Recently eight major articles were published in peer reviewed journals that tested and supported fundamental theoretical, empirical, and practical applications of the Transtheoretical Model of Behavior Change (TTM). Using cutting edge methodologies these studies demonstrate how TTM is continuing to advance the field’s ability to understand, predict, and change risk behaviors critical to the prevention and management of chronic diseases. “These advances help drive Pro-Change’s research and development of new TTM programs,” stated Janice M. Prochaska, President & CEO of Pro-Change Behavior Systems, Inc.
Evaluating theories of behavior change: A Hierarchy of criteria applied to the Transtheoretical model
Critical Issue
- Organizes different criteria suggested by different scientific theorists
Abstract
The most common criteria recommended by philosophers of science for evaluating theories were organized within a hierarchy ranging from the least to the most risky tests for theories of health behavior change. The hierarchy progressed across: (1) Clarity; (2) Consistency; (3) Parsimony; (4) Testable; (5) Predictive Power; (6) Explanatory Power; (7) Productivity; (8) Generalisable; (9) Integration; (10) Utility; (11) Efficacy; and (12) Impact. The hierarchy was applied to the Transtheoretical Model (TTM) as an example of a health behavior change theory. The application was from the perspective of critics and advocates of TTM. Examples of basic and applied research challenging and supporting TTM across the hierarchy of criteria are presented. The goal is to provide a model for comparing alternative theories and to evaluate progress across the hierarchy within a particular theory. As theories meet criteria at each step in the hierarchy, the research and applications they generate can have increasing impacts on the science and practice of health behavior change.
Prochaska, J. O., Wright, J. A., & Velicer, W. F. (in press). Evaluating theories of behavior change: A Hierarchy of criteria applied to the Transtheoretical model. Applied Psychology: An International Review, 00, 00-00.
Testing Theory-Using Quantitative Predictions of Effect Size
Critical Issues
- Generates quantitative theoretical statements
- Provides means of testing specificity of a theory
Abstract
Traditional Null Hypothesis Testing procedures are poorly adapted to theory testing. The methodology can mislead researchers in several ways, including: (a) A lack of power can result in an erroneous rejection of the theory; (b) the focus on directionality (ordinal tests) rather than more precise quantitative predictions limits the information gained; and (c) the misuse of probability values to indicate effect size. An alternative approach is proposed which involves employing the theory to generate explicit effect size predictions that are compared to the effect size estimates and related confidence intervals to test the theoretical predictions. This procedure is illustrated employing the Transtheoretical Model. Data from a sample (N=3,967) of smokers from a large New England HMO system was used to test the model. There were a total of 15 predictions evaluated, each involving the relation between Stage of Change and one of the other 15 Transtheoretical Model variables. For each variable, omega-squared and the related confidence interval was calculated and compared to the predicted effect sizes. Eleven of the 15 predictions were confirmed, providing support for the theoretical model. Quantitative predictions represent a much more direct, informative, and strong test of a theory than the traditional test of significance.
Velicer, W.F., Cumming, G., Fava, J.L., Rossi, J.S., Prochaska, JO, & Johnson, J. L. (in press). Testing Theory-Using Quantitative Predictions of Effect Size. Applied Psychology: An International Review, 00, 00-00.
Validity of Stage Assessment in the Adoption and Maintenance of Physical Activity and Fruit and Vegetable Consumption
Critical Issue
- Strongly supports stage as non-linear change
Abstract
Objective. Stage assessments are examined to develop and test refined measurements that can be used for classifying individuals. Design. Stages were assessed in 1,850 persons in terms of their physical activity and dietary behaviors. Main Outcome Measures. Stages for both behaviors were compared to behavior and other test variables. Misclassification, sensitivity, specificity, Receiver-Operation- Curves, and discontinuity patterns were computed. Discontinuity patterns were tested with trends across stages and planned contrasts between adjacent stages. Results. In comparison to previous studies, sensitivity (70%-80%) and specificity (80%-87%) were high. When using lower level criteria (such as less intensive activity), sensitivity was lower, whereas specificity was higher. When behavioral maintenance was assessed, results suggested that the temporal cut-off point between Action and Maintenance was equally optimal at different cut-off points. Applying contrast analyses, nonlinear trends across the stages and a match of 87% of predictions of stage differences resulted. Conclusion. Stage assumptions are supported in general, and refined stage assessment in particular. Levels of psychological variables (e.g., easiness, habit) may discriminate stages as well as or even better than temporal stage definitions.
