Date of Award


Degree Type


Degree Name

Doctor of Philosophy in Psychology




Personal behavior accounts for much of the risk associated with chronic disease, thereby providing incentive for development of interventions that offer effective prevention on a large scale. Computer tailored interventions have become increasingly common for facilitating behavior change for a number of health concerns associated with chronic disease. Systematic reviews of tailoring have been completed but a sufficient number of outcomes are now available to facilitate the quantitative analysis of overall effect sizes for this type of intervention. The present study employs meta-analytic techniques to assess the mean effect for tailored interventions focusing on four health behaviors: smoking cessation, increase in physical activity, eating a healthy diet, and receiving regular mammography screening. Clinically and statistically significant overall effect sizes were found across each of the four behaviors. Retailored interventions were found to have increased efficacy over tailored interventions based on one assessment only. The addition of counselor calls to the feedback produced greater effects initially, but these were not sustained over time when compared to retailored interventions. A nonsignificant trend was found for effect sizes decreasing over time, with the most significant drops after six months postintervention. Mean effects did not differ by recruitment strategy and differences by theory or study group could not be adequately assessed due to sample size. Gender was the only demographic predictor associated with effect size. This analysis quantifies the effect of tailored interventions, demonstrating the ability to reach large numbers of people with effective techniques that promise to reduce chronic disease burden if implemented consistently.



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