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Evaluation of Pain, Stress and Coping in Puerperal Women After Cesarean Section / Avaliação da dor, Estresse e Coping em Puérperas no Pós-Operatório de Cesárea

2019· article· pt· W2912909314 on OpenAlexaboutno aff
Vania da Rosa Friedrich, Monique Pereira Portella Guerreiro, Eliane Raquel Rieth Benetti, Joseila Sônego Gomes, Rosane Maria Kirchner, Eniva Miladi Fernandes Stumm

Bibliographic record

VenueRevista de Pesquisa Cuidado é Fundamental Online · 2019
Typearticle
Languagept
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsCoping (psychology)HumanitiesPsychologyMedicineClinical psychologyPhilosophy

Abstract

fetched live from OpenAlex

Objetivo: Avaliar dor, estresse percebido e coping em puérperas pós cesárea. Métodos: Estudo transversal, quantitativo, com 65 puérperas em um hospital geral. Foram incluídas puérperas no Pós Operatório de cesárea, com queixas e/ou sinais de dor nas últimas 24 horas. Coleta de dados de abril a julho de 2014, com Formulário de caracterização sociodemográfica/clínica, Questionário McGill de Dor, Escala de Estresse Percebido e Inventário de Estratégias de Coping. Foi realizada análise estatística. Projeto aprovado pelo Comitê de Ética e Pesquisa da Unijuí, CAAE nº 26726014.0.0000.5350. Resultados: 46,4% referiram dor severa; 64,6% dor “enjoada”. Dentre as puérperas, 83,1% foram classificadas em médio estresse e, a Reavaliação Positiva foi o fator de coping mais utilizado. Conclusão: Pelo procedimento cirúrgico a saúde biopsicossocial da puérpera pode ficar comprometida pela presença da dor, entretanto a utilização de estratégias de coping focadas no problema pode favorecer o enfrentamento dos estressores de forma positiva.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.033
GPT teacher head0.346
Teacher spread0.314 · 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 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

Citations2
Published2019
Admission routes1
Has abstractyes

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