Objective: The ability to measure social health inequalities is a prerequisite to the implementation of local policies designed to reduce such inequalities. The absence of individual socioeconomic data in medical and administrative databases does not allow direct evaluation of those inequalities. The objective of this study is to propose a method of measurement of social health inequalities from national health insurance databases and a validated deprivation index.
Methods: 27 health care and prevention indicators were constructed to identify social health inequalities. Medical and administrative databases were cross-matched with the European Deprivation Index, completed by a potential spatial accessibility indicator in order to take into account the spatial distribution health care services.
Results: The study population comprised data devived from the three main health insurance schemes, and represents 89% of the population of the Midi-Pyrenees region. 98% were able to be geographically coded. The 27 indicators were therefore calculated on a total of 2,574,310 individuals, i.e. 87% of the regional population.
Conclusion: This study illustrates the value of using medical and administrative data to create databases allowing measurement of social health inequalities and their variations within a region. The proposed indicators could be used as decision-making tools for the selection of zones of intervention and to assess the impact of public policies designed to reduce social health inequalities.
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JMIR Form Res
December 2024
Department of Communication, Stanford University, Stanford, US.
Background: Contrary to popular concerns about the harmful effects of media use on mental health, research on this relationship is ambiguous, stalling advances in theory, interventions, and policy. Scientific explorations of the relationship between media and mental health have mostly found null or small associations, with the results often blamed on the use of cross-sectional study designs or imprecise measures of media use and mental health.
Objective: This exploratory empirical demonstration aimed to answer whether mental health effects are associated with media use experiences by (1) redirecting research investments to granular and intensive longitudinal recordings of digital experiences to build models of media use and mental health for single individuals over the course of one entire year, (2) using new metrics of fragmented media use to propose explanations of mental health effects that will advance person-specific theorizing in media psychology, and (3) identifying combinations of media behaviors and mental health symptoms that may be more useful for studying media effects than single measures of dosage and affect or assessments of clinical symptoms related to specific disorders.
Blood
January 2025
Fred Hutchinson Cancer Center, Seattle, Washington, United States.
Sclerosis is a highly morbid manifestation of chronic GVHD (cGVHD), associated with distressing symptoms and significant long-term disability. A patient-reported outcome measure (PRO) for cGVHD-associated sclerosis is essential to advance therapeutic trials. We aimed to develop a PRO for adults with cGVHD-associated sclerosis and evaluate and refine its content validity.
View Article and Find Full Text PDFBlood Adv
January 2025
Mayo Clinic, Rochester, Minnesota, United States.
Although social determinants of health (SDoH) investigations have shown limited analyses of socioeconomic and race-ethnic status on certain hematologic malignancies, the impact of factors beyond those across a fuller scope of hematologic cancers remains unknown. The Social Vulnerability Index (SVI), a tool for assessing varied US-census derived sociodemographic factors, allows the specific quantification of SDoH in dynamic, regional contexts for their associations with hematologic-malignancy inequities. To assess the summative influence of varied SDoH-factors on hematologic malignancy outcomes and discern which SDoH-factors contributed the largest associations towards disparities 796,005 adults with hematologic malignancies between 1975-2017 were identified for this retrospective cohort study.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Graduate School of Health Science and Technology, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea.
Background: Artificial intelligence (AI) social chatbots represent a major advancement in merging technology with mental health, offering benefits through natural and emotional communication. Unlike task-oriented chatbots, social chatbots build relationships and provide social support, which can positively impact mental health outcomes like loneliness and social anxiety. However, the specific effects and mechanisms through which these chatbots influence mental health remain underexplored.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Black Dog Institute, University of New South Wales, Sydney, Australia.
Background: With increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment methodologies is crucial for the success of such trials. Evidence on whether web-based recruitment methods are more effective than traditional methods such as newspapers, media, or flyers is inconsistent. Here we present insights from our experience recruiting tertiary education students for a digital mental health artificial intelligence-driven adaptive trial-Vibe Up.
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