Predicting health literacy in Brazil: a machine learning approach.
Health literacy is essential for promoting well-being and the ability to make informed decisions. We investigated the level of health literacy in Brazil and identified the predictive factors that influence it. Our data contribute to the international context, with a focus on countries in the Global...
| Publicado en: | Health Promotion International Vol. 40; no. 3; pp. 1 - 11 |
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| Autores principales: | , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Jun2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=186811111&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 186811111 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09574824 F9Y jtl: Health Promotion International issn: 09574824 maglogo: N pubinfo: dt: Jun2025 vid: 40 iid: 3 pid: 622 pub: Oxford University Press / USA artinfo: ui: 186811111 186811111 186811111 10.1093/heapro/daaf046 186811111 ppf: 1 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Predicting health literacy in Brazil: a machine learning approach. aug: au: Tabak, Benjamin Miranda Almeida, Rubiane Daniele Cardoso de Froner, Matheus Britto Cardoso, Débora Helena Rosa Conceição, Laís Almeida da affil: School of Public Policy and Government, Getulio Vargas Foundation, SGAN 602 Módulos A,B,C, Asa Norte, Brasília 70830-020, Brazil sug: subj: Health Literacy Evaluation Prediction Models Machine Learning Human Brazil Funding Source Descriptive Statistics Algorithms Medication Compliance Educational Status Health Information Questionnaires Public Health Health Policy Health Promotion Health Services Accessibility Social Determinants of Health Adolescence Adult Middle Age Aged Male Female Adolescent: 13-18 years Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Male Female ab: Health literacy is essential for promoting well-being and the ability to make informed decisions. We investigated the level of health literacy in Brazil and identified the predictive factors that influence it. Our data contribute to the international context, with a focus on countries in the Global South and, in particular, Latin America. By analyzing health literacy in Brazil, this study sheds light on the challenges faced by populations with similar socioeconomic backgrounds in low- and middle-income countries, where disparities in access to education and health services are widespread. In addition to descriptive analysis, we used the Random Forest machine learning algorithm, which uses bootstrap aggregation (bagging). To make the results interpretable, we implemented Shapley's Additive exPlanation values. The results show a predominance of problematic levels of health literacy among the population. The analysis reveals that factors such as medication use, dependence on the Unified Health System (Sistema Único de Saúde), and educational level are significant predictors of health literacy. The findings highlight the need for public policies aimed at reducing socioeconomic disparities and improving the public health system in order to promote better access to and understanding of health information. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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