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 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.

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.

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.

Randomized trial outcomes of a TTM-tailored condom use and smoking intervention in urban adolescent females.

Smoking and sexual risk behaviors in urban adolescent females are prevalent and problematic. Family planning clinics reach those who are at most risk. This randomized effectiveness trial evaluated a transtheoretical model (TTM)-tailored intervention to increase condom use and decrease smoking. At baseline, a total of 828 14- to 17-year-old females were recruited and randomized within four urban family planning clinics. Participants received TTM or standard care (SC) computerized feedback and stage-targeted or SC counseling at baseline, 3, 6 and 9 months. Blinded follow-up telephone surveys were conducted at 12 and 18 months. Analyses revealed significantly more consistent condom use in the TTM compared with the SC group at 6 and 12, but not at 18 months. In baseline consistent condom users (40%), significantly less relapse was found in the TTM compared with the SC group at 6 and 12, but not at 18 months. No significant effects for smoking prevention or cessation were found, although cessation rates matched those found previously. This TTM-tailored intervention demonstrated effectiveness for increasing consistent condom use at 6 and 12 months, but not at 18 months, in urban adolescent females. This intervention, if replicated, could be disseminated to promote consistent condom use and additional health behaviors in youth at risk.

Comparing Visual and Statistical Analysis in Single-Case Studies Using Published Studies.

Little is known about the extent to which interrupted time series analysis (ITSA) can be applied to short, single-case study designs and whether those applications produce results consistent with visual analysis (VA). This article examines the extent to which ITSA can be applied to single-case study designs and compares the results based on two methods: ITSA and VA, using papers published in the Journal of Applied Behavior Analysis in 2010. The study was made possible by the development of software called UnGraph®, which facilitates the recovery of raw data from the graphs. ITSA was successfully applied to 94% of the examined graphs with the number of observations ranging from 8 to 136. Moderate to high lag-1 autocorrelations (>.50) were found for 46% of the data series. Effect sizes similar to group-level Cohen's d were identified based on the tertile distribution. Effects ranging from 0.00 to 0.99 were classified as small, those ranging from 1.00 to 2.49 as medium, and large effect sizes were defined as 2.50 or greater. Comparison of the conclusions from VA and ITSA had a low level of agreement (Kappa =.14, accounting for the agreement expected by chance). The results demonstrate that ITSA can be broadly implemented in applied behavior analysis research. These two methods should be viewed as complementary and used concurrently.

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.

Transtheoretical Principles and Processes for Adopting Physical Activity: A Longitudinal 24-Month Comparison of Maintainers, Relapsers, and Nonchangers.

This study examined longitudinal differences in use of transtheoretical model (TTM) behavior change constructs in maintainers (who reached and maintained exercise guidelines), relapsers (who reached guidelines, then regressed), and nonchangers (who did not reach guidelines). Data from two population-based TTM-tailored randomized trial intervention groups targeting exercise behavior (N = 1050) were pooled, and analyses assessed differences in TTM constructs between the three groups at baseline, 12 months, and 24 months. Findings indicated that relapsers tended to use TTM variables similarly to maintainers with the exception of self-efficacy, consciousness raising, and most behavioral processes of change, at 24 months. Nonchangers, however, used all TTM variables less than maintainers at nearly every time point. Findings suggest that relapsers remain more active than nonchangers in terms of use of change processes. Poor response to interventions (nonchangers) may be predicted by low baseline engagement in change processes. Although relapsers reverted to physical inactivity, their overall greater use of TTM constructs suggests that their efforts to change remain better than those of the stable nonchanger group. Future research can focus on treatment engagement strategies to help the stable nonchangers initiate change and to help relapsers to maintain treatment gains.

Automated indexing of Internet stories for health behavior change: weight loss attitude pilot study.

