Primary care provider interventions for addressing cancer screening participation with marginalised patients: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Cancer screening is an integral component of primary care, and providers can play a key role in facilitating screening. While much work has focused on patient interventions, there has been less attention on primary care provider (PCP) interventions. In addition, marginalised patients experience disparities in cancer screening which are likely to worsen if not addressed. The objective of this scoping review is to report on the range, extent and nature of PCP interventions that maximise cancer screening participation among marginalised patients. Our review will target cancers where there is strong evidence to support screening, including lung, cervical, breast and colorectal cancers. METHODS AND ANALYSIS: . Comprehensive searches will be conducted by a health sciences librarian using Ovid MEDLINE, Ovid Embase, Scopus, CINAHL Complete and the Cochrane Central Register of Controlled Trials. We will include peer-reviewed English language literature published from 1 January 2000 to 31 March 2022 that describes PCP interventions to maximise cancer screening participation for breast, cervical, lung and colorectal cancers. Two independent reviewers will screen all articles and identify eligible studies for inclusion in two stages: title and abstract, then full text. A third reviewer will resolve any discrepancies. Charted data will be synthesised through a narrative synthesis using a piloted data extraction form informed by the Template for Intervention Description and Replication checklist. ETHICS AND DISSEMINATION: Since this is a synthesis of digitally published literature, no ethics approval is needed for this work. We will target appropriate primary care or cancer screening journals and conference presentations to publish and disseminate the results of this scoping review. The results will also be used to inform an ongoing research study developing PCP interventions for addressing cancer screening with marginalised patients.
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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 | 0.100 | 0.076 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.082 | 0.016 |
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".