The tobacco quitline setting as a teachable moment: The Educating Quitline Users About Lung (EQUAL) cancer screening randomized trial
Bibliographic record
Abstract
Although lung cancer screening (LCS) using low-dose CT is recommended for high-risk individuals, screening adherence remains low. We conducted a randomized trial to compare two methods of providing LCS education to Maryland Tobacco Quitline (MTQ) callers in order to assess whether this setting may serve as a teachable moment for LCS-eligible individuals. MTQ callers (50-80 years, 20+ pack-years, prior LCS ≥12 months) completed the baseline and were randomized to the Print- or Web-based version of ShouldIScreen.com. Participants completed 1- and 4-month follow-up assessments to evaluate intervention engagement and LCS-related outcomes. Participants (Print = 152, Web = 146) were 61.7 (SD = 6.3) years old and reported 63.5 pack-years (SD = 36.0). Most identified as Black (54.2%), female (66.1%), having internet access (78.9%), completing other recommended cancer screenings (86.3%), and that they would undergo LCS if recommended by their provider (91.3%). By 4 months, significantly more Print (75.0%) than Web (61.6%) participants had read the materials (P = .01). Most reported the interventions contained "the right amount" of information (92.6%) and prepared them to talk with their doctor (57.2%). Regarding screening-related outcomes, 42.8% (Print) and 43.8% (Web) had scheduled or completed a low-dose CT scan or a shared decision-making visit (P = .86). In a racially diverse sample of LCS-eligible quitline callers, offering LCS educational materials resulted in high intervention engagement and screening-related appointments. As >20% did not have internet access, providing participants' preferred modality (web/print) may improve intervention engagement and knowledge. Improving LCS awareness represents an important opportunity to increase screening among eligible but unscreened quitline callers.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".