- Design
- Four-arm randomised clinical trial at 5 US centres
- Population
- 3,220 underserved adults who smoked, referred for lung cancer screening
- Primary outcome
- Biochemically confirmed sustained abstinence through 6 months
- Effect
- 8.8% with incentives vs 4.3% usual care; difference 4.6% (95% CI 2.1 to 7.0)
A four-arm randomised trial at five US centres enrolled 3,220 current smokers referred for lung cancer screening who were Black, Hispanic, rural or of low income. All received ask-advise-refer. Arms then added free nicotine replacement or reimbursed varenicline or bupropion; free medicines plus up to US$600 for biochemically confirmed abstinence; or both plus a mobile health tool.
Sustained, biochemically confirmed abstinence at six months was 4.3% with advice and referral, 5.1% with free medicines, 8.8% with incentives and 7.2% with incentives plus the app. Incentives beat usual care by 4.6 percentage points (95% CI 2.1 to 7.0). Free medicines alone added 0.5 points, which was not significant.
The lesson for any clinician is that offering medicines is not the same as people using them, and that rewarding the outcome moved more people. Absolute quit rates stayed low in every arm.
Cash incentive schemes do not exist in most Indian settings, but the finding still argues for active follow-up rather than a one-off referral, and for biochemical or carbon monoxide confirmation where programmes can offer it.
- Ask every smoker about tobacco at screening and follow-up visits, not just once
- Do not assume a prescription for cessation medicine means it was collected or taken; ask at the next visit
- Where a programme offers incentives for confirmed quitting, refer to it
- Combine medicine with behavioural support and a follow-up date rather than referral alone
- Use a lung cancer screening visit as a cessation opportunity; quitting is the bigger benefit
Why it matters
It challenges the assumption that removing cost is enough to get people using cessation medicines.
Don't overread it
The trial tested US cash incentives in specific underserved groups; the size of effect may not transfer elsewhere.
The statistics, in plain English
A 4.6-point gain sounds small, but it is a doubling from a 4.3% baseline, and the confidence interval (2.1 to 7.0) excludes no effect. The free-medicine interval (−1.7 to 2.6) includes zero, so that arm showed no clear benefit.
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