Telephone versus in‐person colorectal cancer risk and screening intervention for first‐degree relatives: A randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Having a first-degree relative (FDR) with colorectal cancer (CRC) is a significant risk factor for CRC. Counseling for FDRs regarding CRC risk factors and personalized risk is important to improve knowledge and screening compliance. METHODS: A 3-arm randomized controlled trial compared tailored in-person and telephone CRC counseling interventions with controls among FDRs who were not mutation carriers for known hereditary cancer syndromes, but who were considered to be at an increased risk based on family history. It was hypothesized that both telephone and in-person approaches would increase CRC knowledge, screening adherence, perceived risk accuracy, and psychosocial functioning compared with controls. The authors anticipated greater satisfaction with the in-person approach. CRC knowledge, risk perception, psychosocial functioning, and intention to screen were assessed at baseline and at 2-week and 2-month follow-ups (primary endpoint). RESULTS: A total of 278 FDRs (mean age, 47.4 years, standard deviation, 11.38 years) participated. At baseline, participants reported low to moderate CRC knowledge and overestimations of risk. Screening adherence was 73.7%. At 2 months, participants in the in-person arm and telephone arm demonstrated improvements in knowledge and perceived risk and were not found to be statistically different from each other. However, when comparing each intervention with controls, knowledge in the in-person arm was found to be statistically significantly higher, but the difference between the telephone and control arms was not. Cancer-related stress reduced over time in all groups. Intervention benefits were maintained at 1 year. Baseline screening intent/adherence were high, and therefore did not reach statistically significant improvement. CONCLUSIONS: Tailored in-person or telephone formats for providing CRC risk counseling, incorporating behavioral interventions, appear to improve knowledge and risk perceptions, with high client satisfaction.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".