Advertisement

Journal of Computing in Higher Education

, Volume 25, Issue 1, pp 12–26 | Cite as

The feasibility of using video journaling to collect ecological momentary assessment data: application to health behavior change interventions

  • Bridget F. Melton
  • Lauren E. Bigham
  • Helen W. Bland
Article

Abstract

The purpose of this research was to evaluate the feasibility of an ecological momentary assessment (EMA) technique in a health behavior change intervention offered within university general health courses. A six-week health behavior change project was used with two groups: video journaling and traditional (pencil and paper) group. Research methodology employed was a quantitative, quasi-experimental, control and experimental group posttest comparison design. Stage of change data and program satisfaction surveys were collected from participants at a midsized southeastern university (n = 72; 36 video and 36 traditional). Participants were selected through non-probability, purposive sampling. Upon completion of the behavior change intervention 88.9 % (N = 32) of video journaling participants reported being in either the action or maintenance stage of change compared to 63.9 % (N = 23) of the traditional group. Significant difference was found between the video journaling and traditional groups in levels of satisfaction with the program (M = 3.96, SE = 0.79; M = 3.53, SE = .53 respectively; t = −2.74, p < 0.05). EMA techniques using video journaling to aid behavior change interventions among late adolescence showed promise with further research needed to focus on long-term effects of such interventions.

Keywords

Health behavior change Late adolescence Self-monitoring Ecological momentary assessment 

