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Como as redes sociais influenciam a tomada de decisões sobre saúde: um estudo sobre letramento informacional em saúde e comunicação

2023· article· pt· W6958493705 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2023
Typearticle
Languagept
FieldSocial Sciences
TopicMedia and Communication Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracyDigital literacyWork (physics)Context (archaeology)

Abstract

fetched live from OpenAlex

<b>How Social Networks Influence Health Decision-Making: A Study on Health Information Literacy and Communication</b><b>RESUMO</b>A contemporaneidade trouxe mudanças significativas na forma como as pessoas se comunicam e se informam, especialmente sobre temas relacionados à saúde, considerando o que foi vivenciado durante a pandemia de COVID-19, onde se configurou uma epidemia de desinformação (Cinelli et al., 2020). Neste trabalho discutimos a Comunicação em Saúde (Thomas, 2006; Araújo e Cardoso, 2014; Nardi et al., 2018) a partir dos modelos comunicacionais clássicos (McQuail, 2003; Sousa, 2006; Serra, 2007; Martino, 2013) e vislumbramos seu papel em uma sociedade, cada vez mais dependente das redes sociais (Oliveira, 2014). Ponderamos sobre o papel da mídia e do jornalismo, como demandante de ações na promoção à saúde conforme preconiza a Cartas de Ottawa, de 1986. A partir das noções de Letramento Informacional (Gasque, 2012; 2020), Letramento/Literacia em Saúde (OMS, 2021; Peres, Rodrigues e Silva, 2021; Zarcadoolas, Pleasant e Greer, 2005), Letramento Informacional em Saúde (LIS) (Medical Libray Association, 2011; Niemelä et al, 2012), nos propusemos investigar as habilidades individuais em reconhecer; identificar; utilizar; avaliar; analisar e compreender informações em saúde e com elas tomar decisões (OMS, 2021) por meio de pesquisa on-line com 220 respondentes, constatamos a dificuldade no reconhecimento de fontes confiáveis no meio digital e a confiança do público em meios tradicionais como a televisão e os sites de notícias quando se trata de saúde, por essa razão também analisamos notícias veiculadas no mês de novembro de 2023 na editoria de saúde dos principais sites de notícias brasileiros, usando como base uma adaptação do protocolo da Rede Ibero-americana de Monitoramento e Capacitação em Jornalismo Científico (Massarani e Ramalho, 2012).<b>ABSTRACT</b>Contemporaneity has brought significant changes in the way people communicate and inform themselves, especially on health-related topics, considering what was experienced during the COVID-19 pandemic, where an epidemic of misinformation was configured (Cinelli et al., 2020). In this paper, we discuss Health Communication (Thomas, 2006; Araújo and Cardoso, 2014; Nardi et al., 2018) based on classical communication models (McQuail, 2003; Sousa, 2006; Serra, 2007; Martino, 2013) and we glimpse its role in a society increasingly dependent on social networks (Oliveira, 2014). We pondered on the role of the media and journalism as a demand for actions in health promotion as recommended by the Ottawa Charters of 1986. Based on the notions of Information Literacy (Gasque, 2012; 2020), Health Literacy/Literacy (WHO, 2021; Peres, Rodrigues and Silva, 2021; Zarcadoolas, Pleasant &amp; Greer, 2005), Health Information Literacy (HIL) (Medical Libray Association, 2011; Niemelä et al, 2012), we set out to investigate individual abilities to recognize; identify; use; evaluate; analyze and understand health information and make decisions with it (WHO, 2021) through an online survey with 220 respondents, we found the difficulty in recognizing reliable sources in the digital environment and the public's trust in traditional media such as television and news sites when it comes to health, for this reason we also analyzed news published in the month of November 2023 in the health section of the main news sites Brazilians, based on an adaptation of the protocol of the Ibero-American Network for Monitoring and Training in Scientific Journalism (Massarani and Ramalho, 2012). Key words: Information Literacy; Health Information Literacy; Health Communication; Social Media.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.775
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0360.016

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.119
GPT teacher head0.379
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it