Motivational Readiness to Change Exercise Behaviors: An Analysis of the Differences in Exercise, Wearable Exercise Tracking Technology, and Exercise Frequency, Intensity, and Time (FIT) Values and BMI Scores in University Students

References

• Centers for Disease Control and Prevention. Heart Disease. https://www.cdc.gov/heartdisease/conditions.htm. Published October 30, 2017. Accessed June 15, 2017.
   Google Scholar
• National College Health Assessment. http://www.acha-ncha.org/overview.html. Published Fall, 2017. Accessed June 15, 2018.
   Google Scholar
• National Report on College Students. Pearson student mobile device survey. http://www.pearsoned.com/wp-content/uploads/Pearson-Student-Mobile-Device-Survey-2015-National-Report-on-College-Students-public-release.pdf. Published June, 2015. Accessed June 15, 2018.
   Google Scholar
• Bort-Roig J, Gilson ND, Puig-Ribera A, Contreras RS, Trost SG. Measuring and influencing physical activity with smartphone technology: a systematic review. Am J Sports Med. 2014;44:671–686. doi:10.1007/s40279-014-0142-5.
   Google Scholar
• Gropper SS, Simmons KP, Connell LJ, Ulrich PA. Changes in body weight, composition, and shape: a four-year study of college students. J Appl Physiol Nutr Metab. 2012;37:1118–1123. doi:10.1139/h2012-139.
   PubMed Web of Science ®Google Scholar
• United States Department of Health and Human Services. The surgeon general’s call to action to prevent and decrease overweight and obesity. https://www.surgeongeneral.gov/priorities/prevention/about/healthy-aging-in-action-final.pdf. Published November, 2016. Accessed June 15, 2018.
   Google Scholar
• American College of Sports Medicine. Annual survey: 2017 fitness trends. https://www.acsm.org/about-acsm/media-room/news-releases/2015/10/26/annual-survey-reveals-new-1-fitness-trend-in-2016-2017. Published November 2016. Accessed October 2017.
   Google Scholar
• American Heart Association. Healthy living. https://www.heart.org. Published February 2, 2014. Accessed June 15, 2018.
   Google Scholar
• Bower M, Sturman D. What are the educational affordances of wearable technologies? Comput Educ. 2015;88:343–353. doi:10.1016/j.compedu.2015.07.013.
   Web of Science ®Google Scholar
• Cadmus-Bertram L, Marcus BH, Patterson RE, Parker BA, Morey BL. Randomized trial of a fitbit-based physical activity intervention for women. Am J Prev Med. 2015;49(3):414–418. doi:10.1016/j.amepre.2015.01.020.
   PubMed Web of Science ®Google Scholar
• Middelweerd A, van der Laan D, van Stralen M, et al. What features do Dutch university students prefer in a smartphone application for promotion of physical activity? A qualitative approach. Int J Behav Nutr Phys Act. 2015;12(31):1–11. doi:10.1186/s12966-015-0189-1.
   PubMedGoogle Scholar
• Stvilia B, Choi W. Mobile wellness application-seeking behavior by college students: an exploratory study. Lib Inf Sci Res. 2015;37:201–208. doi:10.1016/j.lisr.2015.04.007.
   Web of Science ®Google Scholar
• Gowin M, Cheney M, Gwin S, Wann TF. Health and fitness app use in college students: a qualitative study. Am J Health Educ. 2015;46(4):223–234. doi:10.1080/19325037.2015.1044140.
   Web of Science ®Google Scholar
• Papalia Z, Wilson O, Bopp M, Duffey M. Technology-based physical activity self-monitoring among college students. Int J Exer Sci. 2018;11:1096–1104.
   Google Scholar
• Dunn EE, Robertson-Wilson J. Behavior change techniques and physical activity using the fitbit flex. Int J Exer Sci. 2018;11:561–574.
   Google Scholar
• Fritz T, Huang EM, Murphy GC, Zimmermann T. Persuasive technology in the real world: a study of long-term use of activity sensing devices for fitness. Paper presented at: CHI ‘14 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems; April 26, 2014; Toronto, Ontario, Canada.
   Google Scholar
• Ferguson T, Rowlands AV, Olds T, Maher C. The validity of consumer-level activity monitors in health adults worn in free-living conditions: a cross-sectional study. Int J Behav Nutr Phys Act. 2015;12(42):1–9. doi:10.1186/s12966-015-0201-9.
   PubMed Web of Science ®Google Scholar
• Patel MS, Asch DA, Volpp KG. Wearable devices as facilitators, not drivers, of health behavior change. J Am Med Assoc. 2015;39(13):459–460. doi:10.1001/jama.2014.14781.
   Google Scholar
• Keeley K, Potteiger K, Brown CD. Athletic training education: there’s an app for that. Athl Train Educ J. 2015;10(2):190–199. doi:10.4085/1002190.
   Google Scholar
• Nahm E. Mobile technologies for health education: what do we need to consider? Online J Nurs Inform. 2015;17:18–20.
   Google Scholar
• Barnett BE, Merriman WJ. Knowledge of physical fitness in prospective physical education teachers. Phys Educ. 1994;5:74–78.
   Google Scholar
• Bulger SM, Mohr DJ, Carson LM, Robert DL, Wiegand RL. Preparing prospective physical educators in exercise physiology. Quest. 2000;52:166–185. doi:10.1080/00336297.2000.10491708.
