals were followed for 886 614 person-years, and 9047 individuals (5.6%) died during follow-up. Among men, interaction between mental disorders and loneliness, social isolation and low social support, respectively, accounted for 47% (95% CI: 21–74%), 24% (95% CI: −15 to 63%) and 61% (95% CI: 35–86%) of the excess mortality after adjustment for demographics, country of birth, somatic morbidity, educational level, income and wealth. In contrast, among women, no excess mortality could be attributed to interaction. No clear trends were identified according to age or characteristics of the mental disorder.

Mortality among men, but not women, with a co-occurring mental disorder and social disconnectedness was substantially elevated compared with what was expected. Awareness of elevated mortality rates among socially disconnected men with mental disorders could be of importance to qualify and guide prevention efforts in psychiatric services.

A significant proportion of people with clozapine-treated schizophrenia develop ‘checking’ compulsions, a phenomenon yet to be understood.

To use habit formation models developed in cognitive neuroscience to investigate the dynamic interplay between psychosis, clozapine dose and obsessive–compulsive symptoms (OCS).

Using the anonymised electronic records of a cohort of clozapine-treated patients, including longitudinal assessments of OCS and psychosis, we performed longitudinal multi-level mediation and multi-level moderation analyses to explore associations of psychosis with obsessiveness and excessive checking. Classic bivariate correlation tests were used to assess clozapine load and checking compulsions. The influence of specific genetic variants was tested in a subsample.

A total of 196 clozapine-treated individuals and 459 face-to-face assessments were included. We found significant OCS to be common (37.9%), with checking being the most prevalent symptom. In mediation models, psychosis severity mediated checking behaviour indirectly by inducing obsessions (r = 0.07, 95% CI 0.04–0.09; P < 0.001). No direct effect of psychosis on checking was identified (r = −0.28, 95% CI −0.09 to 0.03; P = 0.340). After psychosis remission (n = 65), checking compulsions correlated with both clozapine plasma levels (r = 0.35; P = 0.004) and dose (r = 0.38; P = 0.002). None of the glutamatergic and serotonergic genetic variants were found to moderate the effect of psychosis on obsession and compulsion (SLC6A4, SLC1A1 and HTR2C) survived the multiple comparisons correction.

We elucidated different phases of the complex interplay of psychosis and compulsions, which may inform clinicians’ therapeutic decisions.

Elevated risk of psychosis for ethnic minority groups has generally been shown to be mitigated by high ethnic density. However, past survey studies examining UK Pakistani populations have shown an absence of protective ethnic density effects, which is not observed in other South Asian groups.

To assess the ethnic density effect at a local neighbourhood level, in the UK Pakistani population in East Lancashire.

Data was collected by the East Lancashire Early Intervention Service, identifying all cases of first episode psychosis (FEP) within their catchment area between 2012 and 2020. Multilevel Poisson regression analyses were used to compare incidence rates between Pakistani and White majority groups, while controlling for age, gender and area-level deprivation. The ethnic density effect was also examined by comparing incidence rates across high and low density areas.

A total of 455 cases of FEP (364 White, 91 Pakistani) were identified. The Pakistani group had a higher incidence of FEP compared to the White majority population. A clear effect of ethnic density on rates of FEP was shown, with those in low density areas having higher incidence rates compared to the White majority, whereas incidence rates in high density areas did not significantly differ. Within the Pakistani group, a dose-response effect was also observed, with risk of FEP increasing incrementally as ethnic density decreased.

Higher ethnic density related to lower risk of FEP within the Pakistani population in East Lancashire, highlighting the impact of local social context on psychosis incidence.

Introducing new disease-modifying therapies (DMTs) for Alzheimer's disease demands a fundamental shift in diagnosis and care for most health systems around the world. Understanding the views of health professionals, potential patients, care partners and taxpayers is crucial for service planning and expectation management about these new therapies.

To investigate the public's and professionals’ perspectives regarding (1) acceptability of new DMTs for Alzheimer's disease; (2) perceptions of risk/benefits; (3) the public's willingness to pay (WTP).

Informed by the ‘theoretical framework of acceptability’, we conducted two online surveys with 1000 members of the general public and 77 health professionals in Ireland. Descriptive and multivariate regression analyses examined factors associated with DMT acceptance and WTP.

Healthcare professionals had a higher acceptance (65%) than the general public (48%). Professionals were more concerned about potential brain bleeds (70%) and efficacy (68%), while the public focused on accessibility and costs. Younger participants (18–24 years) displayed a higher WTP. Education and insurance affected WTP decisions.

