Assessing the feasibility, acceptability and potential effectiveness of an integrated approach to smoking cessation for new and expectant fathers: The Dads in Gear study protocol
Bibliographic record
Abstract
BACKGROUND: Evidence related to the effects of tobacco exposure in pregnancy and on infant and child health have focused on women's smoking cessation. Less often addressed is men's smoking, which when continued in fatherhood, reduces the chances of female partners' cessation and can negatively impact children's health as well as men's health. Dads in Gear (DIG) is an innovative program designed specifically for new fathers who want to reduce and quit smoking that includes three components: smoking cessation, fathering, and physical activity. The over-arching purpose of this study is to evaluate the feasibility of the DIG program and provide estimates of program efficacy. The purpose of this article is to describe the rationale and protocol for evaluating the DIG program's feasibility, acceptability and potential effectiveness. METHODS: Using a prospective, non-comparative design, the DIG program will be implemented and evaluated in six communities. The program will be offered by trained facilitators to fathers who currently smoke and want to quit. The RE-AIM framework will guide the evaluation. Open-ended questions in participant surveys, and semi-structured interviews and weekly telephone de-briefs with facilitators will provide data for a process evaluation. Estimates of effectiveness include smoking behavior, fathering and physical activity measures at baseline, end of program, and 3-month follow up. CONCLUSION: The DIG program could support positive changes with respect to smoking cessation, physical activity and overall health for men. These effects could also promote family health. The program might also provide an effective model for engaging men in other health behavior change.
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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 | 0.062 | 0.038 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.037 | 0.008 |
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".