A pragmatic, randomized, controlled study evaluating the impact of access to smoking cessation pharmacotherapy coverage on the proportion of successful quitters in a Canadian population of smokers motivated to quit (ACCESSATION)
Bibliographic record
Abstract
BACKGROUND: Many smokers find the cost of smoking cessation medications a barrier. Financial coverage for these medications increases utilization of pharmacotherapies. This study assesses whether financial coverage increases the proportion of successful quitters. METHODS: A pragmatic, open-label, randomized, controlled trial was conducted in 58 Canadian sites between March 2009 and September 2010. Smokers (≥10 cigarettes/day) without insurance coverage who were motivated to quit within 14 days were randomized (1:1) in a blinded manner to receive either full coverage eligibility for 26 weeks or no coverage. Pharmacotherapies covered were varenicline, bupropion, or nicotine patches/gum. Investigators/subjects were unblinded to study group assignment after randomization and prior to choosing a smoking cessation method(s). All subjects received brief smoking cessation counseling. The primary outcome measure was self-reported 7-day point prevalence of abstinence (PPA) at week 26. RESULTS: Of the 1380 randomized subjects (coverage, 696; no coverage, 684), 682 (98.0%) and 435 (63.6%), respectively, were dispensed at least one smoking cessation medication dose. The 7-day PPA at week 26 was higher in the full coverage versus no coverage group: 20.8% (n = 145) and 13.9% (n = 95), respectively; odds ratio (OR) = 1.64, 95% confidence interval (CI) 1.23-2.18; p = 0.001. Urine cotinine-confirmed 7-day PPA at week 26 was 15.7% (n = 109) and 10.1% (n = 69), respectively; OR = 1.68, 95% CI 1.21-2.33; p = 0.002. After pharmacotherapy, coverage eligibility was withdrawn from the full coverage group, continuous abstinence between weeks 26 and 52 was 6.6% (n = 46) and 5.6% (n = 38), in the full coverage and no coverage groups, respectively; OR = 1.19, 95% CI 0.76-1.87; p = 0.439. CONCLUSIONS: In this study, the adoption of a smoking cessation medication coverage drug policy was an effective intervention to improve 26-week quit rates in Canada. The advantages were lost once coverage was discontinued. Further study is required on the duration of coverage to prevent relapse to smoking. (clinicaltrials.gov identifier: NCT00818207; the study was sponsored by Pfizer Inc.).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".