To examine the criteria utilised for detaining individuals under the Irish Mental Health Act 2001 (MHA 2001) and their association with clinical features.

Demographic and clinical data of 505 involuntary admissions under the MHA 2001 between 2013 and 2023 were attained. Data included criteria utilised for detention and renewal, sociodemographic and clinical features associated with these criteria, and the use of coercive practices, such as seclusion and restraint.

The majority of patients who were involuntarily admitted (61.4%), or had their admission order affirmed by tribunal (78.2%), were not judged to pose an immediate risk to themselves or others. Patients admitted under the “impaired judgement criterion” were less likely to be secluded (χ2 = 15.8, p < 0.001) or restrained (χ2 = 11.6, p < 0.01). Patients admitted under the “risk criterion” were younger (KW = 12.7, p = 0.02), and less likely to have a psychotic disorder (χ2 = 5.9, p = <0.001) or have a previous involuntary admission (χ2 = 7.7, p = 0.02). Patients who were subject to coercive care were younger (U = 12739, p < 0.001), more likely to be male (χ2 = 4.6, p = 0.03), and have prolonged involuntary admissions (U = 18412, p = 0.02).

Currently, the majority of the involuntary care provided for patients under the MHA 2001 is not related to the risk criterion of causing immediate and serious harm to themselves or others, but rather to the criterion of impaired judgement. Patients admitted under the risk criterion are more often subjected to restrictive practices, but are less likely to suffer from psychosis, than those receiving involuntary care due to their impaired judgement.

Electroconvulsive therapy (ECT) is a safe and effective treatment for several major psychiatric conditions, including treatment-resistant depression, mania, and schizophrenia; nevertheless, its use remains controversial. Despite its availability in some European countries, ECT is still rarely used in others. This study aims to investigate the experiences and attitudes of early career psychiatrists (ECPs) across Europe towards ECT and to examine how their exposure to ECT influences their perceptions.

In Europe, a cross-sectional survey was conducted among ECPs, including psychiatric trainees and recently fully qualified psychiatrists.

A total of 573 participants from 30 European countries were included in the study, of whom more than half (N = 312; 54.5%) received ECT training. Overall, ECPs had a positive attitude towards ECT, with the vast majority agreeing or strongly agreeing that ECT is an effective (N = 509; 88.8%) and safe (N = 464; 81.0%) treatment and disagreeing or strongly disagreeing that ECT was used as a form of control or punishment (N = 545; 95.1%). Those who had received ECT training during their psychiatry training were more likely to recommend ECT to their patients (p < 0.001, r = 0.34), and held more positive views on its safety (p < 0.001, r = 0.31) and effectiveness (p < 0.001, r = 0.33). Interest in further education about ECT was moderately high (modal rating on Likert scale: 4, agree), irrespective of prior training exposure.

ECT training is associated with more favorable perceptions of its safety and effectiveness among ECPs. There is a general willingness among ECPs to expand their knowledge and training on ECT, which could enhance patients’ access to this treatment.

Temperature increases in the context of climate change affect numerous mental health outcomes. One such relevant outcome is involuntary admissions as these often relate to severe (life)threatening psychiatric conditions. Due to a shortage of studies into this topic, relationships between mean ambient temperature and involuntary admissions have remained largely elusive.

To examine associations between involuntary admissions to psychiatric institutions and various meteorological variables.

Involuntary admissions data from 23 psychiatric institutions in the Netherlands were linked to meteorological data from their respective weather stations. Generalized additive models were used, integrating a restricted maximum likelihood method and thin plate regression splines to preserve generalizability and minimize the risk of overfitting. We thus conducted univariable, seasonally stratified, multivariable, and lagged analyses.

A total of 13,746 involuntary admissions were included over 21,549 days. In univariable and multivariable models, we found significant positive associations with involuntary admissions for ambient temperature and windspeed, with projected increases of up to 0.94% in involuntary admissions per degree Celsius temperature elevation. In the univariable analyses using all data, the strongest associations in terms of significance and explained variance were found for mean ambient temperature (p = 2.5 × 10−6, Variance Explained [r2] = 0.096%) and maximum ambient temperature (p = 8.65 × 10−4, r2 = 0.072%). We did not find evidence that the lagged associations explain the associations for ambient temperature better than the direct associations.

