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临床试验/NCT03253406
NCT03253406已完成不适用

Use of Health Wearables to Improve Physical Activity and Eating Behaviors Among College Students: A 12-week Randomized Pilot Study

University of Minnesota2 个研究点 分布在 1 个国家目标入组 38 人开始时间: 2017年9月6日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
入组人数
38
试验地点
2
主要终点
Physical Activity

研究概览

简要总结

The purpose of this pilot randomized trial is to determine (1) the effectiveness of the Polar M400, used in combination with a twice-weekly Facebook-delivered Social Cognitive Theory-based health intervention, in the promotion of more healthful physical activity and nutritious eating behaviors over 12 weeks in college students versus a comparison group; and (2) the validity and reliability of the Polar M400 in the assessment of free-living (i.e., non-laboratory based) physical activity (in this case, steps per day and daily durations of moderate and vigorous physical activity) and energy expenditure.

详细描述

The prevalence of overweight and obesity among individuals 20-39 years of age is 60.9%. Unfortunately, physical inactivity and poor dietary practices among this age cohort appear to be two major contributory factors for the preceding statistic. Among the youngest individuals within this age cohort are college students. Research suggests college students possess risk factors for overweight and obesity as many of these individuals are now independent and, for some, making physical activity- and nutrition-related decisions autonomously for the first time. Studies on obesity- and weight-related behaviors in this population suggest approximately 25% to 30% of college students are overweight or obese. Desai et al. also suggested rates of complete physical inactivity among college students is between 37% and 46%. Unfortunately, dietary practices among college students are not ideal either.

Poor nutritional behaviors also contribute to risk factors among this population. In a study among college freshman and sophomores, Racette, Deusinger, Strube, Highstein, and Deusinger found that 70% of the 764 college students assessed consumed less than the U.S. Department of Agriculture (USDA) recommendations of two servings of fruit and three servings of vegetables daily. Strikingly, approximately half of the students surveyed also reported high-fat fast or fried food consumption ≥ 3 times in the past week. Notably, a subsample of these students was assessed again a year later with 70% of these students gaining, on average, four kilograms. Indeed, other studies have demonstrated the impact poor dietary practices (e.g., consumption of "junk foods", sugar-sweetened beverages, or fast foods high in fat and low in nutrient density) and obesogenic environments (e.g., continuously eating at buffet-style student dining halls) can have on weight gain from freshman year of college onward. As such, not only is it clear that theoretically-backed physical activity interventions are needed among college students, there is also a distinct need to include a dietary component within these interventions. Technology integration within these physical activity and nutritional interventions among college students might present a viable approach.

While few empirical data is available regarding health wearable use among young adults, it is likely that this technology-savvy age cohort represents a large proportion of the one in six consumers currently owning a health wearable. Further, with the number of health wearables sold in 2018 projected to be 110 million, it is likely that this age cohort will contribute substantially to this figure. Moreover, research indicates the popularity of social media among young adults. Indeed, among individuals 18-29 years of age, approximately 90% use at least one social media site. Currently, Facebook represents the most widely used social media site with 1.71 billion active users and individuals 18 to 34 years of age representing the majority of Facebook users.

Therefore, the combined use of health wearable technology, these devices' associated smartphone applications, and a theoretically-driven health intervention delivered via social media, may prove appealing and effective as a health promotion strategy among college students. Specifically, use of the Polar M400 may increase college students' ability to self-regulate physical activity behaviors as self-regulation is posited as an important factor in promoting behavior change. Further, the Polar M400's associated smartphone application-based and Internet-based portal allows individuals to not only track physical activity-related metrics, but view predicted energy expenditure as well, which may allow individuals to self-regulate food intake in relation to daily energy expenditure. In combination with the Polar M400's capabilities, a twice-weekly Facebook-delivered Social Cognitive Theory-based health intervention may be able to increase college students' self-efficacy, outcome expectancy, enjoyment, and social support while decreasing barriers for participation in greater physical activity and nutritious eating behaviors. Relatedly, it is vital to also examine the preceding intervention's ability to promote changes in college students' intrinsic motivation for these health behaviors-an investigation which can be completed via application of the Self-Determination Theory.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Prevention
盲法
Single (Participant)

盲法说明

Every attempt will be made to ensure participants do not know the group with which they have been randomized, accomplished by advertising to potential college student participants that two novel, technology-based interventions will be employed in the study, with no more detail provided. After screening and randomization, participants will be informed of study intervention procedures in an identical manner regardless of group allocation via the use of a study script repeated to each participant by the study's primary investigator. The only difference between the scripts will be a discussion with experimental group participants regarding how to use the Polar M400 smartwatch during the study intervention period. Importantly, college students will be brought into the Lab for screening and baseline testing on an individual basis ensuring the individuals from different groups have no idea of the differing intervention procedures utilized between the experimental and comparison groups.

入排标准

年龄范围
18 Years 至 29 Years(Adult)
性别
All
接受健康志愿者

入选标准

  • 未提供

排除标准

  • 未提供

结局指标

主要结局

Physical Activity

时间窗: "Change in Physical Activity from Baseline to 6 Weeks" and "Change in Physical Activity from Baseline to 12 Weeks"

Will be assessed via Actigraph Link accelerometers with daily moderate-to-vigorous physical activity, light physical activity, sedentary behavior, steps per day, and energy expenditure the outcomes of interest. The Actigraph accelerometer has been validated among adults (Kaminsky \& Ozemek, 2012). Participants will wear the accelerometer for seven days (ensuring the collection of physical activity data on at least two weekdays and one weekend day) as suggested for field-based accelerometer research (Trost, McIver, \& Pate, 2005), with the accelerometer appended to the same wrist as the Polar M400. Accelerometry measurements will take place at baseline, six weeks, and 12 weeks to examine changes over time in the aforementioned outcomes.

次要结局

  • Cardiovascular Fitness("Change in Cardiovascular Fitness from Baseline to 12 Weeks")
  • Barriers("Change in Barriers from Baseline to 12 Weeks")
  • Body Composition("Change in Body Composition from Baseline to 12 Weeks")
  • Social Support("Change in Social Support from Baseline to 12 Weeks")
  • Body Weight("Change in Weight from Baseline to 12 Weeks")
  • Enjoyment("Change in Enjoyment from Baseline to 12 Weeks")
  • Intrinsic Motivation("Change in Intrinsic Motivation from Baseline to 12 Weeks")
  • Nutritious Eating Behaviors("Change in Nutritious Eating Behaviors from Baseline to 12 Weeks")
  • Facebook-Delivered Health Intervention Adherence("Assessed Weekly throughout 12-Week Intervention Period")
  • Self-Efficacy("Change in Self-Efficacy from Baseline to 12 Weeks")
  • Outcome Expectancy("Change in Outcome Expectancy from Baseline to 12 Weeks")

研究者

申办方类型
Other
责任方
Sponsor

研究点 (2)

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