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Record W4220969900 · doi:10.17058/psiunisc.v6i1.16658

Impactos da pandemia COVID-19 nas vivências profissionais de residentes multiprofissionais em saúde

2022· article· pt· W4220969900 on OpenAlexaff
Marcus Vinicius Castro Witczak, Karine Vanessa Perez, Makely Ferreira Rodrigues

Bibliographic record

VenuePSI UNISC · 2022
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesCoronavirus disease 2019 (COVID-19)PsychologyMedicinePhilosophyDisease

Abstract

fetched live from OpenAlex

A pandemia COVID19 impôs aos serviços e trabalhadores da Saúde uma realidade inesperada. Desinformação sobre o vírus causador e o desenvolvimento da doença, o risco da exposição direta e o medo daí consequente, trouxeram aos profissionais novos desafios em suas jornadas e novas fontes de sofrimento e adoecimento mental. Inserem-se neste contexto os Programas de Residência Multiprofissional em Saúde e os residentes. Assim, este estudo, objetivou identificar os impactos da pandemia na saúde mental dos residentes multiprofissionais em saúde. Para o seu desenvolvimento, realizou-se uma pesquisa com os Residentes Multiprofissionais de um hospital de ensino do interior do Rio Grande do Sul, coletando-se dados (maio e junho de 2020) em um questionário semiestruturado. Obteve-se a participação consentida de 20 residentes. Os resultados evidenciam níveis elevados de estresse impactando no autocuidado. Diante disto, momentos de escuta psicológica (para relatarem seus medos, inseguranças e emoções) e o apoio psicossocial no ambiente de trabalho foram estratégias sinalizadas pelos residentes como importantes para enfrentamento do contexto pandêmico.

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)0.005
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0040.000
Scholarly communication0.0010.001
Open science0.0040.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.073
GPT teacher head0.372
Teacher spread0.300 · 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; a candidate call from one teacher head, not a consensus.

Study designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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