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Record W4401948560 · doi:10.54033/cadpedv21n8-255

Acolhimento psicossocial aos trabalhadores da saúde durante a pandemia do Coronavírus: breve relato de experiência

2024· article· pt· W4401948560 on OpenAlex
Joana D’Arc Vieira Couto Astolphi, Daniela Aparecida de Sousa Moreira Ramos

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCaderno Pedagógico · 2024
Typearticle
Languagept
FieldHealth Professions
TopicOccupational Health and Burnout
Canadian institutionsMinistère de l’Emploi et de la Solidarité Sociale (Québec)
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

O artigo tem como objetivo relatar a experiência multiprofissional no manejo de um grupo de acolhimento psicossocial online voltado para trabalhadores da saúde que atuam na linha de frente no combate à COVID-19. Através de uma análise qualitativa dos dados, o estudo identificou tanto fortalezas quanto fragilidades no processo grupal, além de destacar a construção de temas emergentes que foram abordados por meio de intervenções breves durante os encontros virtuais. O estudo sublinha a importância de cuidar da saúde mental desses profissionais, que enfrentam desafios intensos e prolongados. Além disso, a pesquisa demonstra a viabilidade e a eficácia de grupos de acolhimento psicossocial online como uma estratégia potente para promover o cuidado e o bem-estar mental dos trabalhadores da saúde. A experiência relatada serve como exemplo de como o suporte emocional e psicológico pode ser fornecido de forma acessível e contínua, mesmo em contextos de extrema pressão e crise global.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient 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: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.005

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 head0.091
GPT teacher head0.468
Teacher spread0.377 · 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