Perceptions of Health Behaviors and Mobile Health Applications in an Academically Elite College Population to Inform a Targeted Health Promotion Program

  • Jennifer L WarnickEmail author
  • Angela Pfammatter
  • Katrina Champion
  • Tomas Galluzzi
  • Bonnie Spring



College is a critical developmental time when many emerging adults engage in unhealthy behaviors (i.e., lack of exercise, poor diet, smoking) and consequently experience an increased risk for a decline in cardiovascular health. Understanding the beliefs and opinions of the target population is important to develop effective health promotion interventions. The goal of this study was to understand opinions regarding health and health-related mobile technology of college students at an academically elite Midwestern university in order to inform a mobile health promotion intervention following the integrated behavioral model framework.


Eighteen college students between the ages of 18 and 22 participated in one of four focus groups, where they discussed perceptions of health behaviors, technology use, and their college environment. Data were analyzed using inductive thematic analysis as well as consensus and conformity analysis.


Students reported prioritizing academic success over health and believed in a cultural norm within the university that unhealthy behavioral practices lead to increased academic success. Other identified barriers to achieving good health were (a) low self-efficacy for engaging in healthy behaviors when presented with conflicting academic opportunities and (b) low estimation of the importance of engaging in health behaviors. Regarding mobile health applications (apps), students reported preferring apps that were visually attractive, personalized to each user, and that did not involve competing against other users.


These results have implications for the development of mobile health promotion interventions for college students, as they highlight facilitators and barriers to health behavior change in an academically elite student body.


Mobile health Health promotion College Technology Health behavior change 



This work was supported by the American Heart Association Strategically Focused Research Prevention Network (no. 14SFRN20740001); J.R. Albert Foundation, Inc.; and National Institutes of Health’s National Center for Advancing Translational Sciences (UL1TR001422).

Compliance with Ethical Standards

Conflict of Interest

All authors declare that they have no conflict of interests.

Ethical Approval

All procedures performed in this study were in accordance with the ethical standards of the institutional research committee (our institution’s IRB) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in the study.