BACKGROUND: Automated health behavior change interventions show promise, but suffer from high attrition and disuse. The Internet abounds with thousands of personal narrative accounts of health behavior change that could not only provide useful information and motivation for others who are also trying to change, but an endless source of novel, entertaining stories that may keep participants more engaged than messages authored by interventionists. OBJECTIVE: Given a collection of relevant personal health behavior change stories gathered from the Internet, the aim of this study was to develop and evaluate an automated indexing algorithm that could select the best possible story to provide to a user to have the greatest possible impact on their attitudes toward changing a targeted health behavior, in this case weight loss. METHODS: An indexing algorithm was developed using features informed by theories from behavioral medicine together with text classification and machine learning techniques. The algorithm was trained using a crowdsourced dataset, then evaluated in a 2×2 between-subjects randomized pilot study. One factor compared the effects of participants reading 2 indexed stories vs 2 randomly selected stories, whereas the second factor compared the medium used to tell the stories: text or animated conversational agent. Outcome measures included changes in self-efficacy and decisional balance for weight loss before and after the stories were read. RESULTS: Participants were recruited from a crowdsourcing website (N=103; 53.4%, 55/103 female; mean age 35, SD 10.8 years; 65.0%, 67/103 precontemplation; 19.4%, 20/103 contemplation for weight loss). Participants who read indexed stories exhibited a significantly greater increase in self-efficacy for weight loss compared to the control group (F1,107=5.5, P=.02). There were no significant effects of indexing on change in decisional balance (F1,97=0.05, P=.83) and no significant effects of medium on change in self-efficacy (F1,107=0.04, P=.84) or decisional balance (F1,97=0.78, P=.38). CONCLUSIONS: Personal stories of health behavior change can be harvested from the Internet and used directly and automatically in interventions to affect participant attitudes, such as self-efficacy for changing behavior. Such approaches have the potential to provide highly tailored interventions that maximize engagement and retention with minimal intervention development effort.

Outcomes of cluster profiles within stages of change for sun protection behavior.

OBJECTIVE: Predictive and external validity was studied among cluster profiles for sun protection behavior within stages from Transtheoretical Model of behavior change using follow-up data. METHODS: Data from participants in a home-based expert system were analyzed. Longitudinal patterns of clusters on the precontemplation, contemplation, and preparation stages of change were assessed. Differences between clusters on membership in action/maintenance stages and scores on the Sun Protection Behavior Scale (SPBS) were measured at 12 and 24 months after intervention. RESULTS: Differences between clusters on stage progression and on scores from the SPBS were found at 12 and 24 months after intervention at all stages. DISCUSSION: Predictive and external validity of sun protection subtypes was established using sun protection variables after a stage-matched intervention. Results provide information to improve interventions for sun protection.

Treated individuals who progress to action or maintenance for one behavior are more likely to make similar progress on another behavior: coaction results of a pooled data analysis of three trials.

OBJECTIVE: This study compared, in treatment and control groups, the phenomena of coaction, which is the probability that taking effective action on one behavior is related to taking effective action on a second behavior. METHODS: Pooled data from three randomized trials of Transtheoretical Model (TTM) tailored interventions (n=9461), completed in the U.S. in 1999, were analyzed to assess coaction in three behavior pairs (diet and sun protection, diet and smoking, and sun protection and smoking). Odds ratios (ORs) compared the likelihood of taking action on a second behavior compared to taking action on only one behavior. RESULTS: Across behavior pairs, at 12 and 24 months, the ORs for the treatment group were greater on an absolute basis than for the control group, with two being significant. The combined ORs at 12 and 24 months, respectively, were 1.63 and 1.85 for treatment and 1.20 and 1.10 for control. CONCLUSIONS: The results of this study with addictive, energy balance and appearance-related behaviors were consistent with results found in three studies applying TTM tailoring to energy balance behaviors. Across studies, there was more coaction within the treatment group. Future research should identify predictors of coaction in more multiple behavior change interventions.

Factor structure of decisional balance and temptations scales for smoking: cross-validation in urban female African-American adolescents.

BACKGROUND: The transtheoretical model is an influential theoretical model in health psychology, particularly in its application to smoking cessation research. Decisional Balance (DB) and Temptations are key constructs within this framework. PURPOSE: This study examines the psychometric properties of the DB and Temptations scales for smoking in a predominantly African-American sample of urban adolescent girls. METHODS: We used confirmatory factor analysis to compare the fit of previously published factor structures in smokers (n = 233) and nonsmokers (n = 598). External validity was tested by examining stages of change differences in the retained subscales. RESULTS: Results supported the internal and external validity of the DB scale for smokers and nonsmokers. Notably, previously published three-factor (Social Pros, Coping Pros, Cons) and four-factor (Cons split into "Aesthetic Cons" and "Health Cons") models fit equally well, with Cons subscales correlating highly. For Temptations, a previously published three-factor (Negative Affect, Social, Weight Control) hierarchical model fit well in nonsmokers. In smokers, previously published subscales were reliably measured, but their structural relationship remained unclear. Stage difference tests showed medium to large effect sizes of DB and Temptation subscales in smokers and nonsmokers. CONCLUSIONS: The use of DB was validated for both smokers and nonsmokers in this sample of primarily African-American adolescent females, where Cons can be combined or separated into "Aesthetic Cons" and "Health Cons" based on practical utility and preference. For Temptations, more research is needed but large stage differences in Temptations subscales underscore the importance of this concept in smoking acquisition and cessation.

