Using Relational Agents to Promote Exercise and Sun Protection: Assessment of Participants' Experiences With Two Interventions.

BACKGROUND: Relational agents (RAs) are electronic computational figures designed to engage participants in the change process. A recent study, Project RAISE, tested the effectiveness of RAs, combined with existing computer-based interventions to increase regular exercise and sun protection behaviors. Results showed these interventions can be effective but need further development. OBJECTIVE: The purpose of this study was to examine participants' experiences using RAs to increase participant engagement and promote behavior change . METHODS: A qualitative approach was primarily utilized. A 25-question interview guide assessed different components of participants' experiences with the intervention, including motivation, engagement, satisfaction or dissatisfaction, quality of their interaction with the RA, and behavior change. Quantitative assessment of satisfaction was based on a scale of 1 to 10, with 1 representing least satisfied and 10 representing most satisfied. A summative analytic approach was used to assess individuals' qualitative responses. A single analysis of variance (ANOVA) examined levels of satisfaction by gender. RESULTS: Of the original 1354 participants enrolled in Project RAISE, 490 of 1354 (36%) were assigned to the RA group. A sample of 216 out of 490 (44%) participants assigned to the RA group completed the interventions, and follow-up assessments were contacted to participate in the semistructured interview. A total of 34 out of 216 (16%) completed the interview. Participants were motivated by, and satisfied with, the intervention. Participants viewed the RA as supportive, informative, caring, and reported positive behavior change in both exercise and sun protection. Some participants (15/34, 44%) noted the RA was less judgmental and less "overbearing" compared with a human counselor; other participants (12/34, 35%) said that the interaction was sometimes repetitive or overly general. The majority of participants (22/34, 65%) viewed the RA as an important contributor to their behavior change for exercise, sun protection, or both. Levels of satisfaction ranged between 7 and 10. There were no gender differences noted in levels of satisfaction (P=.51). CONCLUSIONS: RAs provide an innovative and attractive platform to increase exercise and sun protection behaviors and potentially other health behaviors.

Psychometric assessment of the processes of change scale for sun protection.

The fourteen-factor Processes of Change Scale for Sun Protection assesses behavioral and experiential strategies that underlie the process of sun protection acquisition and maintenance. Variations of this measure have been used effectively in several randomized sun protection trials, both for evaluation and as a basis for intervention. However, there are no published studies, to date, that evaluate the psychometric properties of the scale. The present study evaluated factorial invariance and scale reliability in a national sample (N = 1360) of adults involved in a Transtheoretical model tailored intervention for exercise and sun protection, at baseline. Invariance testing ranged from least to most restrictive: Configural Invariance (constraints only factor structure and zero loadings); Pattern Identity Invariance (equal factor loadings across target groups); and Strong Factorial Invariance (equal factor loadings and measurement errors). Multi-sample structural equation modeling tested the invariance of the measurement model across seven subgroups: age, education, ethnicity, gender, race, skin tone, and Stage of Change for Sun Protection. Strong factorial invariance was found across all subgroups. Internal consistency coefficient Alpha and factor rho reliability, respectively, were .83 and .80 for behavioral processes, .91 and .89 for experiential processes, and .93 and .91 for the global scale. These results provide strong empirical evidence that the scale is consistent, has internal validity and can be used in research interventions with population-based adult samples.

Intervention effects on stage transitions for adolescent smoking and alcohol use acquisition.

The health impacts of smoking and alcohol abuse have been long established with smoking representing one of the most preventable causes of disease and alcohol use the most popular psychoactive substance among adolescents. The current study evaluated stage of change progression in a large (N = 4,158) school-based, computer-delivered, transtheoretical model (TTM)-tailored multiple behavior intervention focused on preventing acquisition of smoking and alcohol use in adolescents. Assessments began in sixth grade and continued yearly until eighth grade, with a follow-up in ninth grade. Markov modeling was used to (a) characterize the best pattern of stage movement (e.g., no stage change, stage-sequential change, stages skipped), (b) test whether the identified pattern was stable over time (e.g., between assessments and after intervention completion), and (c) to determine whether the substance use prevention (SP) intervention effectively kept adolescents in acquisition stages (e.g., prevents stage movement toward substance use), relative to the comparison intervention. Major findings supported positive effects for both the intervention and comparison condition, which focused on energy balance (EB) behaviors and provided no direct intervention on substance use behaviors. Substantial differences in stage membership and transitions across intervention conditions highlighted the process of smoking and alcohol use acquisition in middle school students across each intervention condition. (PsycINFO Database Record

Intervention Effects on Stage of Change Membership and Transitions among Adolescent Energy Balance Behaviors.