References

  1. Abraham, C., & Michie, A. (2008). A taxonomy of behavior change techniques used in interventions. Health Psychology, 27(3), 379–387.CrossRefGoogle Scholar
  2. American College Health Association (ACHA). (2010). American college health association-national college health assessment II: Reference group executive summary Spring 2010. Linthicum: American College Health Association.Google Scholar
  3. Bellg, A. J., Borrelli, B., Resnick, B., Hecht, J., Minicucci, D. S., Ory, M., et al. (2004). Enhancing treatment fidelity in health behavior change studies: Best practices and recommendations from the NIH behavior change consortium. Health Psychology, 23(5), 443–451.CrossRefGoogle Scholar
  4. Brener, N. D., & Gowda, V. R. (2001). US college students’ reports of receiving health information on college campuses. American Journal of Preventative Medicine, 18, 18–27.Google Scholar
  5. Clough, B., & Casey, L. (2011). Technological adjuncts to increase adherence to therapy: A review. Clinical Psychology Review, 31(5), 697–710.CrossRefGoogle Scholar
  6. Cohn, A., Hunter-Reel, D., Hagman, B., & Mitchell, J. (2011). Promoting behavior change from alcohol use through mobile technology: The future of ecological momentary assessment. Alcoholism, Clinical and Experimental Research, 35(12), 2209–2215.CrossRefGoogle Scholar
  7. Collins, R. L., Kashdan, T. B., & Gollnisch, G. (2003). The feasibility of using cellular phones to collect ecological momentary assessment data: Application to alcohol consumption. Experimental and Clinical Psychopharmacology, 11(1), 73–78.CrossRefGoogle Scholar
  8. DiClemente, C. C., Marinilli, A. S., & Singh, L. E. (2001). The role of feedback in the process of health behavior change. American Journal of Health Behavior, 25(3), 217–227.CrossRefGoogle Scholar
  9. Dishman, R. K., Jackson, A. S., & Bray, M. S. (2010a). Validity of processes of change in physical activity among college students in the TIGER study. Annals of Behavioral Medicine, 40(2), 164–175. doi: 10.1007/s12160-010-9208-2.CrossRefGoogle Scholar
  10. Dishman, R., Vandenberg, R., Motl, R., & Nigg, C. (2010b). Using constructs of the transtheoretical model to predict classes of change in regular physical activity: A multi-ethnic longitudinal cohort study. Annals of Behavioral Medicine: A Publication of the Society Of Behavioral Medicine, 40(2), 150–163.CrossRefGoogle Scholar
  11. Gorely, T., Marshall, S. J., Biddle, S. J. H., & Cameron, N. (2007). The prevalence of leisure time sedentary behavior and physical activity in adolescent girls: An ecological momentary assessment approach. International Journal of Pediatric Obesity, 2, 227–234.CrossRefGoogle Scholar
  12. Grange, D. L., Gorin, A., Dymek, M., & Stone, A. (2002). Does ecological momentary assessment improve cognitive behavioral therapy in binge eating disorder? A pilot study. European Eating Disorders Review, 10, 316–328.CrossRefGoogle Scholar
  13. Gwaltney, C. J., Bartolomei, R., Colby, S. M., & Kahler, C. W. (2008). Ecological momentary assessment of adolescent smoking cessation: A feasibility study. Nicotine Tobacco Research, 10(7), 1185–1190.CrossRefGoogle Scholar
  14. Hayman, B., Wilkes, L., & Jackson, D. (2012). Journaling: identification of challenges and reflection on strategies. Nurse Researcher, 19(3), 27–31.Google Scholar
  15. Heron, K. E., & Smyth, J. M. (2010). Ecological momentary interventions: Incorporating mobile technology into psychosocial and health behavior treatments. British Journal of Health Psychology, 15(1), 1–39.CrossRefGoogle Scholar
  16. Hey, W. T., Calderon, K. S., & Carroll, H. (2006). Use of body-mind-spirit dimensions for the develop of a wellness behavior and characteristic inventory for college students. Health Promotional Practice, 7(1), 125–133.CrossRefGoogle Scholar
  17. Hicks, T., & Heastie, S. (2008). High school to college transition: A profile of the stressors, physical and psychological health issues that affect the first-year on-campus college student. Journal of Cultural Diversity, 15(3), 143–147.Google Scholar
  18. Hufford, M. R., Shields, A. L., Shiffman, S., Paty, J., & Balabanis, M. (2002). Reactivity to ecological momentary assessment: An example using undergraduate problem drinkers. Psychology of Addictive Behaviors, 16(3), 205–211.CrossRefGoogle Scholar
  19. Insel, P. M., & Roth, W. T. (2012). Connect core concepts in health (12th ed.). New York: McGraw-Hill Publishing.Google Scholar
  20. Lawrence, R. S., Gootman, J., & Sim, L. J. (2009). Adolescent health services: Missing opportunities. Washington, DC US: National Academies Press.Google Scholar
  21. Marcus, B. H., Selby, V. C., Niaura, R. S., & Rossi, J. S. (1992). Self-efficacy and the stages of exercise behavior change. Research Quarterly for Exercise and Sport, 63, 60–66.CrossRefGoogle Scholar
  22. Mathers, M., Canterford, L., Olds, T., Hesketh, K., Ridley, K., & Wake, M. (2009). Electronic media use and adolescent health and well-being: Cross-sectional community study. Academic Pediatrics, 9(5), 307–314.CrossRefGoogle Scholar
  23. McKenzie, J. F., Neiger, B. L., & Thackery, R. (2013). Planning, Implementing, & Evaluating Health Promotion Programs as a primer (6th ed.). New York: Pearson.Google Scholar
  24. Minnis, A. M., & Padian, N. S. (2001). Reliability of adolescents’ self-reported sexual behavior: A comparison of two diary methodologies. Journal of Adolescent Health, 28(5), 394–403. doi: 10.1016/S1054-139X(00)00218-4.CrossRefGoogle Scholar
  25. National Center for Education Statistics. (2010). The Condition of Education 2010 (NCES 2010–028). Washington, DC: US Government Printing Office.Google Scholar
  26. Prochaska, J. O., & DiClemente, C. C. (1984). The transtheoretical approach: crossing traditional boundaries of therapy. Homewood: Dorsey Press.Google Scholar
  27. Prochaska, J. O., Johnson, S., & Lee, P. (2009). The transtheoretical model of behavior change. In S. A. Shumaker, J. K. Ockene, & K. A. Riekert (Eds.), The handbook of health behavior change (3rd ed., pp. 59–83). New York: Springer Publishing Co.Google Scholar
  28. Schueller, S. M. (2011). To each his own well-being boosting intervention: Using preference to guide selection. The Journal of Positive Psychology, 6(4), 300–313. doi: 10.1080/17439760.2011.577092.CrossRefGoogle Scholar
  29. Shiffman, S., & Stone, A. A. (1998). Introduction to the special section: Ecological momentary assessment in health psychology. Health Psychology, 17, 3–5.CrossRefGoogle Scholar
  30. Sira, N., & Pawlak, R. (2010). Prevalence of overweight and obesity, and dieting attitudes among Caucasian and African American college students in Eastern North Carolina: A cross-sectional survey. Nutrition Research & Practice, 4(1), 36–42.CrossRefGoogle Scholar
  31. Sternfeld, B., Jiang, S. F., Picchi, T., Chasen-Taber, L., Ainsworth, B., & Quesenberry, C. P. (2012). Evaluation of cell phone-based physical activity diary. Medicine & Science in Sport and Exercise, 44(3), 487–495.CrossRefGoogle Scholar
  32. Stone, A. A., & Shiffman, S. (1994). Ecological momentary assessment (EMA) in behavioral medicine. Annals of Behavioral Medicine, 16, 199–202.Google Scholar
  33. Thomas, J., Bond, D., Ryder, B., Leahey, T., Vithiananthan, S., Roye, G., et al. (2011). Ecological momentary assessment of recommended postoperative eating and activity behaviors. Surgery for Obesity and Related Diseases: Official Journal of the American Society for Bariatric Surgery, 7(2), 206–212.CrossRefGoogle Scholar
  34. United States Department of health and human services, healthy people 2020. (2011, June 29). Adolescent: Overview. Retrieved from http://www.healthypeople.gov/2020/topicsobjectives2020/overview.aspx?topicId=2#Ref_47.
  35. Von Ah, D., Ebert, S., Ngamvitroj, A., Park, N., & Kang, D. (2004). Predictors of health behaviors in college students. Journal of Advanced Nursing, 48(5), 463–474.CrossRefGoogle Scholar
  36. Wang, C. C. (2000). The future of health promotion: Talkin’ technology blues. Health Promotion Practice, 1(1), 77–80.CrossRefGoogle Scholar
  37. Werch, C., Ames, S., Moore, M., Thombs, D., & Hart, A. (2009). Health behavior insights-The transtheorectical/Stage of change model: Carlo C. DiClemente, PhD. Health Promotional Practice, 10(1), 41–48.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Bridget F. Melton
    • 1
  • Lauren E. Bigham
    • 2
  • Helen W. Bland
    • 1
  1. 1.Department of Health and KinesiologyGeorgia Southern UniversityStatesboroUSA
  2. 2.Department of PsychologyUniversity of GeorgiaStatesboroUSA

Personalised recommendations