Shared decision-making is essential to patient-centred care, but remains underutilised in psychiatry, particularly when deciding whether to continue, reduce or stop antipsychotic medication after remission from first-episode psychosis (FEP). Existing decision aids do not fully address recovery goals such as autonomy, identity and social reintegration.

To co-develop a patient decision aid (PDA) prototype that supports individuals in making the decision to continue, reduce or stop antipsychotics following remission from FEP.

We used a patient-centred design process informed by International Patient Decision Aid Standards (IPDAS), User Centered Design (UCD-11) and the CHIME framework. A multidisciplinary steering group – including individuals with lived experience, clinicians, and researchers – co-developed the PDA. Iterative feedback was collected from an external advisory group of patient partners, caregivers and healthcare providers (n = 7). Acceptability was evaluated with structured questionnaires.

The final prototype, structured into five sections (decision overview, personal values, risks and benefits, planning and real-life experiences), demonstrated strong acceptability across stakeholders. Ratings improved with each iteration, with version 3 receiving near-perfect scores on clarity, usefulness and balance. Users described the tool as relatable and empowering. The inclusion of real-life stories and visual decision exercises were particularly valued. However, some clinicians expressed concerns about time constraints and workflow integration.

This recovery-oriented PDA prototype offers a practical, evidence-based resource to facilitate shared decision-making with respect to continuing, reducing or stopping antipsychotics after FEP. Although early feedback is promising, pilot testing is needed to evaluate its impact on decision quality, satisfaction and treatment outcomes.

Real-world evidence on pharmacotherapy for bipolar disorder remains limited; in particular, the effectiveness of combination therapies that are widely used in clinical practice has not been systematically assessed.

To assess the effectiveness of mono- and combination therapy with mood stabilisers and antipsychotics in preventing psychiatric hospitalisation.

This population-based cohort study used a within-individual design and data from the National Database of Health Insurance Claims and Specific Health Check-ups of Japan. Patients aged ≥20 years, with a primary diagnosis of bipolar disorder treated in psychiatric settings between 1 April 2013 and 31 March 2022, were included. Follow-up continued until 31 May 2023. Exposures included monotherapy with mood stabilisers or antipsychotics, and combination therapy involving (a) lithium plus another mood stabiliser or (b) lithium, valproate or lamotrigine plus a commonly prescribed antipsychotic. The primary outcome was time to psychiatric hospitalisation. Adjusted hazard ratios (aHRs) with 95% confidence intervals were estimated using stratified Cox regression.

Among 315 046 patients (median follow-up 7.1 years), 83 621 (26.5%) experienced psychiatric hospitalisation. Monotherapy with lithium (aHR 0.67 [0.66–0.68]), valproate (aHR 0.71, 95% CI 0.70–0.73), lamotrigine (aHR 0.72, 95% CI 0.69–0.75) and carbamazepine (aHR 0.74, 95% CI 0.70–0.78) was associated with reduced hospitalisation compared with non-use of any mood stabilisers. Antipsychotic monotherapy with 15 agents, including aripiprazole (aHR 0.73, 95% CI 0.70–0.75) and zotepine (aHR 0.74, 95% CI 0.69–0.79), was also associated with reduced risk compared with non-use of any antipsychotics. Combination therapy with lithium plus carbamazepine (aHR 0.73, 95% CI 0.64–0.83), zotepine (aHR 0.82, 95% CI 0.72–0.93), aripiprazole (aHR 0.87, 95% CI0.82–0.92) or valproate (aHR 0.92, 95% CI 0.87–0.97) was associated with further reductions in hospitalisation risk compared with lithium monotherapy.

This large, population-based study showed that monotherapy and combination therapy with mood stabilisers and antipsychotics varied in their effectiveness in preventing psychiatric hospitalisation. These findings may inform treatment decisions in the clinical management of bipolar disorder.

Psychotropic medication use has been shown to be associated with decreased bone mineral density (BMD) and quality, and increased fracture risk. Less is known about psychotropic use and associated bone loss over time.

To determine the association between psychotropic medication use and bone loss in men.

Data from 940 men (aged ≥20 years) participating in the Geelong Osteoporosis Study were used in this longitudinal study. BMD (g/cm2) at the spine and hip were measured with dual-energy X-ray absorptiometry at baseline, and 5 and 15 years post-baseline. Body mass index (BMI) was calculated, lifestyle factors and medication use was self-reported, and socioeconomic status was determined. Mood and anxiety disorders were identified through a clinical interview. Multivariable linear regression was used to determine the associations.

