144 Transtheoretical Individualized Multimedia Expert Systems Targeting Adolescents' Health Behaviors Colleen A. Redding, James O. Prochaska, Unto E. Pallonen,Joseph S. Rossi, Wayne E Velicer, Susan R. Rossi, Geoffrey W. Greene, Kathryn S. Meier, Ker~ T E. Evers, Brett A. Plummet, and Jason E. Maddock, Cancer Prevention Research Center, University of Rhode Island The transtheoretical model has advanced research and practice for many health behavior changes among adults, but few applica- tions have been developed and applied among adolescents. This paper will describe an innovative and promising computer-based technology for standardized assessment and individualized theory-based intervention delivery called expert systems. Two different studies utilizing multimedia expert systems technologyfor assessing and intervening with adolescents targeting several health behav- iors will be described. One study includes high school students and targets smoking cessation or prevention, sun protection, and di- etarf fat reduction. The other study includes urban adolescentfemale clients recruited in family planning clinics and targets condom adoption and either smoking cessation or prevention. The advantages and disadvantages of expert systems technology are reviewed. Multimedia expert system technology has the potential to enhance health promotion and adherence by integrating the strongest com- ponents from both clinical and public health models of intervention. T HIS PAPERwill describe the development and appli- cation of current computer-based expert system in- tervention delivery systems being utilized and evaluated in different randomized clinical trials (RCT) targeting different adolescent populations. First, the transtheoreti- cal model that provides the theoretical foundation for expert systems and these RCTs wilt be described. A de- scription of expert systems in general and a rationale for utilizing these systems among adolescents, in particular, will be presented. Then, the studies that are using this technology will be described, as well as some of the con- textual factors influencing expert systems use in different settings. Finally, some of the main strengths and weak- nesses of expert systems as both research and clinical tools will be summarized. Transtheoretical Model The past 20 years of transtheoretical model-based re- search has found some common principles of behavior change which have applied to a wide range of health be- haviors. These behaviors include smoking cessation, ex- ercise adoption, sun protection, dietary fat reduction, condom adoption, adherence to mammography screen- ing, medication adherence, stress management, and sub- stance abuse cessation, to name just a few (Prochaska & DiClemente, 1983, 1985; Prochaska, Norcross, Fowler, Fol- lick, & Abrams, 1992; Prochaska, Redding, Harlow, Rossi, Cognitive and Behavioral Practice 6, 144-153, 1999 1077-7229/99/144-15351.00/0 Copyright © 1999 by Association for Advancement of Behavior Therapy. All rights of reproduction in any form reserved. & Velicer, 1994; Prochaska & Velicer, 1997). These prob- lem behaviors are important from a public health stand- point because they are strongly associated with both in- creased mortality and with decreased quality of life. The TTM is a model of intentional behavior change that has produced a large volume of research and service across a wide range of problem behaviors and populations (Pro- chaska & DiClemente, 1983, 1985; Prochaska et al., 1992, 1994; Prochaska & Velicer, 1997). This model describes the relationships among stages of change, processes of change, decisional balance or the pros and cons of change, situa- tional confidence or self-efficacy in the behavior change, and situational temptations to relapse. Table 1 describes all the constructs that collectively comprise the TTM. This model has several advantages. First, it describes behavior change as a process as opposed to an event. Then, by breaking the change process down into stages and studying which variables are most strongly associated with progress through the stages, this model provides im- portant tools for both research and intervention develop- ment. Across different problem behaviors and popula- tions, different variables have been associated with stage movement for each stage of change (Prochaska, Velicer, Guadagnoli, Rossi, & DiClemente, 1991). These TTM findings inform the design of individualized stage- matched expert system interventions that target those variables most predictive of progress for individuals at each stage of change. One aspect of this model that often goes unrecognized is that it is the processes of change that drive movement through the stages of change (Prochaska & DiClemente, 1984). Thus, although com- monly referred to as the "Stages of Change Model,"