Disaster risk reduction measures are now being developed based on social vulnerability. This study aimed to identify socially vulnerable areas to disasters in Razavi Khorasan Province, Iran.

The research utilized a mixed method approach conducted in 2 stages. First, a vulnerability index was created using 8 sub-indices, and the value of the index was calculated for each of the 91 rural districts in the study area. In the second stage, spatial analysis using Anselin’s Local Moran’s I was performed to identify the most vulnerable districts.

Results indicated that 40 of 91 districts, covering 49% of the total area, had high social vulnerability to disasters. Anselin’s Local Moran’s I analysis identified 2 high-high clusters consisting of 5 districts. The study also found that areas with higher social vulnerability were more susceptible to natural hazards such as floods and earthquakes.

Nearly half of the studied areas exhibited a high level of social vulnerability and were at risk of natural disasters. Implementing general measures to improve the socio-economic status of the population, such as increasing education and income levels, along with specific actions like assisting vulnerable populations in relocating to safer areas, can help mitigate disaster risks.

Violence and suicidality are common in forensic inpatients, most commonly with schizophrenia (SZ), personality disorder (PD), or comorbid SZ and PD (dual diagnosis, DD). There are no biological markers used in risk assessment tools. Lipids may provide a useful biomarker to aid violence prediction, but the roles of diagnosis and sex remain unclear. We therefore investigated lipids in adult forensic inpatients in association with the risk of violence and suicidality by primary diagnosis and sex.

Anonymized data were obtained for all eligible inpatients [n = 230; 114 SZ (75 males), 77 PD (40 males), 39 DD (20 males)] who had been admitted (2002–2021) to Elysium Healthcare (UK-wide) medium/low-secure facilities on lipids, age, sex, diagnosis, medication, risk of violence and suicidality, as well as days in seclusion and on high observations due to violence.

Mean total cholesterol (TC) in the patient sample (4.57, s.d. = 1.09) was lower, relative to the age- and sex-corrected UK population norm (4.91 mmol/l). PD (4.46 ± 1.08 mmol/l) and DD (4.24 ± 0.82 mmol/l), compared to SZ patients (4.77 ± 1.14 mmol/l), had significantly lower TC (not explained by statin use; no effect or interaction involving sex). Lower TC had significant though small associations with more days in seclusion or high observation levels due to violence across all patients, and marginally with suicidality in females.

A low TC-violence (towards others) link exists not only for SZ but also for PD and DD and for males and females, encouraging further enquiry into lipids as a biomarker to aid violence prediction in secure care.

Optimal radiotherapy technique selection for left-sided breast cancer remains challenging. This study compared volumetric-modulated arc therapy (VMAT), VMAT+IMRT (VMAT+IMRT) and IMRT+VMAT (IMRT+VMAT) using an innovative integrated scoring system and risk factor (RF) assessment.

Retrospectively analysed 41 patients with left-sided breast cancer. Treatment plans were evaluated using an integrated scoring system considering tumour coverage and organs at risk (OARs) sparing. RF analysis assessed potential adverse effects on the heart and lungs. Correlation analysis explored relationships between integrated scores and risk factors.

VMAT showed the best overall integrated score (1·0931 ± 0·1707), followed by IMRT+VMAT (1·2011 ± 0·2440) and VMAT+IMRT (1·2264 ± 0·2499). VMAT had the highest percentage of Excellent OAR plans (14·6%), while VMAT+IMRT and IMRT+VMAT showed better PTV coverage (53·7% and 51·2% Excellent, respectively). RF analysis revealed: VMAT (heart RF: 0·341, lung RF: 0·671), VMAT+IMRT (heart RF: 0·294, lung RF: 0·750) and IMRT+VMAT (heart RF: 0·533, lung RF: 0·546). Correlation analysis showed strong positive correlations between integrated scores and lung RF for VMAT (r = 0·671) and VMAT+IMRT (r = 0·750), with IMRT+VMAT showing moderate correlations for lung (r = 0·546) and heart (r = 0·533) RFs.

