Study Results
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Basic Information
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COMPLETED
NA
38 participants
INTERVENTIONAL
2017-09-06
2018-05-07
Brief Summary
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Detailed Description
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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.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
PREVENTION
SINGLE
Study Groups
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Polar M400 + Facebook Group (PM400+FG)
Will be provided a Polar M400 to track physical activity and energy expenditure while also being included in a Facebook group wherein Social Cognitive Theory-based physical activity and nutritious eating tips will be provided twice weekly for 12 weeks.
Polar M400 + Facebook Group (PM400+FG)
Throughout the intervention period experimental group participants will be asked to read and try to implement the twice-weekly physical activity- and nutrition-related health tips posted to the group's Facebook page. Additionally, experimental group participants will be asked to track all physical activity with the Polar M400 smartwatch and use this information to set physical activity-related goals conducive to improved health.
Facebook Only Group (FG)
Included exclusively in a separate, but content-identical, Facebook group for 12 weeks.
Facebook Only Group (FG)
Throughout the intervention period comparison group participants will be asked to read and try to implement the twice-weekly physical activity- and nutrition-related health tips posted to the group's Facebook page.
Interventions
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Polar M400 + Facebook Group (PM400+FG)
Throughout the intervention period experimental group participants will be asked to read and try to implement the twice-weekly physical activity- and nutrition-related health tips posted to the group's Facebook page. Additionally, experimental group participants will be asked to track all physical activity with the Polar M400 smartwatch and use this information to set physical activity-related goals conducive to improved health.
Facebook Only Group (FG)
Throughout the intervention period comparison group participants will be asked to read and try to implement the twice-weekly physical activity- and nutrition-related health tips posted to the group's Facebook page.
Eligibility Criteria
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Inclusion Criteria
* Body mass index ≥ 18.5
* Is currently not engaging in physical activity levels above the Physical Activity Guidelines for Americans (PAGA; U.S. Department of Health and Human Services, 2008)-verified through a structured screening interview prior to participant recruitment and randomization
* Eats less than the recommended two serving of fruits and three serving of vegetables per day (USDA, 2015)-verified through screening using a 10-item fruit and vegetable food frequency questionnaire (F. Thompson et al., 2002)
* No self-reported diagnosed physical/mental disability
* Provides informed consent and completes the Physical Activity Readiness Questionnaire (PAR-Q)
* Willing to be randomized into an intervention or comparison group
Exclusion Criteria
* Contraindication to physical activity participation as determined by PAR-Q results
18 Years
29 Years
ALL
Yes
Sponsors
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University of Minnesota
OTHER
Responsible Party
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Principal Investigators
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Zan Gao, PhD
Role: PRINCIPAL_INVESTIGATOR
University of Minnesota
Locations
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Physical Activity Epidemiology Laboratory
Minneapolis, Minnesota, United States
Countries
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References
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Nelson TF, Gortmaker SL, Subramanian SV, Cheung L, Wechsler H. Disparities in overweight and obesity among US college students. Am J Health Behav. 2007 Jul-Aug;31(4):363-73. doi: 10.5555/ajhb.2007.31.4.363.
Silva MN, Vieira PN, Coutinho SR, Minderico CS, Matos MG, Sardinha LB, Teixeira PJ. Using self-determination theory to promote physical activity and weight control: a randomized controlled trial in women. J Behav Med. 2010 Apr;33(2):110-22. doi: 10.1007/s10865-009-9239-y. Epub 2009 Dec 11.
Racette SB, Deusinger SS, Strube MJ, Highstein GR, Deusinger RH. Weight changes, exercise, and dietary patterns during freshman and sophomore years of college. J Am Coll Health. 2005 May-Jun;53(6):245-51. doi: 10.3200/JACH.53.6.245-251.
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Kaminsky LA, Ozemek C. A comparison of the Actigraph GT1M and GT3X accelerometers under standardized and free-living conditions. Physiol Meas. 2012 Nov;33(11):1869-76. doi: 10.1088/0967-3334/33/11/1869. Epub 2012 Oct 31.
Trost SG, McIver KL, Pate RR. Conducting accelerometer-based activity assessments in field-based research. Med Sci Sports Exerc. 2005 Nov;37(11 Suppl):S531-43. doi: 10.1249/01.mss.0000185657.86065.98.
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Aandstad A, Holtberget K, Hageberg R, Holme I, Anderssen SA. Validity and reliability of bioelectrical impedance analysis and skinfold thickness in predicting body fat in military personnel. Mil Med. 2014 Feb;179(2):208-17. doi: 10.7205/MILMED-D-12-00545.
Rodgers WM, Wilson PM, Hall CR, Fraser SN, Murray TC. Evidence for a multidimensional self-efficacy for exercise scale. Res Q Exerc Sport. 2008 Jun;79(2):222-34. doi: 10.1080/02701367.2008.10599485.
Carlson JA, Sallis JF, Wagner N, Calfas KJ, Patrick K, Groesz LM, Norman GJ. Brief physical activity-related psychosocial measures: reliability and construct validity. J Phys Act Health. 2012 Nov;9(8):1178-86. doi: 10.1123/jpah.9.8.1178. Epub 2011 Dec 27.
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Trost SG, Pate RR, Saunders R, Ward DS, Dowda M, Felton G. A prospective study of the determinants of physical activity in rural fifth-grade children. Prev Med. 1997 Mar-Apr;26(2):257-63. doi: 10.1006/pmed.1996.0137.
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U.S. Department of Health and Human Services. 2008 physical activity guidelines for Americans. Available from https://health.gov/paguidelines/pdf/paguide.pdf. 2008.
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Other Identifiers
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STUDY00000386
Identifier Type: -
Identifier Source: org_study_id
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