Influence of the family cluster effect on psychosocial variables in families undergoing <i>BRCA1/2</i> genetic testing for cancer susceptibility
Bibliographic record
Abstract
OBJECTIVE: This study evaluated the influence of the family cluster effect on behavioral and psychological variables among individuals undergoing BRCA1/2 genetic testing for cancer susceptibility. METHODS: French-Canadian women (n = 552) and men (n = 104) from 140 different families undergoing BRCA1/2 testing between years 1998 and 2004 completed a self-administered questionnaire on a wide range of behavioral and psychological variables. The impact of the family cluster effect on 29 variables was assessed using the intraclass correlation coefficient (ICC) as computed from multilevel random-effect models. RESULTS: ICC values were statistically significant for 22 of the 29 variables. Overall, the mean ICC value was 0.10. The ICC values for knowledge about hereditary breast and ovarian cancer and frequency of alcohol consumption were 0.25. The ICC value for the Impact of Event Scale, which is a commonly used measure of cancer-specific distress, was 0.14. CONCLUSIONS: Our results suggest that the family cluster effect influences the majority of behavioral and psychosocial variables. When studying psychosocial aspects of genetic testing for cancer susceptibility, the family cluster effect should be routinely accounted for when determining sample size and statistical methods.
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 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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".