Lutter contre le tabac et promouvoir l'allaitement au Québec : un défi
Bibliographic record
Abstract
Quebec's breastfeeding rates are in a deplorable state, and even more so for smoking mothers. Public health providers are trying to increase breastfeeding rates and decrease smoking in this specific target group. Should they prioritise tobacco cessation interventions, or breastfeeding promotion interventions, or give equal priority to both goals at the same time? The authors attempt to scientifically answer this question, through a comprehensive literature review over the last ten years. In general, women who smoke have the tendency be younger, be less educated and more underprivileged than mothers who do not smoke and to breastfeed less often. Smoking mothers who do breastfeed usually wean off breastfeeding earlier than those who do not smoke. Pregnancy is considered an ideal moment to stop smoking, but relapse after giving birth is very high. In light of the range of difficulties faced when trying to quit smoking, health professionals should encourage smoking mothers to breastfeed since the benefits of breastfeeding could actually serve to reduce some of the harmful effects related to tobacco. Nicotine patches can be prescribed to increase the chances for successful tobacco cessation amongst these mothers. To date, few studies have been carried out on nicotine replacement therapies and breastfeeding smokers. More research is needed to evaluate the risks and benefits of nicotine substitutes for this sub-group, in both the short and long term.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".