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