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
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
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DOI：
10.2196/jmir.1551
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发表时间：
2011-01-01
影响因子：
7.4
通讯作者：
Wojcik, Janet R.
中科院分区：
文献类型：
--
作者：
Anderson-Bill, Eileen Smith;Winett, Richard A.;Wojcik, Janet R.
背景：对于越来越多的Web用户来说，Internet是一个值得信赖的健康信息来源。在线健康干预的承诺将实现与纯粹的在线理论为基础的程序，为网络用户进行评估的程序的有效性和在线环境中的行为改变理论的应用程序的发展。然而，鲜为人知的是，人口统计学，行为，或心理特征的网络健康用户代表潜在的参与者在网上健康促进研究。我们也不了解网络用户的心理社会特征如何与他们的健康行为相关-这些信息对于发展有效的、基于理论的在线行为改变干预至关重要。目的：这项研究考察了网络健康用户的人口统计学，行为和心理社会特征，这些用户被招募进行基于在线社会认知理论（SCT）的营养，体育活动和体重增加预防干预，方法：通过在线社交和专业网络以及印刷和在线媒体的广告，将参与者定向到WB-GTH网站，对参与者进行筛选，同意，并使用人口统计学，身体活动，心理社会和食物频率在线问卷进行评估结果：从4700次访问该网站，963名网络用户同意参加这项研究：83%（803人）为女性，参与者的平均年龄为44.4岁（SD 11.03岁），91%（873人）为白色，61%（589人）为大学毕业生;参与者的家庭年收入中位数约为85，000美元。参与者的每日步数在低活动范围内（平均值6485.78，SD 2352.54）和总体膳食水平较差（总脂肪g/天，平均值77.79，SD 41.96;来自脂肪的千卡百分比，平均值36.51，SD 5.92;纤维g/天，平均值17.74，SD 7.35;水果和蔬菜的摄入量/天，平均值为4.03，SD为2.33）。网络健康用户有良好的自我效能和健康行为改变的结果期望，但是，他们认为很少的社会支持，使这些变化和从事一些自我调节行为。与SCT一致，理论模型提供了良好的拟合网络用户的数据（近似均方根误差[RMSEA] < .05）。知觉的社会支持和自我调节行为的使用是身体活动和营养行为的强预测因子。网络用户的自我效能也是身体活动和膳食脂肪健康水平的良好预测因素，但不是纤维，水果和蔬菜。社会支持和自我效能间接预测行为，通过自我调节，社会支持有间接的影响，通过自我efficiency.Conclusions：结果表明，网络健康用户访问，并最终参与在线健康干预可能是中年，受过良好教育，中上阶层妇女的有害健康行为，使他们处于肥胖，心脏病，某些癌症和糖尿病的风险。互联网体育活动和营养干预的成功可能取决于他们引导用户发展自我效能以改变行为的程度，但同样重要的是，这些干预措施在多大程度上帮助他们获得社会支持以做出改变。这些干预措施的成功还可能取决于它们在多大程度上为设定目标、规划、跟踪和提供针对性行为的反馈提供了一个平台。
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.