Workforce counts and early-readmission indicators often appear side by side in health-system dashboards, encouraging the assumption that more staff should accompany fewer returns to hospital. We examined whether annual variation in previous-year medical-nursing headcount density was associated with Italy’s official provider-side indicators of unplanned readmission within 30 days after eligible ordinary psychiatric discharges from public psychiatric wards and, secondarily, within 7 days.

Using national mental-health, hospital-discharge and population data, we assembled a retrospective 2015–2024 panel of 21 Italian territorial units (210 unit-years). Exposure was medical and nursing headcount at the end of the preceding year per 100,000 adults. We modelled 30-day readmission counts using Poisson pseudo-maximum likelihood (PPML) with an eligible-discharge offset and territorial-unit and year fixed effects. Primary inference used a restricted wild cluster score bootstrap with 9,999 Rademacher draws and 21 clusters. Secondary and sensitivity analyses were prespecified, source blanks were not imputed, and analytical materials and scripts are openly archived.

Outcome counts and eligible-discharge denominators were complete for all 210 observations; exposure was available for 205. The incidence rate ratio (IRR) per 10 additional medical-nursing staff per 100,000 adults was 1.006 (95% CI 0.934–1.034; p = 0.8095), compatible with relative changes from a 6.6% reduction to a 3.4% increase. Across linear PPML sensitivity analyses, IRRs ranged from 0.995 to 1.042, with all confidence intervals including 1. Across 31 leave-one-unit or leave-one-year-out re-estimates, IRRs ranged from 0.974 to 1.044, and every confidence interval included 1. The nonlinearity test gave p = 0.8572. The 7-day IRR was 1.032 (95% CI 0.929–1.075; p = 0.6743), while the weighted linear model estimated +0.215 percentage points (95% CI −1.159 to +0.704; p = 0.7203).

The data did not provide evidence of a detectable longitudinal ecological association between year-to-year variation in medical-nursing headcount density and the official 30-day readmission indicator. This does not imply that workforce is unimportant: headcount does not capture full-time-equivalent availability, deployment or transition processes, and the provider-side design cannot support patient-level or causal inference. Territorial policy should combine adequate resources with a whole-system view of their deployment, post-discharge organisation, and the social, economic and health context in which care is delivered.

Understanding service users’ knowledge of and attitudes towards the rapidly progressing field of mental health technology (MHT) is an important endeavour in clinical psychiatry.

To evaluate the current use of and attitudes towards MHT (mobile apps, online therapy and counselling, telehealth, web-based programmes, chatbots, social media), a 5-point Likert-scale survey was designed based on previous studies and distributed to attendees of an adult community mental health service in Ireland. Chi-square tests were used and corrected for multiple comparisons.

107 mental health service users completed the survey (58% female, aged 18–80). 86% of respondents owned a smartphone. 27.1% reported using a mental health application, while 33.6% expressed interest in using one in the future. 61.7% reported they had not used and were not interested in using AI for their mental health, and 51.4% indicated they would not feel comfortable using it. 46.8% were not comfortable with psychiatrists utilising AI in their care. The majority (86.9%) preferred face-to-face appointments, while 52.6% would consider using MHT while on a waiting list. Younger participants reported significantly greater comfort using mental health apps and higher self-rated knowledge of AI.

There were low levels of knowledge about and comfort using MHT, accompanied by concerns about confidentiality and privacy. Younger service users tended to be more comfortable with and knowledgeable about MHT. Despite the growing interest in digital approaches, there remains a clear preference for face-to-face appointments, underscoring the importance of addressing privacy and safety concerns, together with training and education.

Relatively little is known about mental healthcare-related harm, with patient safety incidents (PSIs) in community-based services particularly poorly understood. We aimed to characterize PSIs, contributory factors, and reporter-identified solutions within community-based mental health services for working-age adults.

We obtained data on PSIs reported within English services from the National Reporting and Learning System. Of retrieved reports, we sampled all incidents reportedly involving ‘Death’, ‘Severe harm’, or ‘Moderate harm’, and random samples of a proportion of ‘Low harm’ or ‘No harm’ incidents. PSIs and contributory factors were classified through qualitative content analysis using existing frameworks. Frequencies and proportions of incident types were computed, and reporter-identified solutions were inductively categorized.

Of 1825 sampled reports, 1443 were eligible and classified into nine categories. Harmful outcomes, wherein service influence was unclear, were widely observed, with self-harm the modal concern amongst ‘No harm’ (15.0%), ‘Low harm’ (62.8%), and ‘Moderate harm’ (37.6%) categories. Attempted suicides (51.7%) and suicides (52.1%) were the most frequently reported events under ‘Severe harm’ or ‘Death’ outcomes, respectively. Incidents common to most healthcare settings were identified (e.g. medication errors), alongside specialty-specific incidents (e.g. Mental Health Act administration errors). Contributory factors were wide-ranging, with situational failures (e.g. team function failures) and local working conditions (e.g. unmanageable workload) widely reported. Solution categories included service user-directed actions and policy introduction or reinforcement.