  1. 1.
    Afshin A, Forouzanfar MH, Reitsma MB, et al. Health effects of overweight and obesity in 195 countries over 25 years. New Engl J med. 2017;377(1):13–27.CrossRefGoogle Scholar
  2. 2.
    Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, et al. Executive summary: heart disease and stroke statistics—2015 update. Circulation. 2015;131(4):434–41.Google Scholar
  3. 3.
    Spring B, Moller A, Colangelo L, et al. Healthy lifestyle change and subclinical atherosclerosis in young adults: coronary artery risk development in young adults (CARDIA) study. Circulation. 2014;130(1):10–7.CrossRefGoogle Scholar
  4. 4.
    Arnett JJ. Emerging adulthood: a theory of development from the late teens through the twenties. Am Psychol. 2000;55(5):469–80.CrossRefGoogle Scholar
  5. 5.
    Vadeboncoeur C, Townsend N, Foster C. A meta-analysis of weight gain in first year university students: is freshman 15 a myth? BMC Obesity. 2015;2(1):22.CrossRefGoogle Scholar
  6. 6.
    Ogden CL, Carroll MD, Fakhouri TH, Hales CM, Fryar CD, Li X, et al. Prevalence of obesity among youths by household income and education level of head of household—United States 2011–2014. Morb Mortal Wkly Rep. 2018;67(6):186–9.Google Scholar
  7. 7.
    Centers for Disease Control, National Center for Health Statistics. Nutrition and weight status. Healthy people 2020 midcourse review (chapter 29). 2016. Accessed 29 Nov 2018.
  8. 8.
    Lloyd-Richardson EE, Bailey S, Fava JL, Wing R. A prospective study of weight gain during the college freshman and sophomore years. Prev Med. 2009;48:256–61.CrossRefGoogle Scholar
  9. 9.
    Nelson MC, Story M, Larson NI, Neumark-Sztainer D, Lytle LA. Emerging adulthood and college-aged youth: an overlooked age for weight-related behavior change. Obesity. 2008;16(10):2205–11.CrossRefGoogle Scholar
  10. 10.
    American College Health Association. American College Health Association-National College Health Assessment II: Reference Group Executive Summary Spring. Hanover, MD: American College Health Association; 2014.Google Scholar
  11. 11.
    Small M, Bailey-Davis L, Morgan N, Maggs J. Changes in eating and physical activity behaviors across seven semesters of college. Health Educ Behav. 2012;40(4):435–41.CrossRefGoogle Scholar
  12. 12.
    Keating XD, Guan J, Piñero JC, Bridges DM. A meta-analysis of college students’ physical activity behaviors. J Am Coll Heal. 2005;54(2):116–26.CrossRefGoogle Scholar
  13. 13.
    Anderson DA, Shapiro JR, Lundgren JD. The freshman year of college as a critical period for weight gain: an initial evaluation. Eat Behav. 2003;4(4):363–7.CrossRefGoogle Scholar
  14. 14.
    Israel TA, King BA, Husten CG, et al. Tobacco product use among adults—United States, 2012–2013. Morb Mortal Wkly Rep. 2004;63(25):542–7.Google Scholar
  15. 15.
    Lenk K, Rode P, Fabian L, Bernat D, Klein E, Forster J. Cigarette use among young adults: comparisons between 2-year college students, 4-year college students, and those not in college. J Am Coll Heal. 2012;60(4):303–8.CrossRefGoogle Scholar
  16. 16.
    Patterson F, Lerman C, Kaufmann VG, Neuner GA, Audrain-McGovern J. Cigarette smoking practices among American college students: review and future directions. J Am Coll Heal. 2004;52(5):203–12.CrossRefGoogle Scholar
  17. 17.
    Spring B, Moller AC, Coons MJ. Multiple health behaviours: overview and implications. J Public Health. 2012;34(Suppl 1):i3–10.CrossRefGoogle Scholar
  18. 18.
    Kang J, Ciecierski CC, Malin EL, Carroll AJ, Gidea M, Craft LL, et al. A latent class analysis of cancer risk behaviors among U.S. college students. Prev Med. 2014;64:121–5.Google Scholar
  19. 19.
    Laska MN, Pasch KE, Lust K, Story M, Ehlinger E. Latent class analysis of lifestyle characteristics and health risk behaviors among college youth. Prev Sci. 2009;10:376–86.CrossRefGoogle Scholar
  20. 20.
    Wells K, Makela C, Kennedy C. Co-occurring health-related behavior pairs in college students: insights for prioritized and targeted interventions. Am J Health Educ. 2014;45:210–8.CrossRefGoogle Scholar
  21. 21.
    Loef M, Walach H. The combined effects of healthy lifestyle behaviors on all cause mortality: a systematic review and meta-analysis. Prev Med. 2012;55:163–70.CrossRefGoogle Scholar
  22. 22.
    Prochaska JJ, Prochaska JO. A review of multiple health behavior change interventions for primary prevention. Am J Lifestyle Med. 2011;5:208–21.CrossRefGoogle Scholar
  23. 23.
    American Heart Association. 2013 Statistical fact sheet: 2020 impact goal. Dallas TX: American Heart Association; 2013. Available from: Accessed 29 Nov 2018.
  24. 24.
    American Heart Association. My Life Check – Life’s Simple 7. Accessed 17 July 2018.
  25. 25.
    Laitinen TT, Pahkala K, Magnussen CG, Viikari JSA, Oikonen M, Taittonen L, et al. Ideal cardiovascular health in childhood and cardiometabolic outcomes in adulthood. Circulation. 2012;125(16):1971–8.Google Scholar
  26. 26.
    Lloyd-Jones DM. The impact of traditional risk factor development on the life course of cardiovascular diseases. Ethn Dis. 2012;22(3 (Suppl 1)):1–30.Google Scholar
  27. 27.
    Brown DM, Bray SR, Beatty KR, Kwan MY. Healthy active living: a residence community–based intervention to increase physical activity and healthy eating during the transition to first-year university. J Am Coll Heal. 2014;62(4):234–42.CrossRefGoogle Scholar
  28. 28.
    Napolitano MA, Hayes S, Bennett GG, Ives AK, Foster GD. Using Facebook and text messaging to deliver a weight loss program to college students. Obesity. 2013;21(1):25–31.CrossRefGoogle Scholar
