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Record W3033559111 · doi:10.5964/pch.v8i1.310

Association between cancer stigma, pain and quality of life in breast cancer

2020· article· en· W3033559111 on OpenAlexaff
Ora Nakash, Leeat Granek, Michal Cohen, Merav Ben David

Bibliographic record

VenuePsychology Community & Health · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsYork University
Fundersnot available
KeywordsBreast cancerStigma (botany)MedicineQuality of life (healthcare)CancerSocial stigmaOncologyFamily medicinePsychiatryInternal medicineNursing

Abstract

fetched live from OpenAlex

Aim We examined the association between cancer stigma and quality of life. We further explored the role of pain intensity in this association among women with breast cancer in the first months following diagnosis. Methods 105 women with breast cancer within 8 months of diagnosis completed self-report measures assessing cancer stigma, pain intensity and quality of life. Results Our findings show that stigma among breast cancer patients is associated with worse quality of life. Pain intensity partially mediated the relationship between cancer stigma and quality of life. We recruited a convenience sample of women with breast cancer, which may be subject to selection bias. The cross sectional design of the study precludes inferences regarding causality. Conclusions Health professionals should recognize and mitigate the impact of stigma as an important factor that is associated with impaired quality of life among patients with breast cancer. Continued attention should be paid to pain intensity and the complex relationship between stigma and pain in predicting quality of life.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.104
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
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)0.0000.000

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 head0.123
GPT teacher head0.440
Teacher spread0.317 · 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.

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

Citations8
Published2020
Admission routes1
Has abstractyes

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