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Record W1983703619 · doi:10.1002/rnj.21

Rehabilitation After Breast Cancer: Recommendations from Young Survivors

2012· article· en· W1983703619 on OpenAlexaffabout
Julie Easley, Baukje Miedema

Bibliographic record

VenueRehabilitation Nursing · 2012
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsDalhousie University
Fundersnot available
KeywordsRehabilitationBreast cancerPhysical therapyMedicinePhysical medicine and rehabilitationCancerInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: Studies show that younger women have a greater physical, psychological, and social morbidity, and poorer quality of life after a breast cancer diagnosis than older women. With improving survival rates, cancer rehabilitation has an increasing role in the cancer care continuum, particularly for younger women who potentially have many productive years ahead of them. The purpose of this study was to assess the cancer rehabilitation needs of young women after breast cancer treatment. METHODS: In this qualitative, descriptive study, we purposefully sampled 35 breast cancer survivors diagnosed under the age of 50 in Atlantic Canada to participate in two telephone interviews. RESULTS/DISCUSSION: Recommendations included: improved communication between the various healthcare professionals; healthcare professionals taking on a more proactive approach in recommending rehabilitation after treatment; better insurance coverage or financial assistance for rehabilitation services; and more rehabilitation support for rural populations. CONCLUSION: Rehabilitation nurses can play an important role in educating patients, recognizing long-term sequelae, and directing patients to various medical and allied health care professionals to provide proper support and care post-breast cancer treatment.

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 categoriesInsufficient 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 score0.134
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.305
Teacher spread0.295 · 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

Citations23
Published2012
Admission routes2
Has abstractyes

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