‘Imagine if I gave up smoking …’: a qualitative exploration of Aboriginal participants’ perspectives of a self-management pilot training intervention
Bibliographic record
Abstract
This paper reports on a pilot qualitative study investigating Aboriginal participants' perspectives of the Flinders Living Well Smoke Free (LWSF) 'training intervention'. Health workers nationally have been trained in this program, which offers a self-management approach to reducing smoking among Aboriginal clients. A component of the training involves Aboriginal clients volunteering their time in a mock care-planning session providing the health workers with an opportunity to practise their newly acquired skills. During this simulation, the volunteer clients receive one condensed session of the LWSF intervention imitating how the training will be implemented when the health workers have completed the training. For the purpose of this study, 10 Aboriginal clients who had been volunteers in the mock care-planning process, underwent a semi-structured interview at seven sites in Australia, including mainstream health services, Aboriginal community controlled health services and remote Aboriginal communities. The study aimed to gauge their perspectives of the training intervention they experienced. Early indications suggest that Aboriginal volunteer clients responded positively to the process, with many reporting substantial health behaviour change or plans to make changes since taking part in this mock care-planning exercise. Enablers of the intervention are discussed along with factors to be considered in the training program.
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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 | 0.024 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.016 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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".