The transition from childhood to adolescence is a crucial period for the development of healthy behaviors to be sustained later in life. With obesity a leading public health problem, the promotion of healthy behaviors has the potential to make a huge impact. The current study evaluated Stage of Change progression in a large (N = 4158) computer-delivered, Transtheoretical Model-tailored intervention focusing on physical activity and fruit and vegetable consumption (FV). Markov models were used to explore stage transitions and patterns of discrete change from sixth to ninth grade. Nested model comparisons examined the consistency of these patterns across time and intervention condition. Major findings supported models in which participants were free to transition forward and backward to any of the stages, but higher probabilities were observed for remaining in the same stage or for transitioning one or two stages forward. Participants in the intervention group had higher probabilities of transitioning toward Maintenance, with more change occurring relative to the comparison group during transitions from grades six to eight but not for grades eight to nine.

Assessing demographic differences in decisional balance for smoking prevention and temptations to try smoking among adolescent subgroups.

INTRODUCTION: Cigarette smoking initiation remains prevalent in adolescence. Effective prevention methods are needed to dissuade this behavior. Demographic factors are identified as important risk factors in the developmental nature of smoking in adolescence. The current study investigates potential demographic differences for two new trans-theoretical model measures, the Decisional Balance Inventory (pros and cons) for Smoking Prevention and the Temptations to Try Smoking Scale. METHODS: A sample of 6th grade Rhode Island students from 20 middle schools (N = 4151) who were participating in a longitudinal and computer-delivered intervention for substance abuse prevention was assessed on these measures at baseline. Three MANOVA tests were conducted to assess the impact of race (White vs. Non-White), ethnicity (Hispanic vs. Non-Hispanic) and gender (male vs female). RESULTS: Significant effects for race and ethnicity were found for Decisional Balance and Temptations to Try Smoking. For race, Whites reported lesser pros (p <.0001) and Non-Whites reported higher cons (p <.0001) and temptations to try smoking (p <.0001). Differences for ethnicity showed that Hispanics were higher on pros (p <.0001) and temptations to try smoking (p <.0001) than Non-Hispanics. Non-Hispanics reported higher cons (p <.0001). Gender differences were noted only for temptations to try smoking, and showed females were higher on this construct than males (p <.0001). The effect sizes were .01 or below. CONCLUSIONS: The results did not demonstrate a strong association between these demographics and constructs, suggesting that tailored prevention methods based solely on these factors may not dissuade smoking in this group.

Baseline Predictors of Singular Action Among Participants With Multiple Health Behavior Risks.

PURPOSE: Previous studies found that treatment effects can change two behaviors, but not one. This study examined baseline transtheoretical model constructs as three alternative predictors (stage of change, effort, and severity) of singular action among participants with co-occurring health behavior risks. DESIGN: The study examined participants at risk for three pairs of behaviors (sun and smoking; smoking and diet; and diet and sun). Analyses were conducted with participants who changed only one behavior in a pair (singular action). SETTING: School and home-based behavior change programs recruited participants via schools, worksites, and physician practices. School, worksite, medical, and home-based prevention programs were the study setting. SUBJECTS: The sample (N = 3213) was age 44.6 years (SD, 11.1 years), 94.6% white, and 63.7% female. MEASURES: Stages of change, effort, and severity variables were measured. ANALYSIS: Pooled data were analyzed using logistic regressions from three randomized controlled trials. RESULTS: Across all three behaviors, stage of change, effort, and severity effects were consistently related to behavior change at 24 months. Change efforts on one behavior were related to change on another behavior. Baseline sun severity (odds ratio, .97 [.94, 1.00]; p = .046) and smoking severity (odds ratio, .89 [.80, .98]; p = .019) were significant predictors of change on diet at final follow-up. CONCLUSION: Stage of change was the biggest predictor. Problem severity was the smallest predictor of change at 2-year follow-up. Four of six predictors were within behaviors, whereas two were between.

Fat Reduction Efforts: A 24-Month Longitudinal Comparison of a Large Sample of Maintainers, Relapsers, and Non-Changers.

