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Social Media as a Nutrition Resource for Athletes: A Cross-Sectional Survey

Bourke, Bridget Ellen Philippa, Baker, Dane Francis, Braakhuis, Andrea Jane·2019·International Journal of Sport Nutrition and Exercise Metabolism

Abstract

Social media contains a wealth of nutrition information and proposes a cost-effective, highly engaging platform to deliver nutrition information to athletes. This study used an online questionnaire to determine whether New Zealand athletes are using social media as a source of nutrition information and to understand perceptions of social media as a nutrition resource. Quantitative data were analyzed using t tests, chi-squared tests, and logistic regression analysis. Inductive thematic analysis was adopted for the qualitative data. From the 306 athletes who completed the questionnaire, 65% reported social media use for nutrition purposes in the past 12 months. Social media use was predicted by both athlete status and gender. Female athletes were more likely to have used social media for nutrition purposes (odds ratio = 2.7, 95% confidence interval [1.52, 4.62], p = .001) than males. Elite athletes were less likely to have used social media for nutrition (odds ratio = 0.44, 95% confidence interval [0.24, 0.83], p = .011) than recreational athletes. Athletes commonly used social media for practical nutrition purposes, including recipes and information about restaurants/cafes. Perceived advantages of social media as a nutrition resource included ease of access, well-presented information, personal connectedness, and information richness. Athletes’ primary concern for obtaining nutrition information from social media was information unreliability.

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Research works printed but not linked: 26

