Dataset belonging to "Mechanisms of Change in a Go/No-Go Training Game for Young Adult Smokers"

DOI

Objective: Smoking is a major cause of worldwide morbidity and mortality. Evidence-based intervention programs to help young adults quit smoking are largely lacking; identifying targets for intervention is therefore critical. A candidate target is inhibitory control, with previous studies on Go/No-Go trainings showing behavior change in the food and alcohol domain. The current study examined the mechanisms of change of HitnRun, a Go/No-Go game, in a smoking population that was motivated to quit. Methods: A two-armed experimental study (n = 106) was conducted and young adults (Mage = 22.15; SDage = 2.59) were randomly assigned to either play HitnRun or to read a psychoeducational brochure. Prior to and directly following the intervention period, smoking-specific and general inhibitory control, perceived attractiveness of smoking pictures, and weekly smoking behavior were assessed. Results: Results indicate that Go/No-Go training seems to be effective in decreasing evaluations of smoking stimuli rather than top-down smoking-specific and general control processes. Similar reductions for weekly smoking were found in both groups. Conclusions: We conclude that HitnRun shows some promise, but more research and iterative design is needed to create a multi-component intervention for smoking cessation that is dynamically adjustable to the individual needs of young people.

Identifier
DOI https://doi.org/10.17026/dans-xs4-mypy
Metadata Access https://ssh.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-xs4-mypy
Provenance
Creator H. Scholten; M. Luijten; A. Poppelaars; M.C. Johnson-Glenberg; I. Granic
Publisher DANS Data Station Social Sciences and Humanities
Contributor RU Radboud University
Publication Year 2020
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact RU Radboud University
Representation
Resource Type Dataset
Format text/csv; text/xml; text/plain; application/x-stata-14; application/x-spss-sav; application/pdf; application/zip
Size 4164; 5898; 782; 29886; 134218; 49004; 261063; 23125
Version 2.1
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Construction Engineering and Architecture; Engineering; Engineering Sciences; Life Sciences; Medicine; Social Sciences; Social and Behavioural Sciences; Soil Sciences