This study exposes complex attitudes toward emerging DMTs for Alzheimer's disease, challenging conventional wisdom in multiple dimensions. A surprising 25% of the public expressed aversion to these new treatments, despite society's deep-rooted fear of dementia in older age. Healthcare professionals displayed nuanced concerns, prioritising clinical effectiveness and potential brain complications. Intriguingly, younger, better-educated and privately insured individuals exhibited a greater WTP, foregrounding critical questions about healthcare equity. These multifaceted findings serve as a guidepost for healthcare strategists, policymakers and ethicists as we edge closer to integrating DMTs into Alzheimer's disease care.

Major depressive disorder (MDD) has been increasingly understood as a disruption of brain connectome. Investigating grey matter structural networks with a large sample size can provide valuable insights into the structural basis of network-level neuropathological underpinnings of MDD.

Using a multisite MRI data-set including nearly 2000 individuals, this study aimed to identify robust topology and connectivity abnormalities of grey matter structural network linked to MDD and relevant clinical phenotypes.

A total of 955 MDD patients and 1009 healthy controls were included from 23 sites. Individualised structural covariance networks (SCN) were established based on grey matter volume maps. Following data harmonisation, network topological metrics and focal connectivity were examined for group-level comparisons, individual-level classification performance and association with clinical ratings. Various validation strategies were applied to confirm the reliability of findings.

Compared with healthy controls, MDD individuals exhibited increased global efficiency, abnormal regional centralities (i.e. thalamus, precentral gyrus, middle cingulate cortex and default mode network) and altered circuit connectivity (i.e. ventral attention network and frontoparietal network). First-episode drug-naive and recurrent patients exhibited different patterns of deficits in network topology and connectivity. In addition, the individual-level classification of topological metrics outperforms that of structural connectivity. The thalamus-insula connectivity was positively associated with the severity of depressive symptoms.

Based on this high-powered data-set, we identified reliable patterns of impaired topology and connectivity of individualised SCN in MDD and relevant subtypes, which adds to the current understanding of neuropathology of MDD and might guide future development of diagnostic and therapeutic markers.

Higher intensity of psychotherapy might improve treatment outcome in depression, especially in those with comorbid personality disorder.

To compare the effects of 25 individual sessions (weekly) of two forms of psychotherapy – short-term psychoanalytic supportive psychotherapy (SPSP) and schema therapy – with the same treatments given for 50 sessions (twice weekly) in people with depression and personality disorder. Trial registration: NTR5941.

We conducted a pragmatic, double-randomised clinical trial and, over 37 months, recruited 246 adult out-patients with comorbid depression/dysthymia and personality disorder. A 2 × 2 factorial design randomised participants to 25 or 50 sessions of SPSP or schema therapy. The primary outcome was change in depression severity over 1 year on the Beck Depression Inventory II (BDI-II). Secondary outcomes were remission both of depression and personality disorder.

Compared with 25 sessions, participants who received 50 sessions showed a significantly greater decrease in depressive symptoms over time (time × session dosage, P < 0.001), with a mean difference of 5.6 BDI points after 1 year (d = −0.53, 95% CI −0.18 to 0.882, P = 0.003). Remission from depression was also greater in the 50-session group (74% v. 58%, P = 0.025), as was remission of personality disorder (74% v. 56%, P = 0.010).

Greater intensity of psychotherapy leads to better outcomes of both depression and personality status in people with comorbid depression and personality disorder.

Multimorbidity, the presence of two or more health conditions, has been identified as a possible risk factor for clinical dementia. It is unclear whether this is due to worsening brain health and underlying neuropathology, or other factors. In some cases, conditions may reflect the same disease process as dementia (e.g. Parkinson's disease, vascular disease), in others, conditions may reflect a prodromal stage of dementia (e.g. depression, anxiety and psychosis).

To assess whether multimorbidity in later life was associated with more severe dementia-related neuropathology at autopsy.

We examined ante-mortem and autopsy data from 767 brain tissue donors from the UK, identifying physical multimorbidity in later life and specific brain-related conditions. We assessed associations between these purported risk factors and dementia-related neuropathological changes at autopsy (Alzheimer's-disease related neuropathology, Lewy body pathology, cerebrovascular disease and limbic-predominant age-related TDP-43 encephalopathy) with logistic models.

Physical multimorbidity was not associated with greater dementia-related neuropathological changes. In the presence of physical multimorbidity, clinical dementia was less likely to be associated with Alzheimer's disease pathology. Conversely, conditions which may be clinical or prodromal manifestations of dementia-related neuropathology (Parkinson's disease, cerebrovascular disease, depression and other psychiatric conditions) were associated with dementia and neuropathological changes.