This research examined dynamic transtheoretical model (TTM) constructs for dietary fat reduction. This secondary data analysis pooled three large population-based TTM-tailored school, worksite, medical, and home-based intervention studies and examined use of constructs across three groups organized by longitudinal progress (dynatypes): Maintainers, Relapsers, and Stable Non-Changers. The criteria for successful change, at the time, were that less than 30% of calories came from fat. A total of 2,718 adults met criteria for an unhealthy diet at baseline. The majority of participants were female, White, married, and middle-aged. Demographics, Stage of Change, Processes of Change, Decisional Balance, and Temptations were measured. Dynatype groups were assessed with reliable and valid scales assessing constructs at baseline and 6, 12, and 24 months. Analyses included a multivariate analysis of variance followed by a series of analyses of variance, with Tukey follow-up tests assessing differences in use of TTM constructs across the three groups at each time point. Relapsers and Maintainers were similar in their use of all TTM Processes of Change at baseline, with the exception of Self-Liberation (η(2) = 0.15, p < .001) and Reinforcement Management (η(2) = 0.01, p < .001). Although Relapsers reverted to an unhealthy diet, their overall greater use of Processes of Change suggests that their behaviors and strategy use remain better than that of the Stable Non-Changer group. Results suggest that specific cognitive and behavioral constructs may contribute differentially to intervention outcomes.

Extending Theory-Based Quantitative Predictions to New Health Behaviors.

BACKGROUND: Traditional null hypothesis significance testing suffers many limitations and is poorly adapted to theory testing. PURPOSE: A proposed alternative approach, called Testing Theory-based Quantitative Predictions, uses effect size estimates and confidence intervals to directly test predictions based on theory. METHOD: This paper replicates findings from previous smoking studies and extends the approach to diet and sun protection behaviors using baseline data from a Transtheoretical Model behavioral intervention (N = 5407). Effect size predictions were developed using two methods: (1) applying refined effect size estimates from previous smoking research or (2) using predictions developed by an expert panel. RESULTS: Thirteen of 15 predictions were confirmed for smoking. For diet, 7 of 14 predictions were confirmed using smoking predictions and 6 of 16 using expert panel predictions. For sun protection, 3 of 11 predictions were confirmed using smoking predictions and 5 of 19 using expert panel predictions. CONCLUSION: Expert panel predictions and smoking-based predictions poorly predicted effect sizes for diet and sun protection constructs. Future studies should aim to use previous empirical data to generate predictions whenever possible. The best results occur when there have been several iterations of predictions for a behavior, such as with smoking, demonstrating that expected values begin to converge on the population effect size. Overall, the study supports necessity in strengthening and revising theory with empirical data.

Transtheoretical Model Constructs' Longitudinal Prediction of Sun Protection Over 24 Months.

PURPOSE: This research examined dynamic transtheoretical model (TTM) constructs for adopting sun protection practices. This secondary data analysis pooled four large population-based TTM-tailored intervention studies and examined use of constructs across three groups, organized by longitudinal progress: maintainers, relapsers, and stable non-changers. METHODS: A total of 3463 adults, in the USA, who met criteria for unsafe sun exposure at baseline received a TTM-tailored computerized intervention at baseline, 6 months, and 12 months. The final analytic sample consisted of 1894 participants; the majority were female, White, married, and middle-aged. The three groups were assessed with reliable and valid scales assessing use of TTM constructs at baseline, 6 months, 12 months, and 24 months. Analyses included a MANOVA followed by a series of ANOVAs, with Tukey follow-up tests assessing differences in use of TTM constructs across the three groups at each timepoint. RESULTS: Findings demonstrated that relapsers and maintainers were similar in their use of most TTM processes of change at baseline, with the exception of Consciousness Raising, Stimulus Control, Reinforcement Management, and Self-Liberation. CONCLUSIONS: These findings suggest that although relapsers reverted to unsafe sun practices, their overall greater use of processes of change indicates that their change efforts remain better than that of stable non-changers.

Identifying Longitudinal Patterns for Individuals and Subgroups: An Example with Adherence to Treatment for Obstructive Sleep Apnea.

To improve complex behaviors such as adherence to medical recommendations, a better understanding of behavior change over time is needed. The focus of this study was adherence to treatment for obstructive sleep apnea (OSA). Adherence to the most common treatment for OSA is poor. This study involved a sample of 161 participants, each with approximately 180 nights of data. First, a time series analysis was performed for each individual. Time series parameters included the mean (average hours of use per night), level, slope, variance, and autocorrelation. Second, a dynamic cluster analysis was performed to find homogenous subgroups of individuals with similar adherence patterns. A four-cluster solution was found, and the subgroups were labeled: Great Users (17.2%; high mean and level, no slope), Good Users (32.8%; moderate mean and level, no slope), Low Users (22.7%; low mean and level, negative slope), and Slow Decliners (moderate mean and level, negative slope, high variance). Third, participants in the identified subgroups were compared to establish external validity. These steps represent a Typology of Temporal Patterns (TTP) approach. Combining time series analysis and dynamic cluster analysis is a useful way to evaluate longitudinal patterns at both the individual level and subgroup level.