A qualitative study evaluating parental attitudes towards the creation of a female youth cohort (LEGACY) in the Breast Cancer Family Registry
Bibliographic record
Abstract
OBJECTIVES: Expanding the existing Breast Cancer Family Registry (BCFR) to enrol daughters aged 6-17 years in a prospective cohort study named LEGACY (Lessons in Epidemiology and Genetics of Adult Cancer from Youth) offers the opportunity to study the effects of genetic and environmental exposures in youth on adult breast cancer risk. Few studies have assessed parents' willingness to enroll their daughters in genetic epidemiological cohort studies. Since BCFR parents are the gatekeepers of their daughters' future enrollment, it is important to explore their interests and attitudes towards LEGACY. METHODS: Semi-structured telephone interviews were conducted with 85 BCFR participant parents at 3 BCFR sites in Ontario, Canada, and in Utah and Northern California. We explored parents' thoughts and feelings (interests and attitudes) regarding their daughters' enrollment in LEGACY and different data collection modalities. Qualitative analysis of audiotaped interviews was carried out utilizing an inductive content analysis. RESULTS: Parents' acceptance of three data collection modalities were 92% (78/85) for questionnaire data, 87% (74/85) for biological samples and 63% (46/73) for physical examination for pubertal staging. The parents' primary motivation for participation was altruistic. Their concerns regarding their daughters' participation centered on exacerbating awkward pubertal feelings, increasing cancer anxiety, respecting autonomy and maturity, privacy and future use of data and logistical impediments. CONCLUSION: Parents demonstrated a high level of interest in the creation of LEGACY. Their motivation to participate was balanced by their desire to protect daughters from undue harm. These interviews contributed valuable information for the design of LEGACY.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".