Why doesn't Crohn's Disease DNA-based risk information motivate quitting? A qualitative study
Bibliographic record
Abstract
Background: Despite strong expectations that DNA-based risk information can motivate behaviour change, a recent trial found DNA-based risk assessments did not increase quitting in smokers with familial risks of Crohn’s Disease(CD) Aims: To use qualitative methods to explore trial participants’ understandings of CD risk and reasons for (not) quitting. Methods: Thirty-two participants, purposively sampled from the DNA and control groups, were interviewed, with transcripts analysed using framework analysis. Results: Most participants felt their CD risk was low. Several had difficulty applying population-based risk estimates or adopted deterministic views of their risk. Some viewed the smoking-CD link sceptically, particularly if affected relatives were non-smokers. Others saw CD as just another smoking-related risk, which would not motivate quitting. Conclusions: DNA-based risk information regarding common disorders, such as CD, may not motivate quitting due to low magnitude risk estimates, biased risk perceptions, and assimilation of DNA-based information with prior knowledge of smoking-related risks.
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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 | 0.028 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".