Mean ambient temperature is consistently but weakly associated with involuntary psychiatric admissions. Our findings set the stage for further epidemiological and mechanistic studies into this topic, as well as for modeling studies examining future involuntary psychiatric admissions.

Cardiovascular disease (CVD) is twice as prevalent among individuals with mental illness compared to the general population. Prevention strategies exist but require accurate risk prediction. This study aimed to develop and validate a machine learning model for predicting incident CVD among patients with mental illness using routine clinical data from electronic health records.

A cohort study was conducted using data from 74,880 patients with 1.6 million psychiatric service contacts in the Central Denmark Region from 2013 to 2021. Two machine learning models (XGBoost and regularised logistic regression) were trained on 85% of the data from six hospitals using 234 potential predictors. The best-performing model was externally validated on the remaining 15% of patients from another three hospitals. CVD was defined as myocardial infarction, stroke, or peripheral arterial disease.

The best-performing model (hyperparameter-tuned XGBoost) demonstrated acceptable discrimination, with an area under the receiver operating characteristic curve of 0.84 on the training set and 0.74 on the validation set. It identified high-risk individuals 2.5 years before CVD events. For the psychiatric service contacts in the top 5% of predicted risk, the positive predictive value was 5%, and the negative predictive value was 99%. The model issued at least one positive prediction for 39% of patients who developed CVD.

A machine learning model can accurately predict CVD risk among patients with mental illness using routinely collected electronic health record data. A decision support system building on this approach may aid primary CVD prevention in this high-risk population.

In order to minimise physical interaction during the COVID-19 pandemic, telepsychiatry became a key part of clinical practice for many psychiatrists.

This study involved an exploratory, cross-sectional, opt-in online survey circulated to non-consultant doctors in psychiatry working in Ireland. It assessed experience and attitudes in relation to telepsychiatry use.

The response rate was 11.6% (n = 61). Forty-eight individuals (78.6%) had delivered clinical care using telepsychiatry. Fifty-nine individuals (96.7%) were unfamiliar with telepsychiatry prior to the pandemic. Most respondents had not received specific training around use of a telepsychiatry platform (86.9%, n = 63) and were unaware of published guidelines around its optimal use (54.1%, n = 33). Respondents’ concerns included issues around connectivity, medico-legal uncertainty and clinical effectiveness.

Conclusions drawn are limited by the potential for selection bias in this study. Nonetheless the paper has highlighted important issues including the need for more research assessing telepsychiatry clinical and curricular experience. Additional curricular interventions during training could build skillset and confidence in telepsychiatry.

The prenatal and early-life periods pose a crucial neurodevelopmental window whereby disruptions to the intestinal microbiota and the developing brain may have adverse impacts. As antibiotics affect the human intestinal microbiome, it follows that early-life antibiotic exposure may be associated with later-life psychiatric or neurocognitive outcomes.

To explore the association between early-life (in utero and early childhood (age 0–2 years)) antibiotic exposure and the subsequent risk of psychiatric and neurocognitive outcomes.

A search was conducted using Medline, PsychINFO and Excerpta Medica databases on 20 November 2023. Risk of bias was assessed using the Newcastle-Ottawa scale, and certainty was assessed using the grading of recommendations, assessment, development and evaluation (GRADE) certainty assessment.

Thirty studies were included (n = 7 047 853 participants). Associations were observed between in utero antibiotic exposure and later development of autism spectrum disorder (ASD) (odds ratio 1.09, 95% CI: 1.02–1.16) and attention-deficit hyperactivity disorder (ADHD) (odds ratio 1.19, 95% CI: 1.11–1.27) and early-childhood exposure and later development of ASD (odds ratio 1.19, 95% CI: 1.01–1.40), ADHD (odds ratio 1.33, 95% CI: 1.20–1.48) and major depressive disorder (MDD) (odds ratio 1.29, 95% CI: 1.04–1.60). However, studies that used sibling control groups showed no significant association between early-life exposure and ASD or ADHD. No studies in MDD used sibling controls. Using the GRADE certainty assessment, all meta-analyses but one were rated very low certainty, largely owing to methodological and statistical heterogeneity.

While there was weak evidence for associations between antibiotic use in early-life and later neurodevelopmental outcomes, these were attenuated in sibling-controlled subgroup analyses. Thus, associations may be explained by genetic and familial confounding, and studies failing to utilise sibling-control groups must be interpreted with caution. PROSPERO ID: CRD42022304128