Strategies for Supporting Smoking Cessation Among Indigenous Fathers: A Qualitative Participatory Study
Bibliographic record
Abstract
There is a need for tailored smoking cessation programs specifically for Indigenous fathers who want to quit smoking.The aim of this study was to engage Indigenous men and key informants in guiding cultural adaptations to the Dads in Gear (DIG) cessation program. In Phase 1 of this qualitative participatory study, Indigenous men were engaged in group sessions and key informants in semistructured interviews to gather advice related to cultural adaptations to the DIG program. These data were used to guide the development of program prototypes. In Phase 2, the prototypes were evaluated with Indigenous fathers who were using tobacco (smoking or chewing) or were ex-users. Data were analyzed inductively. Recommendations for programming included ways to incorporate cultural values and practices to advance men's cultural knowledge and the need for a flexible program design to enhance feasibility and acceptability among diverse Indigenous groups. Men also emphasized the importance of positive message framing, building trust by providing "honest information," and including activities that enabled discussions about their aspirations as fathers as well as cultural expectations of current-day Indigenous men. That the Indigenous men's level of involvement with their children was diverse but generally less prescriptive than contemporary "involved fathering" discourse was also a key consideration in terms of program content. Strategies were afforded by these insights for meeting the men where they are in terms of their fathering-as well as their smoking and physical activity. This research provides a model for developing evidence-based, gender-specific health promotion programs with Indigenous men.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".