Evidence map›Paper›PMID 36627613›Full record

ArticleBMC public health2023

Lottery incentives for smoking cessation at the workplace: design and protocol of the smoke-free lottery - a cluster randomized trial.

Koen van der Swaluw, Marieke Hiemstra, Mattijs Lambooij, Eline Roordink, Nina van der Vliet, Else Zantinge, Karin Proper, Marcel Zeelenberg, Henriette M Prast

Abstract readClinical Trial Protocol
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Trial
  2. Promoting healthy behaviour with financial incentives: three challenges and solutions for large scale implementation.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Koen van der SwaluwNational Institute of Public Health and the Environment (RIVM), Centre for Nutrition, Prevention and Health Services, 3720, BA, Bilthoven, The Netherlands. koen.van.der.swaluw@rivm.nl.ORCID 0000-0001-6420-3446
Marieke HiemstraNational Institute of Public Health and the Environment (RIVM), Centre for Nutrition, Prevention and Health Services, 3720, BA, Bilthoven, The Netherlands.
Mattijs LambooijNational Institute of Public Health and the Environment (RIVM), Centre for Nutrition, Prevention and Health Services, 3720, BA, Bilthoven, The Netherlands.
Eline RoordinkNational Institute of Public Health and the Environment (RIVM), Centre for Nutrition, Prevention and Health Services, 3720, BA, Bilthoven, The Netherlands.
Nina van der VlietNational Institute for Public Health and the Environment (RIVM), Centre for Sustainability, Environment and Health, 3720, BA, Bilthoven, The Netherlands.
Else ZantingeNational Institute of Public Health and the Environment (RIVM), Centre for Health and Society, 3720, BA, Bilthoven, The Netherlands.
Karin ProperNational Institute of Public Health and the Environment (RIVM), Centre for Nutrition, Prevention and Health Services, 3720, BA, Bilthoven, The Netherlands.
Marcel ZeelenbergTilburg University, Department of Social Psychology, Tilburg School of Social and Behavioral Sciences, 5000, LE, Tilburg, the Netherlands.
Henriette M PrastTilburg University, 5000, LE, Tilburg, the Netherlands.

Funding

Rijksinstituut voor Volksgezondheid en Milieu S04000401
6 · The paper itself

Abstract

backgroundSmoking is the leading behavioral risk factor for the loss of healthy life years. Many smokers want to quit, but have trouble doing so. Financial incentives in workplace settings have shown promising results in supporting smokers and their design influences their impact. Lotteries that leverage behavioral economic insights might improve the effectiveness of workplace cessation support. METHODS AND

designWe examine in a cluster randomized trial if a workplace cessation group training paired with lottery deadlines will increase continuous abstinence rates over and above the cessation training alone. Organizations are randomized to either the control arm or lottery arm. The lotteries capitalize regret aversion by always informing winners at the deadline, but withholding prizes if they smoked. In the lottery-arm, winners are drawn out of all participants within a training group, regardless of their smoking status. In weeks 1-13 there are weekly lotteries. Winners are informed about their prize (€50), but can only claim it if they did not smoke that week, validated biochemically. After 26 weeks, there is a long-term lottery where the winners are informed about their prize (vacation voucher worth €400), but can only claim it if they were abstinent between weeks 13 and 26. The primary outcome is continuous abstinence 52 weeks after the quit date. DISCUSSION: There is a quest for incentives to support smoking cessation that are considered fair, affordable and effective across different socioeconomic groups. Previous use of behavioral economics in the design of lotteries have shown promising results in changing health behavior. This cluster randomized trial aims to demonstrate if these lotteries are also effective for supporting smoking cessation. Therefore the study design and protocol are described in detail in this paper. Findings might contribute to the application and development of effective cessation support at the workplace.

trial registrationNetherlands Trial Register Identifier: NL8463 . Date of registration: 17-03-2020.

Indexed as

MotivationSmoking CessationHealth BehaviorHumansRandomized Controlled Trials as TopicResearch DesignWorkplaceBehavioral economicsCommitment deviceDeadlinesIncentivesLotterySmoking cessationWorkplace

Identifiers

PMID36627613
PMCPMC9831882

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.