Study findings provide novel insights into incidents, contributory factors, and reported solutions within community-based mental healthcare. Targets for safety improvement are outlined, aimed at strengthening system-based prevention of incidents.

Hoarding disorder studies are primarily based on persons who seek treatment and demonstrate good insight. The aim of the present study is to evaluate whether there are differences between community and treatment-seeking samples of individuals with hoarding disorder (HD).

Fourteen people with HD from the community and twenty treatment-seeking people with HD were assessed by a battery of instruments to evaluate HD features and other associated characteristics.

Compared to the treatment-seeking sample, the HD community sample was older, had poorer insight, and had a lower prevalence of comorbid obsessive-compulsive disorder (OCD). There were no differences in gender, education, presence of psychiatric comorbidities, quality of life, and hoarding behavior characteristics between the samples. The final logistic regression model with the Dimensional Obsessive-Compulsive Scale (DOCS) as the single predictor of treatment-seeking status was statistically significant, indicating that it was able to distinguish between the two samples. The model explained between 20.7% and 27.9% of the variance of subjects, and correctly classified 67.6% of cases.

Our results indicate that there appear to be few differences between the treatment-seeking and community samples of individuals with HD. The presence of comorbid OCD in treatment-seeking groups seems to be more frequent than in HD community samples.

The COVID-19 pandemic has impacted communities worldwide. Behavioral health providers are at the forefront providing services and are thus vulnerable to psychological sequalae. This study hypothesizes that the fear of COVID-19 predicts depression and anxiety among these providers.

A questionnaire was delivered to community behavioral health providers to assess fear of COVID-19 using the Fear of COVID-19 Scale (FCV-19S). Anxiety and depression were assessed using Generalized Anxiety Disorder (GAD-2) scale and Patient Health Questionnaire (PHQ-2). Demographic data were analyzed using descriptive statistics, and the relationship between explanatory variables and outcomes was assessed using univariate generalized linear models and 1-way analysis of variance (ANOVA).

FCV-19S scores were significantly higher among persons who smoked (z = 2.4, P < 0.05) or had a predisposing health condition. The multivariate models showed significant association with fear of COVID-19 and having a predisposing health condition, belonging to an ethnic minority group, not been diagnosed positive, and having a high total anxiety score.

The study indicated that 50% of the behavioral health providers screened had poor mental health owing to multiple factors identified. Hence, it is essential to strengthen their support to better mitigate situations contributing to fear.

Patient safety problems stemming from healthcare represent a significant cause of morbidity and mortality globally. The evidence base on safety in mental healthcare, particularly regarding community-based mental health services, has long fallen behind that of physical healthcare, with fewer research publications, developed primarily in isolation from the wider improvement science discipline. This disconnect both yields, and stems from, conceptual and practical challenges which must be surmounted in order to advance the science and improvement of safety in mental healthcare.

The objectives of this research were to conduct a narrative review to provide an overview of conceptual issues in this area, their origins, and implications for patient safety science and clinical care. We also sought to identify approaches to overcoming these issues.

We examined theoretical and empirical evidence from the fields of patient safety, mental health, and improvement science to address this knowledge gap.

We identified challenges with defining safety in the context of community mental healthcare, ascertaining what constitutes a ‘preventable’ safety problem requiring intervention, and in finding relevant research evidence. The research indicated that risk management has taken precedence over proactive safety promotion in mental healthcare. This positions service users as the origin of safety risks, with iatrogenic harm and latent system hazards associated with mental healthcare widely overlooked.

We propose a broader conceptualisation of safety to advance the field and outline potential next steps for the integration and uptake of different sources of ‘safety intelligence’ within community mental health services.

NS is the director of London Safety and Training Solutions Ltd, which offers training in patient safety, implementation solutions and human factors to healthcare organisations and the pharmaceutical industry. The other authors have no competing interests.

The COVID-19 pandemic caused changes to how healthcare services are utilised and delivered.

We examine the impact of COVID-19 on the pattern of emergency patient presentations referred on to the community mental health team and the impact of utilising telemedicine on time to follow-up.

We retrospectively reviewed all clinical records of patients currently attending our service. We identified presentations to the emergency department (N=119) who were subsequently referred on for mental health follow-up.

