Beyond Quitting: Any Additional Impact of Mailing Free Nicotine Patches to Current Smokers?
Bibliographic record
Abstract
With smoking being the leading cause of preventable mortality,1 there is a great need to develop effective means to promote tobacco cessation. One method, mailing free nicotine patches through mass distribution initiatives, has proved popular in both United States and Canada.2,3 Further, mailing nicotine patches without behavioral support has been found to promote tobacco cessation when compared to participants randomized into a no intervention control group at a 6-month follow-up (30-day abstinence: 7.6% vs. 3.0%; odds ratio [OR], 2.65; 95% confidence interval [CI], 1.44 to 4.89, p = .002).4 While promoting abstinence is the gold standard in tobacco cessation initiatives, does mailing nicotine patches to those interested have additional benefits even among those who do not succeed at quitting?5–7 In our trial (ClinicalTrials.gov # NCT01429129),4,8 we recruited 2093 current adult smokers (10 or more cigarettes per day) using a random digit dialling telephone survey who were willing to take part in a baseline, 8-week, and 6-month longitudinal survey (participants paid $20 at each time point). As part of the baseline survey, we asked a series of hypothetical questions to identify participants who would be interested in receiving free nicotine patches, would use them to try to quit smoking within 1 week of receiving them, and would be willing to have them mailed to their home. Of these participants, those who did not report any health contraindications to using nicotine patches (n = 999) were randomized into two conditions—a condition where they were told that we actually had a supply of free nicotine patches (5 weeks per person) and could mail it to their home (n = 500; all said yes), or a no intervention condition (n = 499) that was not told about nicotine patches and had no awareness that anyone else was receiving patches. All participants were then followed up at 8 weeks and 6 months. Beyond assessing abstinence at these time points (7-day abstinence at 8 weeks and 30-day abstinence at 6 months),4 we asked if current smoking participants had made a serious quit attempt (for at least 24 hours), were intending to quit in the next 30 days, and the number of cigarettes per day that they were currently smoking. Analyses were conducted using an intention-to-treat approach and with missing data replaced with the last available value carried forward. Analyses reported here exclude participants reporting abstinence at each time point (pattern of outcomes are the same when these participants were included—not reported here; no significant differences observed at baseline). Compared to those who did not receive free nicotine patches, participants who received the patches reported an increased likelihood of a serious quit attempt, and intending to quit in the next 30 days, at both 8 weeks and 6 months (Quit attempts: 8 weeks: OR = 5.00; 95%CI, 3.61 to 6.90; p < .001; 6 months: OR = 2.96; 95%CI, 2.22 to 3.94; p < .001; intent to quit: OR = 2.28; 95%CI, 1.73 to 3.00, p < .001; 6 months: OR = 1.47; 95%CI, 1.05 to 1.89, p = .023). Further, those who received nicotine patches reported smoking fewer cigarettes per day compared to those in the no intervention control group (8 weeks: mean [SD], 12.99 [9.28] vs. 17.33 [8.76] cigarettes per day; Exp(β) = 0.75 [95%CI, 0.66 to 0.86]; p < .001; 6 months: mean [SD], 13.17 [9.72] vs. 16.04 [9.16] cigarettes per day; Exp(β) = 0.82 [95%CI, 0.72 to 0.94]; p = .003). The provision of free nicotine patch by mail appears to have secondary benefits beyond promoting abstinence that are supportive of tobacco cessation objectives. These findings provide additional evidence of the benefits of mass distribution initiatives as well as the effectiveness of nicotine patches to promote tobacco cessation, even when behavioral support is not provided. This research is funded by the Canadian Institutes of Health Research (CIHR). RFT and JAC are Canada Research Chairs funded by Health Canada. STL is a Chair in Applied Public Health funded by the Public Health Agency of Canada (PHAC) in partnership with Canadian Institutes of Health Research (CIHR) Institute of Neurosciences, Mental Health and Addiction (INMHA) and Institute of Population and Public Health (IPPH). Support to CAMH for salary of scientists and infrastructure has been provided by the Ontario Ministry of Health and Long Term Care. JAC, VK, LZ, and SL have no conflicts of interest to declare. RFT declares that, in the past 3 years, she has consulted with Apotex on topics unrelated to smoking cessation. PS has received grant/research funding from Pfizer Inc., Pfizer Canada Inc., and Shoppers Drug Mart. Speakers’ bureau fees were received from Pfizer Inc. Canada, Pfizer Global, and ABBVie. Furthermore, Dr. Selby has received consulting fees from Pfizer Inc., Pfizer Canada Inc., Pfizer Global, NABI Pharmaceuticals, and V-CC Systems Inc. JAC and VK had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. We acknowledge the support of CAMH and the CAMH foundation, the Canada Foundation for Innovation (#20289 and #16014), the Ontario Ministry of Research. The views expressed in this article do not necessarily reflect those of the Ministry of Health and Long Term Care.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.063 | 0.002 |
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".