Aging and the social cognitive determinants of physical activity behavior and behavior change: evidence from the guide to health trial.

Part one of this study investigated the effect of aging on social-cognitive characteristics related to physical activity (PA) among adults in the baseline phase of a health promotion intervention. Participants' questionnaire responses and activity logs indicated PA levels and self-efficacy declined with age, while social support and the use of self-regulatory behaviors (e.g., goal setting, planning, and keeping track) increased. With age participants were also less likely to expect PA to interfere with their daily routines and social obligations. Part two of the study was among overweight/obese, inactive participants completing the intervention; it examined whether improvements in psychosocial variables might counteract declining PA associated with age. After treatment, participants were more active and decreased body weight regardless of age, and improved self-efficacy, outcome expectations, and self-regulatory behaviors. In a causal model, increases in self-efficacy at 7-months lead to increased PA levels and, albeit marginally, weight loss at 16 months; increased PA was associated with greater weight loss. Aging adults who were more confident exercised more and as a result lost more weight. This longitudinal study suggests interventions that offset the effect of aging on self-efficacy may be more successful in helping older participants become more active and avoid weight gain.

Web-based guide to health: relationship of theoretical variables to change in physical activity, nutrition and weight at 16-months.

BACKGROUND: Evaluation of online health interventions should investigate the function of theoretical mechanisms of behavior change in this new milieu. OBJECTIVES: To expand our understanding of how Web-based interventions influence behavior, we examined how changes at 6 months in participants' psychosocial characteristics contributed to improvements at 16 months in nutrition, physical activity (PA), and weight management as a result of the online, social cognitive theory (SCT)-based Guide to Health intervention (WB-GTH). METHODS: We conducted recruitment, enrollment, and assessments online with 272 of 655 (41.5%) participants enrolling in WB-GTH who also completed 6- and 16-month follow-up assessments. Participants' mean age was 43.68 years, 86% were female, 92% were white, mean education was 17.45 years, median income was US $85,000, 84% were overweight or obese, and 73% were inactive. Participants received one of two equally effective versions of WB-GTH. Structural equation analysis of theoretical models evaluated whether psychosocial constructs targeted by WB-GTH contributed to observed health behavior changes. RESULTS: The longitudinal model provided good fit to the data (root mean square error of approximation <.05). Participants' weight loss at 16 months was predicted by improvements in their PA (beta(total) = -.34, P = .01), consumption of fruits and vegetables (F&V) (beta(total) = -.20, P = .03) and calorie intake (beta(total) = .15, P = .04). Improvements at 6 months in PA self-efficacy (beta(total) = -.10, P = .03), PA self-regulation (beta(total) = -.15, P = .01), nutrition social support (beta(total) = -.08, P = .03), and nutrition outcome expectations (beta(total) = .08, P = .03) also contributed to weight loss. WB-GTH users with increased social support (beta(total) = .26, P = .04), self-efficacy (beta(total) = .30, P = .01), and self-regulation (beta(total) = .45, P = .004) also exhibited improved PA levels. Decreased fat and sugar consumption followed improved social support (beta(total) = -.10, P = .02), outcome expectations (beta(total) = .15, P = .007), and self-regulation (beta(total) = -.14, P = .008). Decreased calorie intake followed increased social support (beta(total) = -.30, P < .001). Increased F&V intake followed improved self-efficacy (beta(total) = .20, P = .01), outcome expectations (beta(total) = -.29, P = .002), and self-regulation (beta(total) = .27, P = .009). Theorized indirect effects within SCT variables were also supported. CONCLUSIONS: The WB-GTH influenced behavior and weight loss in a manner largely consistent with SCT. Improving social support, self-efficacy, outcome expectations, and self-regulation, in varying combinations, led to healthier diet and exercise habits and concomitant weight loss. High initial levels of self-efficacy may be characteristic of Web-health users interested in online interventions and may alter the function of SCT in these programs. Researchers may find that, although increased self-efficacy enhances program outcomes, participants whose self-efficacy is tempered by online interventions may still benefit. TRIAL REGISTRATION: Clinicaltrials.gov NCT00128570; http://clinicaltrials.gov/ct2/show/NCT00128570 (Archived by WebCite at http://www.webcitation.org/5vgcygBII).

Social cognitive determinants of nutrition and physical activity among web-health users enrolling in an online intervention: the influence of social support, self-efficacy, outcome expectations, and self-regulation.

BACKGROUND: The Internet is a trusted source of health information for growing majorities of Web users. The promise of online health interventions will be realized with the development of purely online theory-based programs for Web users that are evaluated for program effectiveness and the application of behavior change theory within the online environment. Little is known, however, about the demographic, behavioral, or psychosocial characteristics of Web-health users who represent potential participants in online health promotion research. Nor do we understand how Web users' psychosocial characteristics relate to their health behavior-information essential to the development of effective, theory-based online behavior change interventions. OBJECTIVE: This study examines the demographic, behavioral, and psychosocial characteristics of Web-health users recruited for an online social cognitive theory (SCT)-based nutrition, physical activity, and weight gain prevention intervention, the Web-based Guide to Health (WB-GTH). METHODS: Directed to the WB-GTH site by advertisements through online social and professional networks and through print and online media, participants were screened, consented, and assessed with demographic, physical activity, psychosocial, and food frequency questionnaires online (taking a total of about 1.25 hours); they also kept a 7-day log of daily steps and minutes walked. RESULTS: From 4700 visits to the site, 963 Web users consented to enroll in the study: 83% (803) were female, participants' mean age was 44.4 years (SD 11.03 years), 91% (873) were white, and 61% (589) were college graduates; participants' median annual household income was approximately US $85,000. Participants' daily step counts were in the low-active range (mean 6485.78, SD 2352.54) and overall dietary levels were poor (total fat g/day, mean 77.79, SD 41.96; percent kcal from fat, mean 36.51, SD 5.92; fiber g/day, mean 17.74, SD 7.35; and fruit and vegetable servings/day, mean 4.03, SD 2.33). The Web-health users had good self-efficacy and outcome expectations for health behavior change; however, they perceived little social support for making these changes and engaged in few self-regulatory behaviors. Consistent with SCT, theoretical models provided good fit to Web-users' data (root mean square error of the approximation [RMSEA] < .05). Perceived social support and use of self-regulatory behaviors were strong predictors of physical activity and nutrition behavior. Web users' self-efficacy was also a good predictor of healthier levels of physical activity and dietary fat but not of fiber, fruits, and vegetables. Social support and self-efficacy indirectly predicted behavior through self-regulation, and social support had indirect effects through self-efficacy. CONCLUSIONS: Results suggest Web-health users visiting and ultimately participating in online health interventions may likely be middle-aged, well-educated, upper middle class women whose detrimental health behaviors put them at risk of obesity, heart disease, some cancers, and diabetes. The success of Internet physical activity and nutrition interventions may depend on the extent to which they lead users to develop self-efficacy for behavior change, but perhaps as important, the extent to which these interventions help them garner social-support for making changes. Success of these interventions may also depend on the extent to which they provide a platform for setting goals, planning, tracking, and providing feedback on targeted behaviors.