Colorectal cancer screening behaviors among South Asian immigrants in Canada: a qualitative study
Bibliographic record
Abstract
Purpose – The purpose of this paper is to gain an in-depth understanding of beliefs, attitudes, and reasons for decision making about colorectal cancer (CRC) screening among South Asian (SA) immigrants. Design/methodology/approach – Six focus groups conducted in English, Punjabi, and Urdu were held with 42 SA immigrants, 50-74 years old and at average risk for CRC, from November 2012 to May 2013. All focus group discussions were audio-taped and transcribed verbatim. Data analysis used an inductive and systematic approach employing constant comparison techniques. Findings – Three dominant themes emerged. Beliefs and attitudes towards cancer and screening represented SA immigrant’s perceptions that early detection was beneficial; screening was not necessary in the absence of symptoms; cancer was scary; and the loss of previously established bowel practices upon immigration as potential risks for CRC. Knowledge and awareness focused on unscreened participants’ cancer stories; screened participants’ knowledge of CRC, risk factors, and screening; experiential learning from focus groups; and screened participants’ strategies to promote screening. Support and accessibility concentrated on physician support and responsibility to provide information, explanation, and recommend screening to facilitate access. Originality/value – Findings provide novel insights on socio-cultural context, beliefs, and barriers to CRC screening among SA immigrants. Culturally appropriate community-based strategies included story-telling, the use of social networks, and greater physician engagement. Enhancing collaborative partnerships with physicians and public health may minimize structural barriers and reduce health disparities. Future research could explore effectiveness of outreach strategies including these collaborations.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".