Date of Award

2004

Degree Type

Dissertation

Degree Name

Doctor of Philosophy in Psychology

Department

Psychology

First Advisor

Joseph S. Rossi

Abstract

Interventions to decrease unhealthy behaviors and to increase healthy behaviors are crucial for health promotion and disease prevention. Computerized tailored interventions provide a promising approach for creating positive health behavior change. The Transtheoretical Model (TTM) delineates a way to conceptualize behavior change, provides the foundation for developing assessments of an individual's readiness to change, and is utilized in tailoring interventions for actualizing behavior change. To produce optimally tailored interventions: (1) theory that guides interventions needs to be comprehensively tested; and (2) empirical data that drive the tailored interventions needs to be systematically generated. This program of research tests theoretical assumptions of the model and begins to outline necessary tailoring data, and does so in three main phases: (1) comparison of effect size procedures; (2) cross-sectional meta-analytic investigation of the Stages of Change and Decisional Balance; and (3) a cross-sequential cross-validation study of the cross-sectional study.

In meta-analyses, essential information for calculating effect size is often missing in published studies. Such missing data precludes the inclusion of studies in the meta-analysis thereby introducing bias to the review. Methods to utilize as much data as possible are invaluable to meta-analytic work. A comparison of effect size procedures was conducted in order to identify a bias correction for studies otherwise unusable. The study included 38 studies, with a total of 46 datasets for each of the Decisional Balance measures. Hedge 's g provided a 10% larger effect size than a standard score method of effect size estimation for both the Pros and Cons measures. A single correction equation was developed to allow the use of standard score estimation in future meta-analytic work with these constructs.

The second phase of this program of research utilized meta-analytic procedures with longitudinal data to examine 146 datasets across 55 behaviors spanning 18 countries and including 85,272 participants. This study identified a 2-factor structure for the Pros and Cons in 96% of the studies, with a crossover occurring before the Action Stage in the majority of studies. Overall magnitudes of

effect were larger in the earlier Stages for Pros and in the later Stages for Cons. Heterogeneity of effect size distribution was found and moderators assessed. Generalizability of these constructs were supported, especially across behaviors and populations. Moderators of effect were found to be differentially related across particular Stage transitions but in no readily apparent pattern.

Thirdly, longitudinal changes in Decisional Balance across the Stages of Change were assessed across the Stage transitions using a cross-sequential approach. Overall magnitudes of effect were somewhat larger for the longitudinal data. Similar magnitudes of effects for cross-sectional adjacent stage transitions and longitudinal stage movements in the early stages were found between cross-sectional and cross-sequential profile for the two behaviors examined.

Overall, the use of preexisting studies can lead to groundbreaking empirical data for the development of more comprehensive and more precisely tailored health prevention and disease prevention interventions and further research will continue to delineate important patterns of relationships between these variables.

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