Objective: To determine factors associated with increased response readiness to CBRN threats of paramedics in Ontario, Canada.
Methods: An internet-based survey was distributed via email and delivered at the start of each shift presentation during October, 2019. The target population was active-duty paramedics in the Ontario region of Canada. The survey was comprised of 6 sections pertaining to demographics, attitudinal components of risk perception, self-efficacy, deployment concerns, and resilience. Survey mean, univariate, and multivariate regression analyses were used to find the individual effect of each variable.
Results: The univariate analysis indicated that higher response readiness was associated with additional training, education, CBRN, and family concerns, and incident experience. However, some variables were non-significant in the multivariate analysis. Increased response readiness was associated with CBRN concerns and training.
Conclusion: CBRN concerns and focused training regarding terrorism were both associated with increased response readiness. The information from the study can be used to build upon existing knowledge and support paramedics though training and preparation for CBRN specific disasters. The findings may also be used to improve current competency-based frameworks focused on response readiness.
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http://dx.doi.org/10.1017/dmp.2022.184 | DOI Listing |
Int J Health Plann Manage
January 2025
SMRI, The University of Sydney, Sydney, Australia.
This article serves as a guide to the Tobacco-Free Generation policy (TFG) for policy-makers, drawing on experiences of negotiations regarding TFG in a wide number of jurisdictions. It explains the underlying concept: the highly addictive nature of nicotine prompts policy focus on preventing initial use by forbidding sales to those born after a prescribed cut-off birthdate, while resisting prohibition for those in older cohorts who may already be nicotine-dependent. The policy signals that there is no safe age for tobacco products.
View Article and Find Full Text PDFBMJ Open
January 2025
Deep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg
Objectives: Diabetes distress can negatively affect the well-being of individuals with type 1 diabetes (T1D). Voice-based (VB) technology can be used to develop inexpensive and ecological tools for managing diabetes distress. This study explored the competencies to engage with digital health services, needs and preferences of individuals with T1D or caring for a child with this condition regarding VB technology to inform the tailoring of a co-designed tool for supporting diabetes distress management.
View Article and Find Full Text PDFDisaster Med Public Health Prep
January 2025
Kentucky Department for Public Health, Division of Epidemiology and Health Planning, Frankfort, KY.
Objectives: On July 28, 2022, eastern Kentucky experienced the state's deadliest flood in recorded history. In response to ongoing mental health concerns from community members who survived the flood, local health department directors in affected communities requested technical assistance from the Kentucky Department for Public Health and the Centers for Disease Control and Prevention.
Methods: Two simultaneous Community Assessments for Public Health Emergency Response (CASPERs) were conducted 6 weeks after the flood.
Nat Commun
January 2025
Grid Therapeutics, Durham, NC, USA.
GT103 is a first-in-class, fully human, IgG3 monoclonal antibody targeting complement factor H that kills tumor cells and promotes anti-cancer immunity in preclinical models. We conducted a first-in-human phase 1b study dose escalation trial of GT103 in refractory non-small cell lung cancer to assess the safety of GT103 (NCT04314089). Dose escalation was performed using a "3 + 3" schema with primary objectives of determining safety, tolerability, PK profile and maximum tolerated dose (MTD) of GT103.
View Article and Find Full Text PDFNat Med
January 2025
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
The integration of large language models (LLMs) into clinical diagnostics has the potential to transform doctor-patient interactions. However, the readiness of these models for real-world clinical application remains inadequately tested. This paper introduces the Conversational Reasoning Assessment Framework for Testing in Medicine (CRAFT-MD) approach for evaluating clinical LLMs.
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