  29. 29.
    Plotnikoff RC, Costigan SA, Williams RL, Hutchesson MJ, Kennedy SG, Robards SL, et al. Effectiveness of interventions targeting physical activity, nutrition and healthy weight for university and college students: a systematic review and meta-analysis. Int J Behav Nutr Phy. 2015;12(1):45.Google Scholar
  30. 30.
    Simmons VN, Heckman BW, Fink AC, Small BJ, Brandon TH. Efficacy of an experiential, dissonance-based smoking intervention for college students delivered via the internet. J Consult Clin Psychol. 2013;81(5):810–20.CrossRefGoogle Scholar
  31. 31.
    Harrison MA, Bealing CE, Salley JM. 2 TXT or not 2 TXT: college students’ reports of when text messaging is social breach. Soc Sci J. 2015;52(2):188–94.CrossRefGoogle Scholar
  32. 32.
    Harrison MA, Gilmore AL. U txt WHEN? College students’ social contexts of text messaging. Soc Sci J. 2012;49(4):513–8.CrossRefGoogle Scholar
  33. 33.
    Pew Research Center (2018) Mobile fact sheet. Accessed 13 July 2018.
  34. 34.
    Poushter J Smartphone ownership and internet usage continues to climb in emerging economies. Pew Research Center 2016;22:1–44.Google Scholar
  35. 35.
    Brown ON, O’Connor LE, Savaiano D. Mobile MyPlate: a pilot study using text messaging to provide nutrition education and promote better dietary choices in college students. J Am Coll Heal. 2014;62(5):320–7.Google Scholar
  36. 36.
    Patrick K, Marshall SJ, Davila EP, Kolodziejczyk JK, Fowler JH, Calfas KJ, et al. Design and implementation of a randomized controlled social and mobile weight loss trial for young adults (project SMART). Contemp Clin Trials. 2014;37(1):10–8.Google Scholar
  37. 37.
    Riley W, Obermayer J, Jean-Mary J. Internet and mobile phone text messaging intervention for college smokers. J Am Coll Heal. 2008;57(2):245–8.CrossRefGoogle Scholar
  38. 38.
    Fishbein M. The role of theory in HIV prevention. AIDS Care. 2010;12(3):273–8.CrossRefGoogle Scholar
  39. 39.
    Fishbein M, Cappella JN. The role of theory in developing effective health communications. J Commun. 2006;56:S1–S17.CrossRefGoogle Scholar
  40. 40.
    Montaño DE, Kasprzyk D. Theory of reasoned action, theory of planned behavior, and the integrated behavioral model. In: Glanz K, Rimer BK, Viswanath K, editors. Health behavior and health education: theory, research, and practice. San Francisco, CA: John Wiley & Sons; 2008. p. 67–121.Google Scholar
  41. 41.
    Brown B. Adolescents’ relationships with peers. In: Lerner R, Steinberg L, editors. Handbook of adolescent psychology. 2nd ed. New York, NY: Wiley; 2004. p. 363–94.Google Scholar
  42. 42.
    Gardner M, Steinberg L. Peer influence on risk taking, risk preference, and risky decision making in adolescence and adulthood: an experimental study. Dev Psychol. 2005;41:625–35.CrossRefGoogle Scholar
  43. 43.
    LaCaille LJ, Dauner KN, Krambeer RJ, Pedersen J. Psychosocial and environmental determinants of eating behaviors, physical activity, and weight change among college students: a qualitative analysis. J Am Coll Heal. 2011;59(6):531–8.CrossRefGoogle Scholar
  44. 44.
    Klasnja P, Hekler EB, Shiffman S, Boruvka A, Almirall D, Tewari A, et al. Microrandomized trials: an experimental design for developing just-in-time adaptive interventions. Health Psychol. 2015;34(S):1220–8.Google Scholar
  45. 45.
    Patton MQ. Qualitative research and evaluation methods. New York, New Delhi, London: Thousand Oaks Sage Publications; 2002.Google Scholar
  46. 46.
    Ulin PR, Robinson ET, Tolley EE. Qual Meth Pub Health. San Francisco, CA: Jossey-Bass; 2005.Google Scholar
  47. 47.
    Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101.CrossRefGoogle Scholar
  48. 48.
    NVivo qualitative data analysis Software; QSR International Pty Ltd. Version 10, 2012.Google Scholar
  49. 49.
    Onwuegbuzie AJ, Dickinson WB, Leech NL, Zoran AG. A qualitative framework for collecting and analyzing data in focus group research. Int J Qual Methods. 2009;8(3):1–21.CrossRefGoogle Scholar
  50. 50.
    Goldstein CM, Xie SS, Hawkins MA, Hughes JW. Reducing risk for cardiovascular disease: negative health behaviors in college students. Emerg Adulthood. 62(5):320–7.Google Scholar
  51. 51.
    Leshed G, Sengers P. I lie to myself that I have freedom in my own schedule: productivity tools and experiences of busyness. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 905–914): ACM; 2011.Google Scholar
  52. 52.
    Trockel MT, Barnes MD, Egget DL. Health-related variables and academic performance among first-year college students: implications for sleep and other behaviors. J Am Coll Heal. 2000;49(3):125–31.CrossRefGoogle Scholar
  53. 53.
    Lindsay GA, Hanks WA, Hurley RD, Dane S. Descriptive epidemiology of dozing and driving in a college student population. J Am Coll Heal. 1999;47(4):157–62.CrossRefGoogle Scholar
  54. 54.
    Pilcher JJ, Walters AS. How sleep deprivation affects psychological variables related to college students’ cognitive performance. J Am Coll Heal. 1997;46(3):121–6.CrossRefGoogle Scholar
  55. 55.
    Stock C, Wille L, Krämer A. Gender-specific health behaviors of German university students predict the interest in campus health promotion. Health Promot Int. 2001;16(2):145–54.CrossRefGoogle Scholar

Copyright information

© International Society of Behavioral Medicine 2019

Authors and Affiliations

  1. 1.Department of Clinical & Health PsychologyUniversity of FloridaGainesvilleUSA
  2. 2.Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoUSA

Personalised recommendations