MétaCan
Menu
Back to cohort
Record W4409910462 · doi:10.1590/0034-7167-2024-0075pt

Assistência de enfermagem ao paciente hospitalizado com COVID-19 à luz do Cuidado Fundamental

2025· article· pt· W4409910462 on OpenAlexaff
Fabieli Borges, Elizabeth Bernardino, Camila Rorato, Daniele Cristina dos Reis Bobrowec, Olívia Luciana dos Santos Silva, Amanda Gomes Ribeiro Pujol de Carvalho, Clémence Dallaire

Bibliographic record

VenueRevista Brasileira de Enfermagem · 2025
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)NursingMedicinePsychologyGerontologyDiseaseInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

RESUMO Objetivos: analisar como a pandemia de COVID-19 implicou no Cuidado Fundamental prestado por enfermeiros ao paciente hospitalizado em um hospital público. Métodos: pesquisa qualitativa, descritiva, exploratória. Foram entrevistados 24 enfermeiros que assistiram a pacientes com COVID-19 em um hospital público na capital no Paraná, de janeiro a fevereiro de 2022. Aplicou-se aos dados a Análise de Conteúdo de Creswell, operacionalizados pelo software MaxQda e à luz da teoria dos Cuidados Fundamentais. Resultados: foi obtido três categorias com suas dimensões respectivas: Cuidados Físicos (Higiene Pessoal; Conforto e Mobilização; Comer e beber; Descanso e sono; Segurança e Gerenciamento de medicamentos), Cuidado Psicossocial (Comunicação; Privacidade; dignidade, respeito e crenças; bem-estar emocional) e Cuidado Relacional (Escuta ativa; Empatia e compaixão; Engajamento, apoio e envolvimento a famílias e cuidadores e, trabalho com os pacientes). Considerações Finais: o período da pandemia pode ter oportunizado o olhar na relação enfermeiro-paciente-assistir especialmente alicerçado na teoria dos Cuidados Fundamentais.

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.562
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0060.002
Open science0.0060.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.062
GPT teacher head0.385
Teacher spread0.323 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueRevista Brasileira de EnfermagemSame topicHealthcare during COVID-19 PandemicFrench-language works237,207