Socioeconomic predictors of smoking cessation in a worldwide online smoking cessation trial

Julia I. Bravin, Eduardo L. Bunge, Benjamin Evare, Robert E. Wickham, Eliseo J. Pérez-Stable, Ricardo F. Muñoz

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Objective: This article studies the impact of country level and individual level socioeconomic factors as predictors of smoking cessation from a worldwide online smoking cessation participant preference study conducted from 2008 to 2011. Method: We collected data through the San Francisco Stop Smoking Internet website. A total of 13,620 adult smokers from 109 countries and territories entered the study. Participants were able to choose from among nine components. Once selected, participants had access to their customized homepage that displayed a navigation bar with only the selected elements. The intervention was designed to take up to 8 weeks to complete. Participants received emails to complete follow-up assessments at 1, 3, 6, and 12 months after enrolling in the study. Results: Of those who provided data at any follow-up (n = 4678), 38.3% reported quitting smoking for at least seven days at one of the follow-ups. Multilevel logistic regression models demonstrated that greater gross domestic product (GDP) per capita, higher level of individual education, and subjective socioeconomic status, significantly predicted the likelihood of quitting at 1-month follow-up. Conclusions: Higher socioeconomic status at country and individual levels are associated with greater success in online smoking interventions. Future studies should address this disparity.

Original languageEnglish (US)
Pages (from-to)410-418
Number of pages9
JournalInternet Interventions
Volume2
Issue number4
DOIs
StatePublished - Nov 1 2015
Externally publishedYes

Keywords

  • GDP
  • Global health disparities
  • Internet intervention
  • Smoking cessation
  • Socioeconomic predictors
  • Subjective perceptions of social standing

ASJC Scopus subject areas

  • Health Informatics

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