Objective: Disasters by definition overwhelm the resources of a hospital and may require a response from a range of practitioners. Disaster training is part of emergency medicine (EM) resident curricula, but less emphasized in other training programs. This study aimed to compare disaster educational training and confidence levels among resident trainees from multiple specialties.
Design: A structured questionnaire assessed graduate medical training in disaster education and self-perceived confidence in disaster situations. Cross-sectional sampling of resident trainees from the departments of surgery, pediatrics, internal medicine, and EM was performed.
Setting: The study took place at a large urban academic medical center during March 2013.
Participants: Among 331 available residents, a convenience sample of 157 (47.4 percent) was obtained.
Main Outcome Measures: Outcomes investigated include resident confidence in various disaster scenarios, volume of disaster training currently received, and preferred education modality.
Results: EM trainees reported 7.3 hours of disaster instruction compared to 1.3 hours in non-EM trainees (p < 0.001). EM residents reported significantly more confidence in disaster scenarios compared to non-EM residents except for overall low confidence levels for mega mass casualty incidents. The preferred education modality for both EM and non-EM residents was simulation exercises followed by lecture.
Conclusions: This study demonstrated relatively lower confidence among non-EM residents in disaster response as well as lower number of disaster education time. These data report a learner preference for simulation training.
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http://dx.doi.org/10.5055/ajdm.2017.0253 | DOI Listing |
BMC Med Inform Decis Mak
January 2025
Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, 2007, Australia.
This study aimed to compare and evaluate the prediction accuracy and risk of bias (ROB) of post-traumatic stress disorder (PTSD) predictive models. We conducted a systematic review and random-effect meta-analysis summarizing predictive model development and validation studies using machine learning in diverse samples to predict PTSD. Model performances were pooled using the area under the curve (AUC) with a 95% confidence interval (CI).
View Article and Find Full Text PDFFuture military conflicts are likely to involve peer or near-peer adversaries in large-scale combat operations, leading to casualty rates not seen since World War II. Casualty volume, combined with anticipated disruptions in medical evacuation, will create resource-limited environments that challenge medical responders to make complex, repetitive triage decisions. Similarly, pandemics, mass casualty incidents, and natural disasters strain civilian health care providers, increasing their risk for exhaustion, burnout, and moral injury.
View Article and Find Full Text PDFJ Trauma Stress
January 2025
Phoenix Australia-Centre for Posttraumatic Mental Health, Department of Psychiatry, University of Melbourne, Carlton, Australia.
Individuals exposed to disasters are at high risk of developing mental health conditions, yet the availability of mental health practitioners is often limited. The aim of this scoping review was to examine the quality of the evidence for psychosocial interventions that can be delivered by non-mental health workers in the context of disasters. Searches were performed in PsycInfo, EMBASE, Family & Society Studies Worldwide, CINAHL, Global Health, PubMed, and SCOPUS, from inception through to November 2024, to identify studies of relevance.
View Article and Find Full Text PDFSci Data
January 2025
Department of Psychology, Faculty of Arts, Masaryk University, Brno, Czech Republic.
Empirical data on human evacuation behavior are invaluable for adjusting and training computational algorithms that simulate evacuation processes, including agent-based modeling. We provide a dataset on human decision-making during evacuations from virtual buildings, captured using experimental methods that controlled specific building layout parameters. An online experiment assigned participants a random subset of tasks featuring T-intersections.
View Article and Find Full Text PDFSleep Med
January 2025
Institute of Disaster Management and Vulnerability Studies, University of Dhaka, Dhaka, Bangladesh; Department of Human Development and Family Sciences, Texas Tech University, Lubbock, TX, United States. Electronic address:
Objectives: This study aimed to assess the prevalence and correlates of anxiety-induced sleep disturbance (AISD) in Paraguayan adolescents through sex-stratified analysis.
Methods: This study used the cross-sectional data from Paraguay's 2017 Global School-Based Student Health Survey (GSHS). A total of 3149 in-school adolescents (12-17 years; 51.
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