MétaCan
Menu
Back to cohort

The Face of Suffering Among Women With Breast Cancer—Being in a Field of Forces

2002· article· en· W2065788487 on OpenAlexaboutno aff
Maria Arman, Arne Rehnsfeldt, Lisbet Lindholm, Elisabeth Hamrin

Bibliographic record

VenueCancer Nursing · 2002
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsBreast cancerExistentialismMedicineHealth careDiseaseQualitative researchPhenomenology (philosophy)Meaning (existential)CancerNursingPsychotherapistPsychologyInternal medicineSociology

Abstract

fetched live from OpenAlex

Through qualitative interviews, the suffering experiences of women with breast cancer and their significant others were disclosed. Seventeen women with different stages of breast cancer and 16 significant others from 4 different care cultures in Sweden and Finland participated. Five of the women had advanced metastatic breast cancer, and 12 had a localized disease. Mean age was 48 years. As a methodology, a team approach, inspired by the Vancouver School of Doing Phenomenology, was used. The findings elucidate how the suffering experience touched the women's inner existence and values. This can metaphorically be described as a "field of force" and affected everything in the women's lives, including their views of themselves and their relationships. Existential questions were raised about life and death and the meaning of life. In their suffering, the women's dependency upon significant others, as well as healthcare personnel, was prominent. Suffering related to healthcare was a strong theme. Different faces of suffering related to breast cancer may still be unknown by healthcare professionals working in cancer care.

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)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0120.014
Scholarly communication0.0050.004
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.271
Teacher spread0.261 · 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 designQualitative
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

Citations104
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueCancer NursingSame topicCancer survivorship and careFrench-language works237,207