Trust, choice and obligation: a qualitative study of enablers of colorectal cancer screening in South Australia
Bibliographic record
Abstract
Colorectal cancer (CRC) has the second highest cancer prevalence and mortality rates in Australia. The Australian National Bowel Cancer Screening Program (NBCSP) aims to increase early detection of CRC by offering free faecal occult blood testing. The NBCSP aims to offer choice to consumers about whether or not to participate in screening. This article presents data on trust, choice and perceived obligation to participate in the NBCSP by population groups with low uptake. A qualitative study was undertaken in South Australia. We interviewed 94 people from four culturally distinct groups: Greek, Iranian, Anglo-Australian and Indigenous peoples. This article demonstrates the complexity of factors shaping the choice, or lack thereof, to participate in the NBCSP. Informed choice is based on adequate knowledge, although this varied among our participants, highlighting the need for more health education in appropriate languages. An obligation to participate was found in the Iranian and Anglo-Australian groups and resulted from an established personal relationship with the doctor, a sense of duty, the acknowledgement of government investment and appreciation. Overall, this article makes a link between trust, choice and obligation, adding to literature on the sociology of trust and medical screening and highlighting important issues in the need of a policy and practice to improve CRC screening rates.
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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 | 0.018 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".