Antidepressants are pivotal in treating major depressive disorder and other psychiatric conditions. However, despite their widespread use, evidence regarding the serious adverse effects of prolonged antidepressant use and withdrawal in complex older-adult populations remains limited.

We aimed to investigate the association between phases of antidepressant treatment with emergency hospital admission and hospital admissions related to adverse drug reactions in older adults with polypharmacy in English primary care.

We conducted a case–control study using linked primary and secondary care electronic health record data from the Clinical Practice Research Databank GOLD and Aurum. We included individuals aged 65–100 years with polypharmacy (i.e. those who were prescribed five or more medicines). We used conditional logistic regression to investigate the associations between the phases of antidepressant treatment and hospital admission risks.

We found 626 199 emergency hospital admission cases and matched with 3 639 740 controls. The initiation phase of antidepressants was associated with the greatest increase in the risk of emergency hospital admission (adjusted odds ratio 2.30, 95% CI 2.23–2.38), followed by short treatment gap or early discontinuation after short-term use (adjusted odds ratio 1.41, 95% CI 1.37–1.45). We found that patients had a higher risk of serotonin-related symptoms, falls and trauma, and cardiovascular events during antidepressant use phases, and the risks tend to decrease in past exposure phases for most conditions.

Individuals who are on the initiation and short treatment gap or early discontinuation after short-term use of antidepressant treatment are associated with a higher risk of hospital admission. This study highlights the need for vigilant monitoring of antidepressant initiation and withdrawal in older-adult polypharmacy patients.

Information about a treatment’s benefits and harms available to a patient often relies on text. However, for many medical conditions, patients must trade off benefits and harms across multiple competing treatments. It remains unknown how to appropriately communicate information on benefits and harms to patients.

We compared three communication tools using textual information (Cochrane summary of findings table) or increasing combinations of textual and graphical information (Kilim and Vitruvian plots, respectively) to convey the available evidence.

Communication of Benefit–Risk Information, an online randomised controlled trial, is a three-group, parallel, open-label, automated, randomised controlled trial (no. NCT05917639). We recruited participants aged between 18 and 65 years from the general population. Participants were randomly allocated (1:1:1) to one of the three communication tools providing information on competing fictional treatments for social anxiety, and were asked to choose one based on externally provided preferences. The primary outcome was the perceived level of decisional conflict when selecting a treatment (decisional conflict scale (DCS): 0 = best, 100 = worst). Because this was an all-or-nothing, single-visit trial, only those participants providing data contributed to the primary analyses (modified intention to treat).

We recruited 2178 adults between 1 June and 27 November 2023. Vitruvian and Kilim plots outperformed the Cochrane summary of findings table on the primary outcome (adjusted mean difference −10.9, 95% CI −13.5 to −8.2, P < 0.0001 and −9.7, 95% CI −12.4 to −7.1, P < 0.0001), respectively). Results varied by participants’ literacy and numeracy skills, lived experience of the condition of interest, ethnic group, gender assigned at birth and age.

Combining graphical and textual information, as opposed to text only, improved communication and reduced decisional conflict when choosing across multiple competing medical interventions. Organisations involved in disseminating scientific evidence should consider endorsing a combined graphical and textual approach and adopting more intuitive and accessible communication methods. We identified several prognostic factors that should inform the development of future patient decision aids and communication of scientific findings.

NCT05917639.

Identifying patients with first-episode psychosis (FEP) who are unlikely to achieve early clinical recovery (ECR) is critical for personalised intervention and resource allocation. ECR – defined as the concurrent achievement of symptomatic and functional remission – represents a clinically meaningful outcome that captures both illness control and functional reintegration.

To develop and externally validate prediction models for ECR using clinical, cognitive and genetic data.

We analysed two large, independent Spanish cohorts: the primeros episodios psicóticos cohort (N = 335), for model development and internal validation, and the Programa Asistencial a las Fases Iniciales de Psicosis cohort (N = 668), for external validation. Forty-seven baseline clinical and cognitive variables and 87 polygenic risk scores (PRSs) were examined. Predictors were selected using penalised logistic regression. Logistic regression and three machine learning algorithms were compared for discrimination, calibration and clinical utility.

The best-performing model was a logistic regression using six routinely collected clinical and cognitive predictors (duration of untreated psychosis, days of treated psychosis, baseline functioning, insight, executive function and cognitive reserve), with an optimism-corrected area under the receiver operating characteristic curve of 0.73 in development and 0.63 in external validation. PRS models showed limited external generalisability and did not improve prediction. Machine learning algorithms offered no advantage over regression models.

