Abstract Aims Depression and post-traumatic stress disorder (PTSD) are highly prevalent and frequently co-occur in conflict-affected populations, yet the complex relationships among their symptoms remain poorly understood. This study applied psychological network analysis and Bayesian network modelling to examine symptom associations and exploratory directional dependencies among participants living in Cox’s Bazar and neighbouring Bandarban, Bangladesh. Methods Baseline data were obtained from 9,397 participants, including forcibly displaced Rohingya refugees and host-community members. Depression symptoms (Patient Health Questionnaire-9) and PTSD symptoms (Harvard Trauma Questionnaire-16) were analysed using regularized partial correlation networks and directed acyclic graphs. Symptom centrality, bridge centrality, predictability and network stability were assessed, alongside sensitivity analyses by settlement status and sex. Results Distinct yet interconnected clusters of depression and PTSD symptoms emerged. Guilt, anhedonia, recurrent traumatic thoughts, emotional detachment, hopelessness about the future and rumination emerged as the most central symptoms. Bridge-strength analyses identified guilt and physical health problems as the most prominent bridge symptoms linking depression and PTSD symptom communities. Bayesian network analysis identified several highly stable exploratory directional dependencies involving anhedonia, guilt, rumination, recurrent traumatic thoughts and emotional detachment. The network demonstrated excellent stability (correlation stability = 0.75), while symptom-level classification accuracy ranged from 0.542 to 0.791. Sensitivity analyses indicated that network structure differed across settlement settings, whereas no significant difference in overall network structure was detected between sexes. Conclusions These findings provide a nuanced understanding of symptom interrelationships between depression and PTSD in a major humanitarian setting. Symptoms such as guilt, rumination, recurrent traumatic thoughts and physical health problems warrant further interventions as potential intervention targets, potentially informing more focused and culturally sensitive mental health strategies for conflict-affected populations.
Abstract Aim Although asthma is strongly associated with elevated psychiatric morbidity, the extent to which neighbourhood deprivation is associated with psychiatric disorder risk in this population remains insufficiently understood. This study aims to examine whether neighbourhood deprivation is associated with the incidence of psychiatric disorders among adults with asthma, and whether these associations vary by sex and psychiatric disorder subtype. Methods Using nationwide Swedish registers (1997–2018), we identified 393,061 adults aged 25–64 years with asthma and followed them for incident psychiatric disorders. Neighbourhood deprivation was assessed at baseline and categorized into low, moderate and high levels. Cox proportional hazards models estimated hazard ratios (HRs) with 95% confidence intervals (CIs) and were stratified by sex and psychiatric disorder subtype. Results During the follow-up period, 207,900 individuals (68,327 men and 139,573 women) developed psychiatric disorders. The incidence of psychiatric disorders increased progressively with higher levels of neighbourhood deprivation. In the fully adjusted models, compared with those living in low-deprivation areas, men in moderate and high deprivation areas had 11% (HR, 1.11; 95% CI, 1.08–1.13) and 31% (HR, 1.31; 95% CI, 1.27–1.35) higher hazards, respectively, while women had 10% (HR, 1.10; 95% CI, 1.08–1.11) and 22% (HR, 1.22; 95% CI, 1.19–1.25) higher hazards. Disorder-specific analyses revealed particularly strong associations for developmental delay (HR = 2.82), pervasive developmental disorder (HR = 1.96), schizophrenia (HR = 1.79) and substance use disorder (HR = 1.71). Women consistently showed higher cumulative incidence than men across all deprivation levels. Conclusions Neighbourhood deprivation was associated with higher psychiatric morbidity among individuals with asthma. These findings suggest the importance of integrating respiratory and mental healthcare with structural interventions targeting socio-economic disadvantage to help reduce inequalities in psychiatric outcomes.
Abstract Aims 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. Methods 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. Results 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). Conclusions 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.
Abstract Aims Post-traumatic stress symptoms (PTSS) are a substantial yet underrecognised mental health concern in oncology. Large-scale epidemiological data across diverse cancer types are scarce. This study aimed to estimate the prevalence of post-traumatic stress disorder (PTSD) and to identify socio-demographic and psychosocial correlates in a large, unselected outpatient cohort. Methods In this cross-sectional study, 4,103 adult outpatients with solid tumours or haematologic malignancies were screened during routine care using the PTSS-8-Cancer scale. Socio-demographic, clinical and psychosocial variables were collected concurrently. Associations between screening results and patient characteristics were examined using correlational and chi-square analyses. Results Overall, 32.5% screened positive for probable PTSD. Prevalence was highest in breast cancer (39.7%), female genital cancers (37.2%) and head and neck cancers (36.1%). A positive screening for PTSD was more common among women, younger patients, those with lower income, without a partner and with a history of psychiatric illness. While these associations were statistically significant, effect sizes were generally small. Conclusions One in three cancer outpatients experience substantial PTSS, with elevated prevalence in certain diagnostic groups. Small effect sizes for socio-demographic predictors underscore that psychological distress is broadly distributed. Findings support universal psychosocial screening and integration of trauma-informed care into oncology services to address a significant, population-level mental health burden.
