Primary care providers’ views on a future lung cancer screening program
Bibliographic record
Abstract
BACKGROUND: The National Lung Screening Trial demonstrated that screening with low-dose computed tomography significantly reduces mortality from lung cancer in high-risk individuals. OBJECTIVE: To describe the role preferences and information needs of primary care providers (PCPs) in a future organized lung cancer screening program. METHODS: We purposively sampled PCPs from diverse health regions of Ontario and from different practice models including family health teams and community health centres. We also recruited family physicians with a leadership role in cancer screening. We used focus groups and a nominal group process to identify informational priorities. Two analysts systematically applied a coding scheme to interview transcripts. RESULTS: Four groups were held with 34 providers and administrative staff [28 (82%) female, 21 (62%) physicians, 7 (20%) other health professionals and 6 (18%) administrative staff]. PCPs and staff were generally positive about a potential lung cancer screening program but had variable views on their involvement. Informational needs included evidence of potential benefits and harms of screening. Most providers preferred that a new program be modelled on positive features of an existing breast cancer screening program. Lung cancer screening was viewed as a new opportunity to counsel patients about smoking cessation. CONCLUSIONS: The development of a future lung cancer screening program should consider the wide variability in the roles that PCPs preferred. An explicit link to existing smoking cessation programs was seen as essential. As providers had significant information needs, learning materials and opportunities should be developed with them.
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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".