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Record W7120661988

Returning to work and family household income after breast and gynecologic cancer treatment

2017· article· pt· W7120661988 on OpenAlexaboutno aff
Priscila Aparecida Bilck

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2017
Typearticle
Languagept
FieldMedicine
TopicWomen's cancer prevention and management
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Breast cancerGynecologic cancerLow incomeFamily income
DOInot available

Abstract

fetched live from OpenAlex

Objetivo: Analisar as características de retorno ao trabalho e renda familiar entre mulheres tratadas para câncer de mama e câncer ginecológico, considerando suas condições clínicas e físico-funcionais. Métodos: Estudo transversal com mulheres maiores de 18 anos acometidas pelo câncer de mama e ginecológico, que foram admitidas na Maternidade Carmela Dutra (Florianópolis - SC) para tratamento oncológico. A avaliação consistiu em uma ficha de avaliação inicial com perguntas relacionadas aos aspectos laborais e financeiros, aplicação dos questionários McGill e DASH e exame físico para avaliar a sensibilidade, presença de linfedema e cordão axilar. Resultados: Foram avaliadas 160 participantes, sendo 89 com câncer de mama e 71 com câncer ginecológico, com idade média de 53,69 ± 12,18 anos. Verificou-se que a complicação físico-funcional mais frequente foi a dor (55,6%) para os dois tipos de câncer, e disfunção de MMSS em 47,2% daquelas com câncer de mama. Ao serem questionadas sobre os aspectos laborais, 78,1% das participantes referiram que trabalhavam antes da doença, sendo que destas, 55,2% retornaram ao trabalho. Entre as que não retornaram, o motivo principal foi afastamento ou perícia por causa da doença (44,6%). Durante o tratamento, 45,6% das participantes apresentaram dificuldades financeiras como resultado do câncer, e 39,4% afirmaram precisar de ajuda financeira. Conclusão: Os resultados deste estudo apontaram que os tratamentos para o câncer de mama e ginecológico influenciaram negativamente os aspectos laborais e financeiros das sobreviventes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.029
GPT teacher head0.270
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2017
Admission routes1
Has abstractyes

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