A simple, interpretable logistic regression model based on routine clinical and cognitive variables can predict early recovery in FEP with acceptable generalisability. These findings support the use of transparent, clinically grounded models in early psychosis care and highlight the current limitations of genetic predictors for individualised treatment.

Mentalising skills may be conceptualised as composed by both personal and interpersonal competencies, in turn shaped by early adverse experiences and coping strategies. Although cross-sectional observations described a role for mentalising skills in burnout development, large-scale longitudinal studies on the topic remain limited, especially in relation to psychiatry training.

The primary aim was to investigate protective and risk factors for higher burnout scores across time. Secondary aims included testing whether psychiatry exhibited different burnout scores across time in comparison to other medical residents.

A cohort of 1803 medical residents (1131 psychiatry residents) was assessed for mentalising skills, conceptualised as composed of emotional regulation (Difficulties in Emotion Regulation Scale), interpersonal competencies (Interpersonal Competence Questionnaire), coping strategies (Coping Orientation to Problems Experienced) and burnout dimensions (Maslach Burnout Inventory). One-year follow-up was available for 520 psychiatry residents (73.03% response rate) and 234 other medical residents (35.94% response rate). Longitudinal mixed models and bivariate latent change models were employed.

Across all residents, greater levels of burnout were associated with higher scores in insecure attachment, emotional dysregulation and maladaptive coping, as well as lower scores in interpersonal skills. Attending at least one supervision per month was associated with lower burnout scores across time. According to a bivariate latent change model, emotional regulation improvements through years were associated with lower burnout scores across time. In psychiatry residents, lower burnout scores across time were observed as compared to other medical residents. Psychiatry residents benefited from a higher protective effect of interpersonal competencies (group by moderator by time interaction) and coping strategies against burnout.

Mentalising skills may mitigate burnout development. Training in psychiatry emerged as a potential mitigating factor against burnout increases. Structured supervisions may foster professional development and emotional resilience.

Females are less likely than males to be diagnosed with attention–deficit hyperactivity disorder (ADHD). When diagnosed, females are older than males.

In this study, we examined the childhood antecedents of later ADHD diagnosis and its impact on adolescent/emerging adult outcomes, with a focus on females.

In this cohort study, we used data from a Welsh nation-wide electronic cohort of 13 593 individuals (n = 2680 (19.7%) females) diagnosed with ADHD and 578 793 individuals (n = 286 734 (49.5%) females) without ADHD. We compared females with later diagnoses (ages 12–25) to those with earlier, timely diagnoses (ages 5–11) and no diagnosis, in terms of childhood (ages 5–11) antecedents and adolescent/adult (ages 12–25) outcomes. We also tested for sex differences.

Although females with earlier ADHD diagnosis showed more health and educational difficulties in childhood than those with later diagnosed ADHD (odds ratios ranged from 0.18 to 0.92), there was clear evidence of these difficulties in females with later diagnosed ADHD, compared with females without ADHD (odds ratios: 1.07–9.02). In adolescence/early adulthood, females with later diagnosed ADHD used more healthcare services and had worse mental health, educational and socioeconomic outcomes than females diagnosed earlier (odds ratios: 1.39–4.96) and those without ADHD (odds ratios: 1.54–23.98). Many of these outcomes were exacerbated in females compared with males.

The results demonstrate that later ADHD diagnosis is associated with significant negative outcomes by adolescence and disproportionately disadvantages females. Despite later diagnosis, there was clear evidence of childhood mental health and educational difficulties when compared with females without ADHD. Therefore, timely childhood ADHD diagnosis may help to mitigate later risks, especially for females.

Depression is the most common mental illness globally and is a leading cause of years lived with disability. The manifestation of depressive symptoms can vary among ethnic groups. Individuals in South Asian countries experience higher levels of somatic symptoms than those in other regions, but it is not known whether this pattern extends to the South Asian diaspora.

To provide a qualitative synthesis of what is known regarding depression symptoms among the South Asian diaspora in English-speaking countries.

A systematic scoping review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews guidelines, based on a pre-registered protocol (doi.org/10.17605/OSF.IO/5E6ZK). The review included qualitative, quantitative and mixed-methods primary research, reporting depression symptoms based on samples of adults of the South Asian diaspora in English-speaking countries with substantial South Asian populations. Qualitative content analysis was used to identify widely reported symptoms of depression among the South Asian diaspora.

Commonly reported symptoms included physical pain, heart-related symptoms and repetitive negative thinking, none of which are included in ICD-11 diagnostic criteria for depressive disorders. Sleep-related disturbances are also widely reported in research into experiences of depression among the South Asian diaspora.

Current diagnostic criteria for depression might not capture symptoms of some South Asian individuals, which may cause missed opportunities for intervention.

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.