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Record W2803028345 · doi:10.1097/ncc.0000000000000600

Exploring Women’s Support Needs After Breast Reconstruction Surgery

2018· article· en· W2803028345 on OpenAlexafffund
Tracey Carr, Gary Groot, David L. Cochran, Mikaela Vancoughnett, Lorraine Holtslander

Bibliographic record

VenueCancer Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsCanadian Rural Health Research SocietyUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsThematic analysisMedicineEmotional supportSocial supportInformation needsNursingMastectomyFamily supportNeeds assessmentHealth careFamily medicineQualitative researchPsychologyBreast cancerPhysical therapySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: The procedures for breast reconstruction (BR) after mastectomy frequently initiate a difficult recovery period. A better understanding of women's support needs after surgery would improve patient care. OBJECTIVE: The aim of this study was to identify patients' support needs after BR. METHODS: In a retrospective study design, 21 participants described their support experiences after BR, including their sources of support and the impact of support on their recovery in a semistructured interview. Transcriptions of the interviews were analyzed using thematic analysis. RESULTS: Four support needs were identified and were composed of elements of instrumental, emotional, and informational support. These needs were addressed to varying degrees by healthcare providers, family members, and other women who had BR experience. CONCLUSION: Women's experience of BR and their ability to cope are markedly better when their support needs are effectively addressed. Greater attention to their needs for support has the potential to improve patient care. IMPLICATIONS FOR PRACTICE: Nurses play a pivotal role in providing information to women who are recovering from BR. Improved access to communication channels between nurses and patients would likely improve patients' support experiences. In addition, nurses can assess the women's specific support needs and partner with families to help them understand how best to support women during recovery.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.944
Threshold uncertainty score0.999

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)0.0020.000

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 head0.063
GPT teacher head0.281
Teacher spread0.218 · 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 designOther design
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

Citations26
Published2018
Admission routes2
Has abstractyes

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