Web-Based Smoking-Cessation Programs. Results of a Randomized Trial

Victor J. Strecher, Jennifer B. McClure, Gwen L. Alexander, Bibhas Chakraborty, Vijay N. Nair, Janine M. Konkel, Sarah M. Greene, Linda M. Collins, Carola C. Carlier, Cheryl J. Wiese, Roderick J. Little, Cynthia S. Pomerleau, Ovide F. Pomerleau

Research output: Contribution to journalArticlepeer-review

202 Scopus citations


Background: Initial trials of web-based smoking-cessation programs have generally been promising. The active components of these programs, however, are not well understood. This study aimed to (1) identify active psychosocial and communication components of a web-based smoking-cessation intervention and (2) examine the impact of increasing the tailoring depth on smoking cessation. Design: Randomized fractional factorial design. Setting: Two HMOs: Group Health in Washington State and Henry Ford Health System in Michigan. Participants: 1866 smokers. Intervention: A web-based smoking-cessation program plus nicotine patch. Five components of the intervention were randomized using a fractional factorial design: high- versus low-depth tailored success story, outcome expectation, and efficacy expectation messages; high- versus low-personalized source; and multiple versus single exposure to the intervention components. Measurements: Primary outcome was 7 day point-prevalence abstinence at the 6-month follow-up. Findings: Abstinence was most influenced by high-depth tailored success stories and a high-personalized message source. The cumulative assignment of the three tailoring depth factors also resulted in increasing the rates of 6-month cessation, demonstrating an effect of tailoring depth. Conclusions: The study identified relevant components of smoking-cessation interventions that should be generalizable to other cessation interventions. The study also demonstrated the importance of higher-depth tailoring in smoking-cessation programs. Finally, the use of a novel fractional factorial design allowed efficient examination of the study aims. The rapidly changing interfaces, software, and capabilities of eHealth are likely to require such dynamic experimental approaches to intervention discovery.

Original languageEnglish (US)
Pages (from-to)373-381
Number of pages9
JournalAmerican Journal of Preventive Medicine
Issue number5
StatePublished - May 2008

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Public Health, Environmental and Occupational Health


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