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<b>Rede de atenção à saúde na perspectiva de usuários com diabetes/ Health care network in the perspective of users with diabetes<b>

2019· article· pt· W2965252359 on OpenAlexaff
Karyne da Silva do Carmo, Marcelo Medeiros, Onislene Alves Evangelista de Almeida, Tânia Cristina Morais Santa Bárbara Rehem, Margareth Santos Zanchetta, Walterlânia Silva Santos

Bibliographic record

VenueCiência Cuidado e Saúde · 2019
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPerspective (graphical)Health professionalsGerontologyHumanitiesMedicinePsychologyHealth carePhilosophyArtPolitical science

Abstract

fetched live from OpenAlex

Objetivo: Compreender as perspectivas de usuários do SUS com Diabetes Mellitus tipo 2 (DM2) sobre seu atendimento na Rede de Atenção à Saúde (RAS). Método: Trata-se de estudo qualitativo de caráter descritivo, desenvolvido por meio de entrevistas gravadas digitalmente, individual, posteriormente transcritas e aplicada a técnica de análise de conteúdo, modalidade temática. Resultados: Entrevistou-se 12 pessoas com DM2, predominando mulheres, de ensino fundamental completo, com média de tempo do referido diagnóstico de seis anos. Essas características reforçaram o uso de diferentes pontos da RAS. Emergiram quatro categorias: Fragilidade da UBS como porta de entrada à RAS, (Des) acolhimento nos diferentes pontos da RAS, Educação em Saúde e Serviços de saúde em RAS, que sumarizaram as percepções desses usuários sobre seu percurso assistencial dentro da RAS, e destacaram dificuldades na comunicação entre os pontos de atenção, na gestão de recursos materiais e humanos. Considerações finais: Conclui-se a importância do monitoramento e avaliação das RAS com vistas à qualificação dos processos de trabalho e fortalecimento dos serviços a partir da reflexão crítica das ações, tendo o usuário como protagonista do sistema, além da possibilidade de sensibilizar gestores e profissionais de saúde sobre as articulações dos serviços na composição das RAS.

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.

How this classification was reachedexpand

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0040.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.274
Teacher spread0.259 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2019
Admission routes1
Has abstractyes

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