Cluster subtypes within the precontemplation stage of change for sun protection behavior.

The aim of this study is to identify replicable cluster subtypes within the precontemplation stage of change for sun protection. Secondary data analysis of baseline data from a sample of participants in a home-based expert system intervention was performed. Three random samples were selected from participants in the precontemplation stage (N = 570). Cluster analyses were performed using the scales of pros, cons, and self-efficacy. Interpretability of pattern, pseudo F-test, and dendograms were used to determine the number of clusters. A four-cluster solution replicated across subsamples. Significant differences between clusters on the nine processes of change and on behavioral measures were found. Cluster solutions were robust, interpretable and with good initial external validity. They replicated patterns found for other behaviors, demonstrating long-term predictability and providing basis for tailored interventions.

The benefits and challenges of multiple health behavior change in research and in practice.

OBJECTIVE: The major chronic diseases are caused by multiple risks, yet the science of multiple health behavior change (MHBC) is at an early stage, and factors that facilitate or impede scientists' involvement in MHBC research are unknown. Benefits and challenges of MHBC interventions were investigated to strengthen researchers' commitment and prepare them for challenges. METHOD: An online anonymous survey was e-mailed to listservs of the Society of Behavioral Medicine between May 2006 and 2007. Respondents (N=69) were 83% female; 94% held a doctoral degree; 64% were psychologists, 24% were in public health; and 83% targeted MHBC in their work. RESULTS: A sample majority rated 23 of the 24 benefits, but only 1 of 31 challenge items, as very to extremely important. Those engaged in MHBC rated the total benefits significantly higher than respondents focused on single behaviors, F(1,69)=4.21, p<.05, and rated the benefits significantly higher than the challenges: paired t(57)=7.50, p<.001. The two groups did not differ in ratings of challenges. CONCLUSION: It appears that individuals focused solely on single behaviors do not fully appreciate the benefits that impress MHBC researchers; it is not that substantial barriers are holding them back. Benefits of MHBC interventions need emphasizing more broadly to advance this research area.

Validity of stage assessment in the adoption and maintenance of physical activity and fruit and vegetable consumption.

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% to 80%) and specificity (80% to 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.

Motivation for blood donation among African Americans: developing measures for stage of change, decisional balance, and self-efficacy constructs.

Despite a specific need for transfused blood among African Americans due to higher rates of sickle cell disease, African Americans donate blood significantly less frequently than their White counterparts. This study describes the development and validation of culturally adapted measures of the transtheoretical model (TTM) constructs of Stage of Change, Decisional Balance, and Self-efficacy applied to blood donation in an African American sample. Exploratory and confirmatory analyses produced one pros and two cons scales for the Decisional Balance Inventory, and one scale for the Situational Self-efficacy Measure. Expected patterns for the Decisional Balance and Self-efficacy Scales by Stage of Change were found, but only the pros and one cons scale varied significantly. Results provide support for use of the TTM applied to blood donation and have important implications for development of effective assessment and intervention tools to increase blood donation among the African American population.

Time series analysis of treatment adherence patterns in individuals with obstructive sleep apnea.

BACKGROUND: Adherence to medical recommendations is often suboptimal, making examination of adherence data an important scientific concern. Studies that attempt to predict or modify adherence often face the problem that adherence as a dependent variable is complex and non-normally distributed. Traditional statistical approaches to adherence data may mask individual variability that may guide clinician and researcher's development of adherence interventions. In this study, we employ time series analysis to examine adherence patterns objectively in patients with obstructive sleep apnea (OSA). Although treatment adherence is poor in OSA, state-of-the-art adherence monitoring allows a comprehensive examination of objective data. PURPOSE: The purpose of the study is to determine the number and types of adherence patterns seen in a sample of patients with OSA receiving positive airway pressure (PAP). METHODS: Seventy-one moderate to severe OSA participants with 365 days of treatment data were studied. RESULTS: Adherence patterns could be classified into seven categories: (1) Good Users (24%), (2) Slow Improvers (13%), (3) Slow Decliners (14%), (4) Variable Users (17%), (5) Occasional Attempters (8%), (6) Early Drop-outs (13%), and (7) Non-Users (11%). CONCLUSIONS: Time series analysis provides a useful method for examining adherence while maintaining a focus on individual differences. Implications for future research are discussed.