Lippke, S., Ziegelmann, J.P., Schwarzer, R. & Velicer, W.F. (in press). Validity of Stage Assessment in the Adoption and Maintenance of Physical Activity and Fruit and Vegetable Consumption. Health Psychology, 00, 00-00.
Stage and Non-stage Theories of Behavior and Behavior Change: A Comment on Schwarzer
Critical Issue
- Includes analogy to punctuated equilibrium Theory in Natural Sciences
Abstract
Schwarzer characterizes theories as being Continuum Models or Stage Models. We prefer the labels Theories of Behavior and Theories of Behavior Change. The stage concept is designed to represent the temporal dimension. In this way, individuals are viewed as evolving over time. Theories of behavior change also focus on dynamic variables, i.e. variables that are open to change while theories of behavior will focus on static variables. Schwarzer focuses on the Health Action Process Approach (HAPA), which distinguishes between pre-intentional motivational processes and post-intentional volition processes and makes a compelling case that theories of behavior change need to differentiate between at least two stages, motivation and action, if they are to fill the intention–behavior gap. In some HAPA studies, these two stages are expanded into three stages. The issue of how many stages there are and what are the best ways to represent, assess and treat the different stages represents an important research focus. This response discusses several reasons to believe that the stage differentiation of five stages included as part of the Transtheoretical Model is superior to the two- or three-stage model included as part of HAPA.
Velicer, W. F, & Prochaska, J. O. (2008). Stage and Non-stage Theories of Behavior and Behavior Change: A Comment on Schwarzer. Applied Psychology: An International Review, 57, 75-83.
Meta-Analytic Examination of the Strong and Weak Principles Across 48 Health Behaviors
Critical Issue
- TTM relation between stage and decisional balance replicates across 48 different behaviors
Abstract
Objective. The strong and weak principles of change state that progress from the precontemplation to the action stage of change is associated with a one standard deviation increase in the pros and a one-half standard deviation decrease in the cons of change. In this study these relationships, originally developed by Prochaska [Prochaska, J.O., 1994. Strong and weak principles for progressing from precontemplation to action on the basis of 12 problem behaviors. Health Psychology, 13, 47–51.] Based on an examination of 12 studies of 12 different behaviors, were re-examined using many more datasets and much more rigorous statistical methods. Methods. The current study analyzes 120 datasets from studies conducted between 1984 and 2003 across and within 48 health behaviors, including nearly 50,000 participants from 10 countries. The datasets were primarily analyzed utilizing metaanalytic techniques. Results. Despite the range of behaviors and populations, the results were remarkably consistent with the original results (pros=1.00 standard deviation, cons=0.56 standard deviation). Few potential moderators showed any impact on effect size distributions. Conclusions. This updated and enhanced examination of two important principles of behavior change is a significant contribution to the field of multiple health risk behaviors, as it clearly demonstrates the consistency of the theoretical principles across multiple behaviors, which has implications for developing multiple health risk behavior interventions.Hall, K., Rossi, J. S. (2008). Meta-Analytic Examination of the Strong and Weak Principles Across 48 Health Behaviors. Preventive Medicine, 46-266-274
Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions
Critical Issue
- Evaluates consistency of tailoring and stage effects across intervention studies
Abstract
Although there is a large and growing literature on tailored print health behavior change interventions, it is currently not known if or to what extent tailoring works. The current study provides a meta-analytic review of this literature, with a primary focus on the effects of tailoring. A comprehensive search strategy yielded 57 studies that met inclusion criteria. Those studies—which contained a cumulative N=58,454—were subsequently meta-analyzed. The sample size-weighted mean effect size of the effects of tailoring on health behavior change was found to be r = .074. Variables that were found to significantly moderate the effect included (a) type of comparison condition, (b) health behavior, (c) type of participant population (both type of recruitment and country of sample), (d) type of print material, (e) number of intervention contacts, (f) length of follow-up, (g) number and type of theoretical concepts tailored on, and (h) whether demographics and/or behavior were tailored on. Implications of these results are discussed and future directions for research on tailored health messages and interventions are offered.