VMAT demonstrated the best balance between PTV coverage and OAR sparing, hybrid techniques improved target coverage but increased risk to OAR. The RF analysis highlighted varying impacts on heart and lung across techniques. This analysis provides valuable insights for technique selection, potentially improving treatment outcomes and reducing complications in left-sided breast cancer radiotherapy.

The threat of novel pathogens and natural hazards is increasing as global temperatures warm, leading to more frequent and severe occurrences of infectious disease outbreaks and major hurricanes. The COVID-19 pandemic amplified the need to examine how risk perceptions related to hurricane evacuations shift when vaccines become available. This study explores individuals’ expected evacuation plans during the early stages of COVID-19 vaccine availability.

In March 2021, an online survey was disseminated in Puerto Rico and the US Virgin Islands.

An overwhelming majority (72.6%) of respondents said that their vaccination status would not affect their hurricane evacuation intentions. The unvaccinated were significantly more likely to consider evacuating during a hurricane than the vaccinated. Even with vaccines available, respondents suggested they were less likely to evacuate to a shelter during the 2021 season than prior to the COVID-19 pandemic. Respondents generally believed that the risk of contracting COVID-19 at a shelter was greater than the risk of sheltering-in-place during a hurricane.

Government officials need to develop and communicate clear information regarding evacuation orders for municipalities that may be more impacted than others based on the trajectory of the storm, social determinants of health, and other factors like living in a flood zone.

To examine if the current taught undergraduate psychiatry syllabus at an Irish University relates to what doctors in psychiatry consider to be clinically relevant and important.

Doctors of different clinical grades were invited to rate their views on 216 items on a 10-point Likert scale ranging from ‘0 = not relevant’ to ‘10 = very relevant’. Participants were invited to comment on topics that should be excluded or included in a new syllabus. Thematic analysis was conducted on this free-text to identify particular themes.

The doctors surveyed rated that knowledge of diagnostic criteria was important for medical students. This knowledge attained high scores across all disorders with particularly high scores for a number of disorders including major depressive disorder (mean = 9.64 (SD = 0.86)), schizophrenia (mean = 9.55 (SD = 0.95)) and attention deficit hyperactivity disorder (Attention Deficit Hyperactivity Disorder (ADHD); mean = 9.26 (SD = 1.40)). Lower scores were noted for less frequently utilised management strategies (transcranial magnetic stimulation (mean = 4.97 (SD = 2.60)), an awareness of the difference in criteria for use disorder and dependence from psychoactive substances (mean = 5.56 (SD = 2.26)), and some theories pertaining to psychotherapy (i.e. Freud’s drive theory (mean = 4.59 (SD = 2.42)).

This study highlights the importance of an undergraduate programme that is broad based, practical and relevant to student’s future medical practice. An emphasis on diagnosis and management of major psychiatry disorders, and knowledge of the interface between mental health services, other medical specialities and support services was also deemed important.

Scalable assessment tools for precision psychiatry are of increasing clinical interest. One clinical risk assessment that might be improved by such approaches is assessment of violence perpetration risk. This is an important adverse outcome to reduce for some people presenting to services for first-episode psychosis. A prediction tool (Oxford Mental Illness and Violence (OxMIV)) has been externally validated in these services, but clinical acceptability and role need to be examined and developed.

This study aimed to understand clinical use of the OxMIV tool to support violence risk management in early intervention in psychosis services in terms of acceptability to clinicians, patients and carers, practical feasibility, perceived utility, impact and role.

A mixed methods approach integrated quantitative data on utility and patterns of use of the OxMIV tool over 12 months in two services with qualitative data from interviews of 20 clinicians and 12 patients and carers.

The OxMIV tool was used 141 times, mostly in new assessments. Required information was available, with only family history items scored unknown to any notable degree. The OxMIV tool was deemed helpful by clinicians in most cases, especially if there were previous risk concerns. It was acceptable practically, and broadly for the service, for which its concordance with clinical judgement was important. Patients and carers thought it could improve openness. There was some limited impact on plans for clinical support.

The OxMIV tool met an identified clinical need to support clinical assessment for violence risk. Linkage to intervention pathways is a research priority.

