Predictors of Participation in Psychosocial Telephone Counseling following Genetic Testing for BRCA1 and BRCA2 Mutations
Bibliographic record
Abstract
Although adjunctive educational and psychosocial programs are now being developed for BRCA1 and BRCA2 (BRCA1/2) mutation carriers, limited information is available about whether mutation carriers will want to receive such programs or about the characteristics of individuals who participate. The goals of the present study were to describe rates of completing a psychosocial telephone counseling (PTC) intervention that was offered to female BRCA1/2 mutation carriers and to identify sociodemographic and psychological factors associated with decisions to complete the intervention. Subjects were 66 BRCA1/2 mutation carriers who were randomized to receive a PTC intervention following receipt of genetic test results. Sociodemographic and psychological factors were evaluated before notification of assignment to the PTC intervention. Completion of the intervention was determined from study records. Overall, 75.8% of subjects completed the PTC intervention. Compared to unaffected subjects, those affected with breast and/or ovarian cancer were 76% less likely to complete the intervention [odds ratio (OR) = 0.24, 95% confidence interval (CI) = 0.06, 0.98, P = 0.05]. In addition, subjects with higher levels of cancer-specific distress [OR = 4.74, 95% CI = 1.02, 22.03, P = 0.05] and those with greater perceptions of social support [OR = 5.81, 95% CI = 1.29, 26.16, P = 0.02] were also most likely to complete the intervention. The results of this study suggest that while most BRCA1/2 mutation carriers are likely to complete an adjunctive psycho-educational program, personal history of cancer, cancer-specific distress, and perceptions of social support are likely to influence participation.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".