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Record W1557247778 · doi:10.1097/ncc.0000000000000124

Women With Breast Cancer

2014· article· en· W1557247778 on OpenAlexaff
Susanne Hellerstedt-Börjesson, Karin Nordin, Marie-Louise Fjällskog, Inger K. Holmström, Cecilia Arving

Bibliographic record

VenueCancer Nursing · 2014
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsMedicineVisual analogue scaleBreast cancerEpirubicinPhysical therapyDocetaxelChemotherapyPerceptionPain assessmentThematic analysisCancerQualitative researchInternal medicinePain managementPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Chemotherapy treatment for cancer diseases can cause body pain during adjuvant therapy. OBJECTIVE: The aim was to describe the perceived impact of adjuvant chemotherapy-induced pain (CHIP) on the daily lives of women with newly diagnosed breast cancer, using triangulation. METHOD: Fifty-seven women scheduled for chemotherapy in doses of 75 mg/m or greater of epirubicin and/or docetaxel participated. Twenty-two of these women registered pain with values of 4 or more on the visual analog scale on day 10 following chemotherapy. Of these 22, 16 participated in an interview and colored a printed body image. A qualitative thematic stepwise analysis of the interviews was performed. RESULTS: Chemotherapy-induced pain had a profound impact on daily life. Ten women reported the worst possible pain, with visual analog scale scores of 8 to 10. Three different categories crystallized: perception (A) of manageable pain, which allowed the women to maintain their daily lives; perception (B) of pain beyond imagination, whereby the impact of pain had become more complex; and perception (C) of crippling pain, challenging the women's confidence in survival. CONCLUSIONS: The findings highlight the inability to capture CHIP with 1 method only; it is thus necessary to use complimentary methods to capture pain. We found that pain had a considerable impact on daily life, with surprisingly high scores of perceived pain, findings that to date have been poorly investigated qualitatively. IMPLICATIONS FOR PRACTICE: Nurses need to (1) better identify, understand and treat CHIP, using instruments and protocols; and (2) provide improved communication about pain and pain management.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.282
Teacher spread0.270 · 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

Citations23
Published2014
Admission routes1
Has abstractyes

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