Participation rates for organized colorectal cancer screening programmes: an international comparison
Bibliographic record
Abstract
OBJECTIVE: Participation, an indicator of screening programme acceptance and effectiveness, varies widely in clinical trials and population-based colorectal cancer (CRC) screening programmes. We aimed to assess whether CRC screening participation rates can be compared across organized guaiac fecal occult blood test (G-FOBT)/fecal immunochemical test (FIT)-based programmes, and what factors influence these rates. METHODS: Programme representatives from countries participating in the International Cancer Screening Network were surveyed to describe their G-FOBT/FIT-based CRC screening programmes, how screening participation is defined and measured, and to provide participation data for their most recent completed screening round. RESULTS: Information was obtained from 15 programmes in 12 countries. Programmes varied in size, reach, maturity, target age groups, exclusions, type of test kit, method of providing test kits and use, and frequency of reminders. Coverage by invitation ranged from 30-100%, coverage by the screening programme from 7-67.7%, overall uptake/participation rate from 7-67.7%, and first invitation participation from 7-64.3%. Participation rates generally increased with age and were higher among women than men and for subsequent compared with first invitation participation. CONCLUSION: Comparisons among CRC screening programmes should be made cautiously, given differences in organization, target populations, and interpretation of indicators. More meaningful comparisons are possible if rates are calculated across a uniform age range, by gender, and separately for people invited for the first time vs. previously.
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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".