Venous thromboembolism (VTE) is a fatal condition affecting older people. This study aims to identify specific risk factors for VTE in older psychiatric in-patients within mental hospital settings. Using predefined search terms, we searched five databases to capture studies evaluating risk factors associated with the occurrence of deep vein thrombosis and pulmonary embolism in older psychiatric in-patients.

Thirteen studies were identified, and a narrative synthesis performed. Increasing age was a consistent risk factor for VTE. Diagnosis and psychotropic medication use were inconsistent. Depression, catatonia and use of restraint in people with dementia were associated with higher risks.

Older psychiatric in-patients differ from medical and surgical in-patients in their risk profiles. Screening tools used in general hospital patients are of limited use among older adults in psychiatric hospital settings. An exclusive screening tool to identify VTE risk factors in older psychiatric in-patients is needed.

Diabetes is a global health concern, and early identification of high-risk individuals is crucial for preventive interventions. Finnish Diabetes Risk Score (FINDRISC) is a widely accepted non-invasive tool that estimates the 10-year diabetes risk. This study aims to validate the FINDRISC in the Turkish population and develop a specific model using data from a nationwide cohort.

The study used data of 12249 participants from the Türkiye Chronic Diseases and Risk Factors Survey. Data included sociodemographic variables, lifestyle factors, and anthropometric measurements. Multivariable logistic regression was employed using FINDRISC variables to predict incident type 2 diabetes mellitus (T2DM). Two country-specific models, one incorporating the waist-to-hip ratio (WHR model) and the other waist circumference (WC model), were developed. The least absolute shrinkage and selection operator (LASSO) algorithm was used for variable selection in the final models, and model discrimination indexes were compared.

The optimal FINDRISC cut-off was 8.5, with an area under the curve (AUC) of 0.76, demonstrating good predictive performance in identifying T2DM cases in the Turkish population. Both WHR and WC models showed similar predictive accuracy (AUC: 0.77). Marital status and education were associated with increased diabetes risk in both country-specific models.

The study found that the FINDRISC tool is effective in predicting the risk of type 2 diabetes in the Turkish population. Models using WHR and WC showed similar predictive performance to FINDRISC. Sociodemographic factors may play a role in diabetes risk. These findings highlight the need to consider population-specific characteristics when evaluating diabetes risk.

Climate change is significantly altering our planet, with greenhouse gas emissions and environmental changes bringing us closer to critical tipping points. These changes are impacting species and ecosystems worldwide, leading to the urgent need for understanding and mitigating climate change risks. In this study, we examined global research on assessing climate change risks to species and ecosystems. We found that interest in this field has grown rapidly, with researchers identifying key factors such as species' vulnerability, adaptability, and exposure to environmental changes. Our work highlights the importance of developing better tools to predict risks and create effective protect strategies.

The rising concentration of greenhouse gases, coupled with environmental changes such as albedo shifts, is accelerating the approach to critical climate tipping points. These changes have triggered significant biological responses on a global scale, underscoring the urgent need for robust climate change risk assessments for species and ecosystems. We conducted a systematic literature review using the Web of Science database. Our bibliometric analysis shows an exponential growth in publications since 2000, with over 200 papers published annually since 2019. Our bibliometric analysis reveals that the number of studies has exponentially increased since 2000, with over 200 papers published annually since 2019. High-frequency keywords such as ‘impact’, ‘risk’, ‘vulnerability’, ‘response’, ‘adaptation’, and ‘prediction’ were prevalent, highlighting the growing importance of assessing climate change risks. We then identified five universally accepted concepts for assessing the climate change risk on species and ecosystems: exposure, sensitivity, adaptivity, vulnerability, and response. We provided an overview of the principles, applications, advantages, and limitations of climate change risk modeling approaches such as correlative approaches, mechanistic approaches, and hybrid approaches. Finally, we emphasize that the emerging trends of risk assessment of climate change, encompass leveraging the concept of telecoupling, harnessing the potential of geography, and developing early warning mechanisms.

Climate change risks to biodiversity and ecosystem: key insights, modeling approaches, and emerging strategies.