Physical multimorbidity alone is not associated with greater dementia-related neuropathological change; inappropriate inclusion of brain-related conditions in multimorbidity measures and misdiagnosis of neurodegenerative dementia may better explain increased rates of clinical dementia in multimorbidity

International guidelines present overall symptom severity as the key dimension for clinical characterisation of major depressive disorder (MDD). However, differences may reside within severity levels related to how symptoms interact in an individual patient, called symptom dynamics.

To investigate these individual differences by estimating the proportion of patients that display differences in their symptom dynamics while sharing the same overall symptom severity.

Participants with MDD (n = 73; mean age 34.6 years, s.d. = 13.1; 56.2% female) rated their baseline symptom severity using the Inventory for Depressive Symptomatology Self-Report (IDS-SR). Momentary indicators for depressive symptoms were then collected through ecological momentary assessments five times per day for 28 days; 8395 observations were conducted (average per person: 115; s.d. = 16.8). Each participant's symptom dynamics were estimated using person-specific dynamic network models. Individual differences in these symptom relationship patterns in groups of participants sharing the same symptom severity levels were estimated using individual network invariance tests. Subsequently, the overall proportion of participants that displayed differential symptom dynamics while sharing the same symptom severity was calculated. A supplementary simulation study was conducted to investigate the accuracy of our methodology against false-positive results.

Differential symptom dynamics were identified across 63.0% (95% bootstrapped CI 41.0–82.1) of participants within the same severity group. The average false detection of individual differences was 2.2%.

The majority of participants within the same depressive symptom severity group displayed differential symptom dynamics. Examining symptom dynamics provides information about person-specific psychopathological expression beyond severity levels by revealing how symptoms aggravate each other over time. These results suggest that symptom dynamics may be a promising new dimension for clinical characterisation, warranting replication in independent samples. To inform personalised treatment planning, a next step concerns linking different symptom relationship patterns to treatment response and clinical course, including patterns related to spontaneous recovery and forms of disorder progression.

There are increasing calls for neurodivergent peoples’ involvement in research into neurodevelopmental conditions. So far, however, this has tended to be achieved only through membership of external patient and public involvement (PPI) panels. The Regulating Emotions – Strengthening Adolescent Resilience (RE-STAR) programme is building a new participatory model of translational research that places young people with diagnoses of attention-deficit hyperactivity disorder (ADHD) and autism at the heart of the research team so that they can contribute to shaping and delivering its research plan.

To outline the principles on which the RE-STAR participatory model is based and describe its practical implementation and benefits, especially concerning the central role of members of the Youth Researcher Panel (Y-RPers).

The model presented is a culmination of a 24-month process during which Y-RPers moved from advisors to co-researchers integrated within RE-STAR. It is shaped by the principles of co-intentionality. The account here was agreed following multiple iterative cycles of collaborative discussion between academic researchers, Y-RPers and other stakeholders.

Based on our collective reflections we offer general guidance on how to effectively integrate young people with diagnoses of ADHD and/or autism into the core of the translational research process. We also describe the specific theoretical, methodological and analytical benefits of Y-RPer involvement in RE-STAR.

Although in its infancy, RE-STAR has demonstrated the model's potential to enrich translational science in a way that can change our understanding of the relationship between autism, ADHD and mental health. When appropriately adapted we believe the model can be applied to other types of neurodivergence and/or mental health conditions.

The rising number of dementia diagnoses and imminent adoption of disease-modifying treatments necessitate innovative approaches to identify individuals at risk, monitor disease course and intervene non-pharmacologically earlier in the disease course. Digital assessments of dementia risk and cognitive function have the potential to outperform traditional in-person assessments in terms of their affordability, accuracy and longitudinal tracking abilities. However, their accessibility and reliability in older adults is unclear.

To evaluate the usability and reliability of a smartphone assessment of lifestyle and cognitive factors relevant to dementia risk in a group of UK-based older adults.

Cognitively healthy adults (n = 756) recruited through the Dementias Platform UK Great Minds volunteer register completed three assessments of cognitive function and dementia risk over a 3-month period and provided usability feedback on the Five Lives smartphone application (app). We evaluated cognitive test scores for age, gender and higher education effects, normality distributions, test–retest reliability and their relationship with participants’ lifestyle dementia risk factors.

Participants found the app ‘easy to use’, ‘quick to complete’ and ‘enjoyable’. The cognitive tests showed normal or near-to-normal distributions, variable test–retest reliabilities and age-related effects. Only tests of verbal ability showed gender and education effects. The cognitive tests did not correlate with lifestyle dementia risk scores.

The Five Lives assessment demonstrates high usability and reliability among older adults. These findings highlight the potential of digital assessments in dementia research and clinical practice, enabling improved accessibility and better monitoring of cognitive health on a larger scale than traditional in-person assessments.