Over the study period (median 13.2 years), psychotropic use was associated with change in BMD at the spine (unadjusted mean difference −0.063 g/cm2, 95% CI −0.096 to −0.031, p < 0.001) and hip (−0.038 g/cm2, 95% CI −0.059 to −0.017, p < 0.001). BMI was identified as an effect modifier. Psychotropic use was associated with spine and hip bone loss at the 25th (adjusted mean difference −0.077g/cm2 (95% CI −0.122 to −0.033); and −0.058 g/cm2 (95% CI −0.084 to −0.032), respectively) and 50th percentile (adjusted mean difference −0.053 g/cm2 (95% CI −0.089 to −0.018) and −0.038 g/cm2 (95% CI −0.059 to −0.017), respectively), but not the 75th percentile of BMI (p = 0.121 and p = 0.106, respectively).

Psychotropic use was associated with bone loss in non-obese men, highlighting the need for regular monitoring and preventive strategies to protect bone health.

Antipsychotics used to treat severe mental illness (SMI) markedly raise the risk of metabolic syndrome. Early weight gain predicts worse outcomes, making timely intervention vital, particularly within the first 6 months, when the most weight loss is achievable. This meta-analysis evaluated non-pharmacological weight/body mass index (BMI) management interventions during the first 6 months of their use in people receiving antipsychotics for SMI, to identify effective components with the aim of preventing long-term metabolic complications. Systematic searches of five databases (to October 2024) yielded 1483 studies; 8 (643 participants) met inclusion criteria. Interventions included exercise, nutrition, education, monitoring and psychological input, delivered individually or in groups.

Meta-analysis showed significant weight (−1.93 kg) and BMI (−1.12 kg/m2) reductions. Group-based, multi-component programmes with psychological input were most effective.

Group-based, multi-component interventions that include a psychological element produced the greatest reductions in weight and BMI. Future research should focus on refining and embedding psychologically informed, multi-component group programmes into routine psychiatric care to optimise long-term physical health outcomes.

People with psychosis have a life expectancy that is reduced by 15 years, mainly owing to preventable physical illnesses of which obesity is a precursor. Obesity is three times more common in individuals with psychosis, and antipsychotics are an important cause. Prediction could individualise obesity treatment, but current models are not fully actionable for individuals.

To test whether antipsychotic-induced weight increase at 1 year is causally mediated by weight change in the first 12 weeks of treatment, and then develop and internally validate a causal actionable prediction pathway to prevent antipsychotic-induced obesity.

This was a post hoc analysis of a clinical trial of olanzapine versus haloperidol which recruited 263 participants with first-episode psychosis. We conducted two distinct analyses: causal mediation and prediction modelling, within which there were two sequential models (a baseline model to predict 12-week outcome and a 12-week model to predict 1-year outcome), followed by counterfactual prediction. In the first analysis, we used parallel causal mediation analysis to determine the natural direct and indirect and total effects of antipsychotic choice on weight in 97 participants, considering two mediators: weight change from 0 to 12 weeks, and weight change from 12 to 52 weeks. In the second analysis, we first developed a baseline causal actionable prediction model to predict weight gain at 12 weeks in 172 participants and then a 12-week model to predict obesity at 1 year in 97 of the participants. Finally, we demonstrated counterfactual prediction.

Antipsychotic-induced weight gain at 1 year appeared to be causally mediated by weight change during the first 12 weeks of treatment (indirect effect 5.70; 95% CI 2.83 to 8.66). At internal validation, the discrimination c-statistic for the baseline causal actionable prediction model was 0.728 (95% CI 0.661 to 0.801), and the calibration slope was 0.768 (95% CI 0.436 to 1.21). For the 12-week model, the c-statistic was 0.904 (95% CI 0.820 to 0.961), and the calibration slope was 0.601 (95% CI −0.0633 to 1.21). We used the models to predict the counterfactual outcomes of antipsychotic choice and 12-week weight change.

Our results show that it may be early rather than later weight change that causally mediates antipsychotic-induced weight gain at 1 year. They also demonstrate the potential for causal actionable prediction of counterfactuals for true precision medicine, although this is tempered by the feasibility scope of this study and small sample size. Our results are hypothesis-generating and not yet clinically deployable.

Treatment non-adherence is a well-established predictor of relapse in schizophrenia, yet its broader clinical impact remains unclear. This study examines the association between clinician-recorded treatment non-adherence and clinical outcomes during the first year following a schizophrenia diagnosis. Using a bespoke natural language processing algorithm applied to anonymised electronic health records, we classified the recorded treatment adherence status of 2667 patients. Multivariable and Poisson regression analyses were conducted to assess associations of recorded treatment non-adherence with clinical outcomes.

Compared with the remainder, those classified as non-adherent had greater increases in recorded symptoms and higher frequency and duration of in-patient admissions and crisis care episodes. They were also prescribed a greater number of different antipsychotics and developed a greater number of recorded physical health comorbidities.

Treatment non-adherence is associated with markedly poorer clinical outcomes, emphasising the importance of early identification and targeted interventions to support adherence.