   Web of Science ®Google Scholar
• Van Donselaar L, Leslie DK. Current and recommended preparation of physical education teachers in exercise physiology. Phys Educ. 1990;47:209–217.
   Google Scholar
• Prochaska JO, DiClemente CC. Stages and processes of self-change of smoking: toward an integrative model of change. J Clin Psychol. 1983;51:390–395.
   Web of Science ®Google Scholar
• Cancer Prevention Research Center. Exercise: Stages of change—continuous measure. http://www.uri.edu/research/cprc/Measures/Exercise. Published 2007. Accessed October, 2017.
   Google Scholar
• Samuelson M. Changing unhealthy lifestyle: who’s ready…who’s not: an argument in support of the stages of change component of the transtheoretical model. Am J Health Promot. 1990;12(1):13–14. doi:10.4278/0890-1171-12.1.13.
   Google Scholar
• Carney MM, Kivlahan DR. Motivational subtypes among veterans seeking substance abuse treatment: profiles based on stages of change. Psychol Addict Behav. 1995;9:1135–1142. doi:10.1037/0893-164X.9.2.135.
   Web of Science ®Google Scholar
• DiClemente CC, Hughes SO. Stages of change: profiles in alcoholism treatment. J Subst Abus Alcohol. 1990;2:217–235. doi:10.1016/S0899-3289(05)80057-4.
   Google Scholar
• Baumgartner A, Hensley LD. Conducting and Reading Research in Health and Human Performance. 4th. New York, NY: McGraw-Hill; 2007.
   Google Scholar
• Ceccarini M, Borrello M, Manzoni GM, Castelnuovo G. Assessing motivation and readiness to change for weight management and control: an in-depth evaluation of three sets of instruments. Front Psychol. 2015;6(51):511–521. doi:10.3389/fpsyg.2015.00511.
   PubMedGoogle Scholar
• McConnaughy EA, Prochaska JO, Velicer WF. Stages of change in psychotherapy: measurement and sample profiles. Psychother. 1983;20(8):368–375. doi:10.1037/h0090198.
   Google Scholar
• University of Maryland Baltimore County. The habits lab at UMBC. Published 2016. http://habitslab.umbc.edu/. Accessed September 5, 2018.
   Google Scholar
• Bond B, Hind S, Williams C, Barker A. The acute effect of exercise intensity on vascular function in adolescents. Med Sci Sports Exer. 2015;47(12):2628–2635. doi:10.1249/MSS.0000000000000715.
   PubMed Web of Science ®Google Scholar
• Gorber SC, Tremblay M, Moher D, Gorber B. A comparison of direct vs. self‐report measures for assessing height, weight and body mass index: a systematic review. Obes Rev. 2007;8(4):307–326. doi:10.1111/j.1467-789X.2007.00347.x.
   PubMed Web of Science ®Google Scholar
• Ross R, Janiszewski PM. Is weight loss the optimal target for obesity-related cardiovascular disease risk reduction? Can J Cardiol. 2008;24(Suppl D). doi:10.1016/S0828-282X(08)71046-8. PMID:18787733.
   Google Scholar
• Wortly D, An JY, Nigg CR. Wearable technologies, health and well-being: a case review. Digit Med. 2017;3:11–17. doi:10.4103/digm.digm_13_17.
   Google Scholar
• Butler SM, Black DR, Blue CL, Gretebeck RJ. Change in diet, physical activity and body weight in female college freshman. Am J Health Behav. 2004;28:24–32.
   PubMed Web of Science ®Google Scholar
• Delinsky SS, Wilson GT. Weight gain, dietary restraint and disordered eating in the freshman year of college. Eat Behav. 2008;9(1):82–90. doi:10.1016/j.eatbeh.2007.06.001.
   PubMedGoogle Scholar
• Nelson MC, Kocos R, Lytle LA, Perry CL. Understanding the perceived determinants of weight-related behaviors in late adolescence: a qualitative analysis among college youth. J Nutr Educ Behav. 2006;41(4):287–292. doi:10.1016/j.jneb.2008.05.005.
   Google Scholar
• Cowan LT, Van Wagenen SA, Brown BA, et al. Apps of steel: are exercise apps providing consumers with realistic expectations? A content analysis of exercise apps for presence of behavior change theory. Health Educ. 2012;40(2):133–139.
   Web of Science ®Google Scholar
• Azar K, Lesser LI, Laing BY, et al. Mobile applications for weight management: theory-based content analysis. Am J Prev Med. 2013;45(5):583–589. doi:10.1016/j.amepre.2013.07.005.
   PubMed Web of Science ®Google Scholar
• Mercer K, Li M, Giangregoria L, Burns C, Grindrod K. Behavior change techniques present in wearable activity trackers: a critical analysis. JMIR Mhealth Uhealth. 2016;4(2):40. doi:10.2196/mhealth.4461.
   PubMed Web of Science ®Google Scholar
• Dhawan E Gen-Y workforce and workplace are out of sync. Forbeswoman. www.forbes.com. Published September 8, 2014. Accessed August, 2015.
   Google Scholar
• National Center for Academic Transformation. http://www.thencat.org. Published 2014. Accessed August, 2015.
   Google Scholar
• Merriam SB, Caffarella RS, Baumgartner LM. Learning in Adulthood: A Comprehensive Guide. San Francisco, CA: John Wiley & Sons, Inc; 2007.
   Google Scholar