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Record W2537641920 · doi:10.5539/gjhs.v9n5p180

The Impact of Breast Cancer on Female Sexuality: An Integrative Literature Review

2016· article· en· W2537641920 on OpenAlexvenueno aff
Ana Rita Pimentel Castelo, Anne Fayma Lopes Chaves, Karine C. Bezerra, Camila Teixeira Moreira Vasconcelos, Camila Brasil Moreira

Bibliographic record

VenueGlobal Journal of Health Science · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsScopusCINAHLCochrane LibraryFeelingBreast cancerHuman sexualityMedicineGerontologyQuality of life (healthcare)MEDLINECancerPsychologyMeta-analysisNursingGender studiesPsychological interventionSocial psychologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to conduct an integrative literature review on the impact of breast cancer (CA) on female sexuality.METHODS: The search was performed online in November 2014 using the following databases: Cumulative Index of Nursing and Allied Health Literature (CINAHL), Scopus, PubMed, Latin American and Caribbean Health Sciences (LILACS) and the Cochrane Library. The search results consisted of 13 articles.SYNTHESIS: Most studies have shown that women have less lubrication and a decrease in desire, which directly affect their quality of life. Moreover, 70% of the articles described limitations of the studies, the most cited of which were as follows: small sample size because of the feeling that participants considered the theme to be embarrassing, the altered emotional state decreased willingness to participate in the study, and the non-participation of husbands in the study reduced the impact on marital intimacy.CONCLUSION: It can be concluded that breast cancer has a negative impact on the sexual function of women who are affected by this disease.

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)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0170.014
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.027
GPT teacher head0.433
Teacher spread0.406 · 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 designSystematic review
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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Journal of Health Science→Same topicCancer survivorship and care→French-language works237,207→