Patients being referred to our team from emergency departments were significantly younger during, mean age 33.1 years (SD=12.3) compared to before the pandemic, mean age 40.0 years (SD=14.5), p=0.006 and a higher proportion were new patients during, 55.8%, compared to pre-pandemic period 33.3%, p=0.015. There was also a higher proportion of patients presenting with suicidal ideation and lower proportions of affective, psychosis and suicidal/self-injurious acts during the pandemic period compared to before, p=0.006. The ratio of female to male patients on the other hand were similar during both periods, p=0.853. There appeared to be no difference in median time to follow-up pre and during the pandemic (6.0 vs 5.5 days, p=0.995). Further analysis also found no significant impact on time to follow-up upon implementing telemedicine consultations, with median days to initial follow-up of 6 days pre-pandemic, 4.5 days during pandemic + prior to telemedicine and 6.5 days during pandemic + telemedicine, p=0.602.

This study provides preliminary data on the impact of COVID-19 on mental health emergency presentations and utilization of telemedicine on time to follow-up by CMHTs.

No significant relationships.

Disasters may have major impacts to mental health and to the utilization of mental health services (MHS). Moreover, these effects may be worsened by the preclusion of access to basic services following the event. The aim of this study is to evaluate the utilization of public MHS by the population that suffered water supply interruption following the Mariana Dam Failure in Brazil, 2015.

We conducted an Interrupted Time Series analyzing secondary health data from the municipalities that faced water supply interruption, comparing it to data from the other municipalities of Minas Gerais state.

We found a higher immediate (RR: 1.78; 95% CI: 1.25–2.53) and gradual (RR: 1.05; 95% CI: 1.03–1.06) change in the rate of mental health visits (MHV) in the affected population following the event, whereas there was an immediate fall (RR: 0.41; 95% CI: 0.29–0.59) followed by a higher gradual increase (RR: 1.04; 95% CI: 1.02–1.06) in the rate of hospital admissions (HA) in the affected population.

The results suggest that there was an increase in the utilization of public MHS by the population that suffered water supply interruption following the disaster.

To determine: whether young adults (aged 18–24) not in education, employment or training (NEET) have different psychological treatment outcomes to other young adults; any socio-demographic or treatment-related moderators of differential outcomes; and whether service-level changes are associated with better outcomes for those who are NEET.

A cohort was formed of 20 293 young adults treated with psychological therapies in eight Improving Access to Psychological Therapies services. Pre-treatment characteristics, outcomes, and moderators of differential outcomes were compared for those who were and were not NEET. Associations between outcomes and the following were assessed for those that were NEET: missing fewer sessions, attending more sessions, having a recorded diagnosis, and waiting fewer days between referral and starting treatment.

Those who were NEET had worse outcomes: odds ratio (OR) [95% confidence interval (CI)] for reliable recovery = 0.68 (0.63–0.74), for deterioration = 1.41 (1.25–1.60), and for attrition = 1.31 (1.19–1.43). Ethnic minority participants that were NEET had better outcomes than those that were White and NEET. Living in deprived areas was associated with worse outcomes. The intensity of treatment (high or low) did not moderate outcomes, but having more sessions was associated with improved outcomes for those that were NEET: odds (per one-session increase) of reliable recovery = 1.10 (1.08–1.12), deterioration = 0.94 (0.91–0.98), and attrition = 0.68 (0.66–0.71).

Earlier treatment, supporting those that are NEET to attend sessions, and in particular, offering them more sessions before ending treatment might be effective in improving clinical outcomes. Additional support when working with White young adults that are NEET and those in more deprived areas may also be important.

This study evaluated the relationships between the occurrence of recent and recurring natural disasters on the incidence of acute and chronic health outcomes at the census tract level in 500 cities across the United States between 2001 and 2015.

Using the Centers for Disease Control and Prevention (CDC) 500 cities data set, the CDC Social Vulnerability Index, and the US Small Business Administration (SBA) Disaster Loan Database, we modeled the incidence of self-reported, poor mental and physical health, or a clinical diagnosis of high blood pressure or asthma in census tracts (N = 27 204 tracts in 500 cities) that had experienced recent or recurring natural disasters while controlling for social and environmental risk factors.

Communities that experienced a natural disaster in the previous 5 years compared to those that had not had a higher incidence of poor mental health (RR: 1.02, 95% CI: 1.01-1.02), poor physical health (RR: 1.03, 95% CI: 1.02-1.04), high blood pressure (RR: 1.04, 95% CI: 1.02-1.05), and asthma (RR: 1.01, 95% CI: 1.01-1.02). The incidence of these poor health outcomes increased 1-2% with each additional year that a community experienced a disaster.

Prevention and preparedness plans that work to build resilience in communities before disasters should focus on closing the gap in environmental and social determinants that have been linked with disproportionate health burdens and slow recovery post-disaster.