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Record W2408763348 · doi:10.1097/spc.0000000000000184

Sexual identity after breast cancer

2015· review· en· W2408763348 on OpenAlexaff
Dana A. Male, Karen Fergus, Kimberley Cullen

Bibliographic record

VenueCurrent Opinion in Supportive and Palliative Care · 2015
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsSunnybrook Health Science CentreYork University
Fundersnot available
KeywordsMedicineBreast cancerMEDLINECancerGynecologyInternal medicineBiology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Breast cancer treatment indelibly alters a woman's reproductive and sexual functioning, body integrity, and the ways in which she self-identifies as a sexual being. Improved understanding of how treatment affects these aspects of a woman's health, identity, and relationships is necessary to ameliorate the effectiveness with which these issues are addressed by healthcare providers. RECENT FINDINGS: Women with breast cancer experience significantly greater rates of sexual dysfunction and poorer body image than do healthy women. Despite this reality, most breast cancer patients are dissatisfied with the amount and quality of care they receive from their healthcare providers around sexuality. Although a substantial proportion of women endorse difficulties with sexual functioning, reproduction, and body image, each woman's experience is individual and contextual, influenced by a range of factors (e.g., age, illness stage, treatment type(s), relationship status, and others). SUMMARY: A high proportion of women experience difficulties with sexual health and self-concept secondary to breast cancer, yet an overwhelming number report receiving inadequate or nonexistent care in these domains from their healthcare providers. There remains too wide a gap between the needs of this population and the healthcare system's response to such needs. To bridge this gap, oncology professionals across a range of disciplines must be better trained to identify, assess, and treat such difficulties, preferably using a multimodal approach that includes biological, as well as psychological and social, strategies.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
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 head0.167
GPT teacher head0.471
Teacher spread0.304 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations119
Published2015
Admission routes1
Has abstractyes

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