A meta-analysis of computer-tailored interventions for health behavior change

Abstract

Objective: Computer-tailored interventions have become increasingly common for facilitating improvement in behaviors related to chronic disease and health promotion. A sufficient number of outcome studies from these interventions are now available to facilitate the quantitative analysis of effect sizes, permitting moderator analyses that were not possible with previous systematic reviews.

Method: The present study employs meta-analytic techniques to assess the mean effect for 88 computer-tailored interventions published between 1988 and 2009 focusing on four health behaviors: smoking cessation, physical activity, eating a healthy diet, and receiving regular mammography screening. Effect sizes were calculated using Hedges g. Study, tailoring, and demographic moderators were examined by analyzing between-group variance and meta-regression.

Results: Clinically and statistically significant overall effect sizes were found across each of the four behaviors. While effect sizes decreased after intervention completion, dynamically tailored interventions were found to have increased efficacy over time as compared with tailored interventions based on one assessment only. Study effects did not differ across communication channels nor decline when up to three behaviors were identified for intervention simultaneously.

Conclusion: This study demonstrates that computer-tailored interventions have the potential to improve health behaviors and suggests strategies that may lead to greater effectiveness of these techniques.

Conflict of interest statement

Conflict of Interest Statement James O. Prochaska is founder of and consultant to ProChange Behavior Systems, Inc., which develops and disseminates tailored interventions.

Copyright © 2010 Elsevier Inc. All rights reserved.

Figures

Figure 1

Trends in effect size over outcome time point

Figure 2

Trends in effect size over outcome time point by tailoring method