  1. Carrotte, E.R., Vella, A.M., & Lim, M.S. (2015). Predictors of “liking” three types of health and fitness-related content on social media: A cross-sectional study. Journal of Medical Internet Research, 17(8), 205. PubMed ID: 26297689 doi:10.2196/jmir.4803 · DOI · Paper page
  2. Chou, W.-Y.S., Hunt, Y.M., Beckjord, E.B., Moser, R.P., & Hesse, B.W. (2009). Social media use in the United States: Implications for health communication. Journal of Medical Internet Research, 11(4), e48. PubMed ID: 19945947 doi:10.2196/jmir.1249 · DOI · Paper page
  3. Chung, C.F., Agapie, E., Schroeder, J., Mishra, S., Fogarty, J., & Munson, S.A. (2017). When personal tracking becomes social: Examining the use of Instagram for healthy eating. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Denver, CO, pp. 1674–1687. doi:10.1145/30254533025747 · DOI
  4. Heaney, S., O’Connor, H., Michael, S., Gifford, J., & Naughton, G. (2011). Nutrition knowledge in athletes: A systematic review. International Journal of Sport Nutrition and Exercise Metabolism, 21(3), 248–261. PubMed ID: 21719906 doi:10.1123/ijsnem.21.3.248 · DOI · Paper page
  5. Helm, J., & Jones, R.M. (2016). Practice paper of the Academy of Nutrition and Dietetics: Social media and the dietetics practitioner: Opportunities, challenges, and best practices. Journal of the Academy of Nutrition and Dietetics, 116(11), 1825–1835. PubMed ID: 27788767 doi:10.1016/j.jand.2016.09.003 · DOI
  6. Hull, M.V., Jagim, A.R., Oliver, J.M., Greenwood, M., Busteed, D.R., & Jones, M.T. (2016). Gender differences and access to a sports dietitian influence dietary habits of collegiate athletes. Journal of the International Society of Sports Nutrition, 13, 38. PubMed ID: 27777542 doi:10.1186/s12970-016-0149-4 · DOI · Paper page
  7. Jacobson, B.H., Sobonya, C., & Ransone, J. (2001). Nutrition practices and knowledge of college varsity athletes: A follow-up. Journal of Strength and Conditioning Research, 15(1), 63–68. PubMed ID: 11708709 doi:10.1519/1533-4287(2001)015<0063:NPAKOC>2.0.CO;2 · DOI · Paper page
  8. Khoo, C.S. (2014). Issues in information behaviour on social media. Library & Information Science Research, 24(2), 75.
  9. Lampe, C., Vitak, J., Gray, R., & Ellison, N.B. (2012). Perceptions of Facebook's value as an information source. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Austin, TX, pp. 3195–3204. doi:10.1145/2207676.2208739 · DOI
  10. Lis, D.M., Stellingwerff, T., Shing, C.M., Ahuja, K.D., & Fell, J.W. (2015). Exploring the popularity, experiences, and beliefs surrounding gluten-free diets in nonceliac athletes. International Journal of Sport Nutrition and Exercise Metabolism, 25(1), 37–45. PubMed ID: 24901744 doi:10.1123/ijsnem.2013-0247 · DOI · Paper page
  11. McCully, S.N., Don, B.P., & Updegraff, J.A. (2013). Using the Internet to help with diet, weight, and physical activity: Results from the Health Information National Trends Survey (HINTS). Journal of Medical Internet Research, 15(8), e148. PubMed ID: 23906945 doi:10.2196/jmir.2612 · DOI
  12. Oh, S., & Kim, S. (2014). College students’ use of social media for health in the USA and Korea. Information Research, 19(4), n4.
  13. Pálsdóttir, Á. (2014). Preferences in the use of social media for seeking and communicating health and lifestyle information. Information Research, 19(4), n4.
  14. Pollard, C.M., Pulker, C.E., Meng, X., Kerr, D.A., & Scott, J.A. (2015). Who uses the Internet as a source of nutrition and dietary information? An Australian population perspective. Journal of Medical Internet Research, 17(8), e209. PubMed ID: 26310192 doi:10.2196/jmir.4548 · DOI
  15. Ramaswami, C., Murugathasan, M., Narayanasamy, P., & Khoo, C.S. (2014). A survey of information sharing on Facebook. Information Research, 19(4), 247–249.
  16. Sin, S.-C.J., & Kim, K.-S. (2013). International students’ everyday life information seeking: The informational value of social networking sites. Library & Information Science Research, 35(2), 107–116. doi:10.1016/j.lisr.2012.11.006 · DOI
  17. Thomas, D.R. (2006). A general inductive approach for analyzing qualitative evaluation data. American Journal of Evaluation, 27(2), 237–246. doi:10.1177/1098214005283748 · DOI · Paper page
  18. Torres-McGehee, T.M., Pritchett, K.L., Zippel, D., Minton, D.M., Cellamare, A., & Sibilia, M. (2012). Sports nutrition knowledge among collegiate athletes, coaches, athletic trainers, and strength and conditioning specialists. Journal of Athletic Training, 47(2), 205–211. PubMed ID: 22488287 doi:10.4085/1062-6050-47.2.205 · DOI · Paper page
  19. Trakman, G.L., Forsyth, A., Devlin, B.L., & Belski, R. (2016). A systematic review of athletes’ and coaches’ nutrition knowledge and reflections on the quality of current nutrition knowledge measures. Nutrients, 8(9), 570–593. doi:10.3390/nu8090570 · DOI · Paper page
  20. Vaterlaus, J.M., Patten, E.V., Roche, C., & Young, J.A. (2015). #Gettinghealthy: The perceived influence of social media on young adult health behaviors. Computers in Human Behavior, 45, 151–157. doi:10.1016/j.chb.2014.12.013 · DOI · Paper page
  21. Visschers, V.H.M., Hartmann, C., Leins-Hess, R., Dohle, S., & Siegrist, M. (2013). A consumer segmentation of nutrition information use and its relation to food consumption behaviour. Food Policy, 42, 71–80. doi:10.1016/j.foodpol.2013.07.003 · DOI
  22. Williamson, K., Qayyum, A., Hider, P., & Liu, Y.-H. (2012). Young adults and everyday-life information: The role of news media. Library & Information Science Research, 34(4), 258–264. doi:10.1016/j.lisr.2012.05.001. · DOI
  23. Zhang, Y., He, D., & Sang, Y. (2013). Facebook as a platform for health information and communication: A case study of a diabetes group. Journal of Medical Systems, 37(3), 9942. PubMed ID: 23588823 doi:10.1007/s10916-013-9942-7 · DOI
  24. Zheng, Y. (2014). Patterns and motivations of young adults’ health information acquisitions on Facebook. Journal of Consumer Health on the Internet, 18(2), 157–175. doi:10.1080/15398285.2014.902275 · DOI
  25. Zilberman, D., & Kaplan, S. (2014). What the adoption literature can teach us about social media and network effects on food choices. Paper presented at the AAEA/EAAE/CAES Joint Symposium: Social Networks, Social Media and the Economics of Food, Montreal, Canada.
  26. Zuniga, K.E., Downey, D.L., McCluskey, R., & Rivers, C.A. (2017). Need for and interest in a sports nutrition mobile device application among Division I collegiate athletes. International Journal of Sport Nutrition and Exercise Metabolism, 27(1), 43–49. PubMed ID: 27284955 doi:10.1123/ijsnem.2015-0305 · DOI · Paper page

Metadata

Authors
Bourke, B. E. P., Baker, D. F., & Braakhuis, A. J.
Affiliations
  • The University of Auckland
  • High Performance Sport New Zealand
Venue
International Journal of Sport Nutrition and Exercise Metabolism
Published
2019-07-01
Volume
29
Issue
4
Pages
364-370
ISSN
  • 1526-484X
  • 1543-2742
Cited by
25
References
3

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