Noar, S.M., Benac, C. N., & Harris, M. S. (2007). Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. Psychological Bulletin, 133, 673-693.
Demographic variables, smoking variables, and outcome across five studies
Critical Issue
- Compares stage effect to severity and demographic effects on intervention Outcomes
Abstract
Objective: Intervention effectiveness can potentially be affected by membership in different demographic subgroups (race, ethnicity, gender, age, and education level) or smoking behavior variables (time to first cigarette, longest previous quit attempt, number of attempts in the past year, number of cigarettes, and stage of change). Previous research on these 2 sets of variables has produced mixed results. Design: This secondary data analysis combined data from 5 effectiveness trials (a random digit- dial sample [N=1,358], members of an HMO [N=207], parents of students recruited for a school-based study [N=347], patients from an insurance provider list [N=535], and employees [N=175]) in which smokers were all proactively recruited from a defined population and all received the same expert system intervention. The intervention produced a consistent 22% to 26% point prevalence cessation rate across the 5 studies. Main Outcome Measures: The main outcome measures were 24-hr point prevalence, 7-day point prevalence, 30-day prolonged abstinence, and 6- month prolonged abstinence. Results: There were no significant differences in outcome across gender, race, and ethnicity subgroups. There were significant differences and small effect sizes for age and education subgroups. There were significant differences and large effect sizes for all 5 smoking behavior variables. Discussion: Demographic variables are static variables; whereas the smoking variables are more dynamic, that is, open to change. Given the dynamic nature of the smoking variables and the large effect sizes, interventions tailored on the smoking variables should be more successful.
Velicer, W. F, Redding, C. A., Sun, X. & Prochaska, J. O. (2007). Demographic variables, smoking variables, and outcome across five studies. Health Psychology, 26, 278-287.
Transtheoretical Model-based multiple behavior intervention for weight management: effectiveness on a population basis
Critical Issue
- Demonstrates Transtheoretical Model Tailoring produced significant change in multiple behavior related to healthy weight management.
Abstract
Background. The increasing prevalence of overweight and obesity underscores the need for evidence-based, easily disseminable interventions for weight management that can be delivered on a population basis. The Transtheoretical Model (TTM) offers a promising theoretical framework for multiple behavior weight management interventions. Methods. Overweight or obese adults (BMI 25–39.9; n=1277) were randomized to no-treatment control or home-based, stage-matched multiple behavior interventions for up to three behaviors related to weight management at 0, 3, 6, and 9 months. All participants were re-assessed at 6, 12, and 24 months. Results. Significant treatment effects were found for healthy eating (47.5% versus 34.3%), exercise (44.90% versus 38.10%), managing emotional distress (49.7% versus 30.30%), and untreated fruit and vegetable intake (48.5% versus 39.0%) progressing to Action/Maintenance at 24 months. The groups differed on weight lost at 24 months. Co-variation of behavior change occurred and was much more pronounced in the treatment group, where individuals progressing to Action/Maintenance for a single behavior were 2.5 to 5 times more likely to make progress on another behavior. The impact of the multiple behavior intervention was more than three times that of single behavior interventions. Conclusions. This study demonstrates the ability of TTM-based tailored feedback to improve healthy eating, exercise, managing emotional distress, and weight on a population basis. The treatment produced a high level of population impact that future multiple behavior interventions can seek to surpass.
Johnson, S. S., Paiva, A. L., Cummins, C. O., Johnson, J. L., Dyment, S. J., Wright, J. A., Prochaska, J. O., Prochaska, J. M., & Sherman, K. (2008). Transtheoretical Model-based multiple behavior intervention for weight management: effectiveness on a population basis. Preventive Medicine, 46, 238-246.