The rapid pace of genomic discovery has raised public expectation and concerns about the utility of new discoveries and their potential to exacerbate health disparities. Improving literacy concerning gene and environmental (GxE) contributors to disease is needed to avoid commonly observed deterministic misconceptions about genomics. Mental models approaches that incorporate community engagement processes could be used to inform GxE literacy-building interventions. We used a mental models approach to describe and systematically compare expert and lay understanding of GxE interactions, using the example of podoconiosis, a non-infectious lymphedema endemic in highland Ethiopia. Methods included: (1) specifying elicitation questions for a literature review, (2) eliciting an expert model, (3) eliciting a lay model, and (4) comparing the two models. We used a coding scheme to identify lay participants' knowledge gaps, misunderstandings and extra knowledge relative to the expert standard. Results indicated that lay participants' viewed poverty as an important susceptibility factor and considered heredity and contagion to have a joint causal influence. Experts did not endorse either of these viewpoints. Conventional expert-based interventions aimed to correct misconceptions about behaviors important for prevention may be stymied by lay views that social environmental factors have more important influences on health outcomes. GxE literacy interventions that consider multiple levels of influence including social determinants of health and personal resilience to augment health education strategies are needed in diverse settings. Novel communication approaches will be needed to help target audiences disentangle long-held conceptions of heredity and contagion.
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http://dx.doi.org/10.1080/09581596.2017.1409885 | DOI Listing |
BMC Med Inform Decis Mak
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Department of Pediatrics, School of Medicine, Ekbatan Hospital, Hamadan University of Medical Sciences, Hamadan, Iran.
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Department of Epidemiology and Health Statistics and West China Institute of Preventive and Medical Integration for Major Diseases, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
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BMC Psychiatry
January 2025
Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Background: Mental disorders are increasingly prevalent, leading to increased medical expenditures. To refine the reimbursement of medical costs for inpatients with mental disorders by health insurance, an accurate prediction model is essential. Per-diem payment is a common internationally implemented payment method for medical insurance of inpatients with mental disorders, necessitating the exploration of advanced machine learning methods for predicting the average daily hospitalization costs (ADHC) based on the characteristics of inpatients with mental disorders.
View Article and Find Full Text PDFPrev Sci
January 2025
School of Behavioral Health Sciences, The University of Texas Health Science Center at Houston, 7000 Fannin St, Houston, TX, 77030, USA.
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View Article and Find Full Text PDFSci Rep
January 2025
Center on Translational Neuroscience, Institute of National Security, Minzu University of China, Beijing, China.
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