Teaching tools to engage Anishinaabek First Nations women in cervical cancer screening: Report of an educational workshop
Bibliographic record
Abstract
OBJECTIVE: To explore educational strategies for engaging First Nations women in Canada to attend cervical cancer screening. DESIGN: Within a participatory action research framework, semi-structured interviews with health-care providers in First Nations communities revealed that education about the value of screening is perceived as being a key factor to promote cervical cancer screening. SETTING: To obtain feedback from workshop informants, a 1-day educational workshop was held to identify appropriate educational intervention strategies, which would be applied in a forthcoming randomised controlled cervical screening trial. METHODS: Common discussion and discussion groups, which were facilitated by a First Nations workshop moderator and a note taker. RESULTS: This workshop helped to strengthen the ethical space dialogue with the First Nations communities with whom the study team had established research partnerships. The workshop atmosphere was relaxed and the invited informants decided that an educational health promotion event for community women needed to be held prior to inviting them to the cervical screening trial. Such an event would provide an opportunity to communicate the importance of attending regular cervical screening allowing women to make informed decisions about screening participation. Complementary promotional items, including an eye-catching pamphlet and storytelling, were also suggested. CONCLUSION: The key messages from the events and promotional items can help to destigmatise women who develop a type of cancer that is caused by a sexually transmitted virus that affects both men and women. Developing and implementing positive health education that respectfully depicts female bodies, sexuality and health behaviours through a First Nations lens is strongly warranted.
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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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".