In the UK, clozapine is the only licensed treatment for treatment-resistant schizophrenia (TRS). However, it is underused because initiation is often limited by the need for in-patient admission, which is costly and unattractive to patients. Community clozapine services may address this.

To describe a targeted out-patient clinic (Treating Unmet Needs in Psychiatry (TUNE-UP)) for TRS management and assess its impact on community clozapine initiation rates.

We reviewed clozapine titrations of patients under four community mental health teams from September 2021 to January 2025, recording whether titration occurred as in- or out-patient. The TUNE-UP clozapine clinic operated for 12 months (September 2023 to September 2024). Initiation rates during the TUNE-UP period were compared with those when the service was unavailable, using Poisson regression. Clinical outcomes were assessed using scales including the Positive and Negative Syndrome Scale (PANSS).

Fifty-one individuals commenced clozapine during the study period. There was a significant increase in the rates of community initiation in the TUNE-UP period (11.0 per year) compared with those outside of this period (1.71 per year; incidence risk ratio 6.42 [95% CI 2.04–20.2, P = 0.0015]). Patients seen by TUNE-UP showed significant improvements in PANSS (n = 6, median improvement 21.5 [95% CI 7.0–33.0], P = 0.03).

A specialist service was associated with a significant increase in community clozapine initiations. This approach offers a strategy to improve TRS treatment in the community.

Clozapine is licensed for treatment-resistant schizophrenia (TRS). Because of the risk of clozapine-induced agranulocytosis, its use requires regular haematological monitoring. Substantive evidence supports revisions of absolute neutrophil counts (ANCs) for clozapine discontinuation and ceasing of indefinite haematological monitoring.

To examine the cost-effectiveness and budget impact of different haematological monitoring schemes compared with the current UK monitoring practice for patients using clozapine.

We performed a cost-effectiveness and budget impact analysis from the healthcare system perspective over a 3-year period, comparing the current UK clozapine monitoring practice with extended haematological monitoring and a revision of ANC criteria. Costs and quality-adjusted life years (QALYs) were estimated using a semi-Markov model that followed a simulated cohort of 100 000 adults with TRS. Sensitivity analyses were conducted.

Extended haematological monitoring would lead to lower mean total costs per patient (6388.34 v. 5569.77 GBP) and not compromise quality of life (in QALYs 795.83 v. 795.79 days). A revision of ANC criteria for clozapine discontinuation would not substantially lower costs (6388.34 v. 6390 GBP), but lead to a slight increase in QALYs (795.83 v. 797.08 days), through patients benefitting from longer clozapine treatment. A combination of extended haematological monitoring and revision of ANC criteria would be the dominant strategy, which means that costs are lower (6388.34 v. 5548.50 GBP) and QALYs slightly increase (795.83 v. 797.03 days) compared with the current UK monitoring practice.

A revision of current UK clozapine monitoring practice would be beneficial from both a clinical and an economic perspective. Adjusting ANC criteria for clozapine cessation avoids unnecessary early discontinuation of clozapine treatment and has a positive impact on quality of life. An extension of monitoring intervals reduces costs borne by the healthcare system. Safety is not compromised by these changes.

Clozapine remains underused despite its unparalleled efficacy in treatment-refractory schizophrenia. One of the reasons for its underuse is the fear of severe neutropenia and its consequences.

To scrutinise the association between severe neutropenia and clozapine in a cohort of patients clinically diagnosed with clozapine-induced severe neutropenia.

We used data from the South London and Maudsley National Health Service Foundation Trust’s anonymised case register, known as the Clinical Record Interactive Search. We extracted details of cases where clozapine use was associated with two consecutive neutrophil counts below 1.5 × 109/L. A panel of clinicians independently assessed each case. Agreement was reached on which cases clozapine was the likely or definite cause of the severe neutropenia, the risk to life and whether or not rechallenge with clozapine could be attempted.

There were 96 cases where two consecutive neutrophil counts below 1.5 × 109/L were registered. The panel judged that 9 (9.4%) were definitely caused by clozapine and a further 11 (11.5%) were probably caused by clozapine. Overall, 18 (18.8%) patients should be precluded from ever receiving clozapine again according to the panel (all from the 20 cases where clozapine was the definite or probable cause). Of the remaining 76 cases of severe neutropenia the cause could not be determined in 60 cases, but in 11 cases the cause was benign ethnic neutropenia, in 2 others the cause was cancer chemotherapy, in 2 it was infections and in 1 it was laboratory error. In almost 80% of cases, clozapine was not the clear cause of the neutropenia observed.

The large majority of severe neutropenia episodes mandating cessation of clozapine may not be caused by clozapine. Threshold-based monitoring systems cause unnecessary stopping of clozapine because they lack the necessary specificity for clozapine-related blood disorders.