Benefits and barriers to participation in colorectal cancer screening: a protocol for a systematic review and synthesis of qualitative studies
Bibliographic record
Abstract
INTRODUCTION: Colorectal cancer (CRC) poses a serious health problem worldwide. While screening is effective in reducing CRC mortality, participation in screening tests is generally suboptimal and social inequities in participation are frequently reported. The goal of this review is to synthesise factors that influence an individual's decision to participate in CRC screening, and to explore how those factors vary by sex, ethnicity and socioeconomic status. DATA SOURCES: A primary search of Cumulative Index to Nursing and Allied Health Literature (CINAHL), MEDLINE, EMBASE, PsycINFO, and a secondary search of grey literature and articles taken from references of included articles (from inception to July 2013). DESIGN: A systematic review and Meta-study synthesis of qualitative studies that address perceived benefits and barriers to participation in CRC screening tests among adults 50 years of age or older. REVIEW METHODS: The two-staged Meta-study methodology by Paterson will be used to conduct this review. In stage 1, similarities/differences, patterns and themes will be identified across three levels of analysis while preserving the context of original studies. In stage 2, synthesis will extend beyond the analysis to generate new theory of the phenomenon through a process called Meta-synthesis. DISCUSSION: This review offers to generate a framework to better understand benefits and barriers that affect decision-making to participate in CRC screening among different sectors of the population. This framework will be a relevant tool for policy makers in framing educational materials, for patient-centered communication, and for researchers interested in the science of equity. This review is registered in PROSPERO (registration number: CRD42013005025).
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 | 0.223 | 0.203 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.014 |
| Bibliometrics | 0.018 | 0.015 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.056 | 0.009 |
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".