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Record W2068595110 · doi:10.1007/s10897-013-9667-2

Seeking Balance: Decision Support Needs of Women Without Cancer and a Deleterious <i>BRCA1</i> or <i>BRCA2</i> Mutation

2013· article· en· W2068595110 on OpenAlexaboutno aff
Meghan Underhill‐Blazey, Cheryl B. Crotser

Bibliographic record

VenueJournal of Genetic Counseling · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Cancer InstituteSigma Theta Tau InternationalUniversity of Massachusetts Boston
KeywordsPsychosocialPsychological interventionGenetic counselingMedicineHealth communicationQualitative researchHuman geneticsPsychologyPublic healthBreast cancerCancerNursingPsychiatryGenetics

Abstract

fetched live from OpenAlex

Recommendations for women with a deleterious BRCA1 or BRCA2 gene mutation include complex medical approaches related to cancer risk reduction and detection. Current science has not yet fully elucidated decision support needs that women face when living with medical consequences associated with known hereditary cancer risk. The purpose of this study was to describe health communication and decision support needs in healthy women with BRCA1/2 gene mutations. The original researchers completed an interpretive secondary qualitative data analysis of 23 phenomenological narratives collected between 2008 and 2010. The Ottawa Decision Support and Patient Centered Communication frameworks guided the study design and analysis. Women described a pattern wherein breast and ovarian cancer risk, health related recommendations and decisions, and personal values were prioritized over time based on life contexts. Knowing versus acting on cancer risk was not a static process but an ongoing balancing act of considering current and future personal and medical values, further compounded by the complexity of recommendations. Women shared stories of anticipatory, physical and psychosocial consequences of the decision making experience. The findings have potential to generate future research questions and guide intervention development. Importantly, findings indicate a need for ongoing, long-term, support from genetics professionals and decision support interventions, which challenges the current practice paradigm.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.556

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 head0.008
GPT teacher head0.265
Teacher spread0.258 · 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 designBench or experimental
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

Citations29
Published2013
Admission routes1
Has abstractyes

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