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.

An improved understanding of the factors associated with self-harm in young people who die by suicide can inform suicide prevention measures.

To describe sociodemographic and clinical characteristics and service utilisation related to self-harm in a national sample of young people who died by suicide.

We carried out a descriptive study of self-harm in a national consecutive case series (N = 544) of 10- to 19-year-olds who died by suicide over 3 years (2014–2016) in the UK as identified from national mortality data. Information was collected from coroner inquest hearings, child death investigations, criminal justice system and National Health Service serious incident reports.

Almost half (49%) of these young people had harmed themselves at some point in their lives, a quarter (26%) in the 3 months before death. Girls were twice as likely as boys to have recent self-harm (40 v. 20%; P < 0.001). Compared to the no self-harm group, young people with recent self-harm were more likely to have a mental illness diagnosis (63 v. 23%; P < 0.001); misused alcohol (19 v. 9%; P = 0.07); experienced physical, sexual or emotional abuse (17 v. 3%; P < 0.01); and recent life adversity (95 v. 75%; P < 0.001). Furthermore, they were more likely to be in contact with mental health services (60 v. 10%), or emergency departments or general physicians for a mental health condition (52 v. 10%) in the 3 months before death.

Presentation to services in young people who self-harm is an important opportunity to intervene through comprehensive psychosocial assessment and treatment of underlying conditions.

Early worsening of plasma lipid levels (EWL; ≥5% change after 1 month) induced by at-risk psychotropic treatments predicts considerable exacerbation of plasma lipid levels and/or dyslipidaemia development in the longer term.

We aimed to determine which clinical and genetic risk factors could predict EWL.

Predictive values of baseline clinical characteristics and dyslipidaemia-associated single nucleotide polymorphisms (SNPs) on EWL were evaluated in a discovery sample (n = 177) and replicated in two samples from the same cohort (PsyMetab; n1 = 176; n2 = 86).

Low baseline levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C) and triglycerides, and high baseline levels of high-density lipoprotein cholesterol (HDL-C), were risk factors for early increase in total cholesterol (P = 0.002), LDL-C (P = 0.02) and triglycerides (P = 0.0006), and early decrease in HDL-C (P = 0.04). Adding genetic parameters (n = 17, 18, 19 and 16 SNPs for total cholesterol, LDL-C, HDL-C and triglycerides, respectively) improved areas under the curve for early worsening of total cholesterol (from 0.66 to 0.91), LDL-C (from 0.62 to 0.87), triglycerides (from 0.73 to 0.92) and HDL-C (from 0.69 to 0.89) (P ≤ 0.00003 in discovery sample). The additive value of genetics to predict early worsening of LDL-C levels was confirmed in two replication samples (P ≤ 0.004). In the combined sample (n ≥ 203), adding genetics improved the prediction of new-onset dyslipidaemia for total cholesterol, LDL-C and HDL-C (P ≤ 0.04).

Clinical and genetic factors contributed to the prediction of EWL and new-onset dyslipidaemia in three samples of patients who started at-risk psychotropic treatments. Future larger studies should be conducted to refine SNP estimates to be integrated into clinically applicable predictive models.