Author(s):

  • Abril, Eulàlia Puig

Abstract:

For individuals trying to lose or maintain weight, self-tracking their weight, diet, or exercise is important. In the past, different tracking modes have been examined, like paper and pencil, memory, or personal digital assistants. But the recent advancement and adoption of mobile technologies could also result in easier and simpler self-tracking. However, little is known about self-trackers, their tracking modes, and the absolute or relative contribution of each tracking mode at the population level. This study fills this gap by (a) comparing self-trackers’ characteristics across tracking modes and against nontrackers and (b) testing the relationship between mobile self-tracking and tracking outcomes using a representative sample of data from the Pew Internet and American Life Project from 2012. Controls in the model include demographics, technology use, and health indicators. Results suggest that mobile self-trackers are younger and more educated and that mobile self-tracking is a positive contributor and the best tracking mode.

Document:

https://doi.org/10.1080/10810730.2016.1153756

References:
  1. Aadahl, M., & Jørgensen, T. (2003). Validation of a new self-report instrument for measuring physical activity. Medicine & Science in Sports & Exercise, 35(7), 1196–1202. doi:10.1249/01.MSS.0000074446.02192.14 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  2. Anderson, J., & Raine, L. (2014). The Internet of things will thrive by 2025. Retrieved from http://www.pewinternet.org/2014/05/14/internet-of-things/ [Google Scholar]
  3. Baker, R. C., & Kirschenbaum, D. S. (1998). Weight control during the holidays: Highly consistent self-monitoring as a potentially useful coping mechanism. Health Psychology, 17(4), 367–370. doi:10.1037/0278-6133.17.4.367 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  4. Bandura, A. (1988). Self-regulation of motivation and action through goal systems. In V. Hamilton, G. H. Bower, & N. H. Frijda (Eds.), Cognitive perspectives on emotion and motivation (pp. 37–61). Dordrecht, The Netherlands: Kluwer Academic. [Crossref][Google Scholar]
  5. Bandura, A. (1991). Social cognitive theory of self-regulation. Organizational Behavior and Human Decision Processes, 50(2), 248–287. doi:10.1016/0749-5978(91)90022-L [Crossref], [Web of Science ®][Google Scholar]
  6. Boase, J., & Ling, R. (2013). Measuring mobile phone use: Self-report versus log data. Journal of Computer-Mediated Communication, 18(4), 508–519. doi:10.1111/jcc4.12021 [Crossref], [Web of Science ®][Google Scholar]
  7. Bowling, A. (2005). Just one question: If one question works, why ask several? Journal of Epidemiology & Community Health, 59(5), 342–345. doi:10.1136/jech.2004.021204 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  8. Briggs, M. (2014). If numbers could speak: Bringing “quantified self” to an alternative demographic. USU Student Showcase, 2014(4). Retrieved from http://digitalcommons.usu.edu/student_showcase/33 [Google Scholar]
  9. Buhi, E. R., Trudnak, T. E., Martinasek, M. P., Oberne, A. B., Fuhrmann, H. J., & McDermott, R. J. (2013). Mobile phone-based behavioural interventions for health: A systematic review. Health Education Journal, 72(5), 564–583. doi:10.1177/0017896912452071 [Crossref], [Web of Science ®][Google Scholar]
  10. Burke, L. E., Conroy, M. B., Sereika, S. M., Elci, O. U., Styn, M. A., Acharya, S. D., … Glanz, K. (2011). The effect of electronic self-monitoring on weight loss and dietary intake: A randomized behavioral weight loss trial. Obesity, 19(2), 338–344. doi:10.1038/oby.2010.208 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  11. Burke, L. E., Wang, J., & Sevick, M. A. (2011). Self-monitoring in weight loss: A systematic review of the literature. Journal of the American Dietetic Association, 111(1), 92–102. doi:10.1016/j.jada.2010.10.008 [Crossref], [PubMed][Google Scholar]
  12. Butryn, M. L., Phelan, S., Hill, J. O., & Wing, R. R. (2007). Consistent self-monitoring of weight: A key component of successful weight loss maintenance. Obesity, 15(12), 3091–3096. doi:10.1038/oby.2007.368 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  13. Carels, R. A., Darby, L. A., Rydin, S., Douglass, O. M., Cacciapaglia, H. M., & O’Brien, W. H. (2005). The relationship between self-monitoring, outcome expectancies, difficulties with eating and exercise, and physical activity and weight loss treatment outcomes. Annals of Behavioral Medicine, 30(3), 182–190. doi:10.1207/s15324796abm3003_2 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  14. Centers for Disease Control and Prevention. (2013). Overweight and obesity. Retrieved from http://www.cdc.gov/obesity/data/adult.html [Google Scholar]
  15. Consolvo, S., McDonald, D. W., Toscos, T., Chen, M. Y., Froehlich, J., Harrison, B., & Libby, R. (2008). Activity sensing in the wild: A field trial of ubifit garden. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1797–1806). New York, NY: Association for Computing Machinery. [Google Scholar]
  16. Feiler, B. (2014, May). The United States of metrics. Retrieved from the New York Times website: www.nytimes.com/2014/05/18/fashion/the-united-states-of-metrics.html?_r=0 [Google Scholar]
  17. Fox, S., & Duggan, M. (2013). Tracking for health. Retrieved from http://www.pewinternet.org/2013/01/28/tracking-for-health/ [Google Scholar]
  18. Gasser, R., Brodbeck, D., Degen, M., Luthiger, J., Wyss, R., & Reichlin, S. (2006). Persuasiveness of a mobile lifestyle coaching application using social facilitation. In W. Ijsselsteijn, Y. de Kort, C. Midden, B. Eggen, & E. van den Hoven (Eds.), Persuasive technology (pp. 27–38). Berlin, Germany: Springer-Verlag. [Crossref][Google Scholar]
  19. Gerber, B. S., Stolley, M. R., Thompson, A. L., Sharp, L. K., & Fitzgibbon, M. L. (2009). Mobile phone text messaging to promote healthy behaviors and weight loss maintenance: A feasibility study. Health Informatics Journal, 15, 17–25. doi:10.1177/1460458208099865 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  20. Glanz, K., Lewis, F. M., & Rimer, B. K. (1990). Health behavior and health education: Theory, research, and practice. San Francisco, CA: Jossey-Bass. [Google Scholar]
  21. Gokee-Larose, J., Gorin, A. A., & Wing, R. R. (2009). Behavioral self-regulation for weight loss in young adults: A randomized controlled trial. International Journal of Behavioral Nutrition and Physical Activity, 6(1), 10. doi:10.1186/1479-5868-6-10 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  22. Grave, R. D., Calugi, S., & El Ghoch, M. (2013). Lifestyle modification in the management of obesity: Achievements and challenges. Eating and Weight Disorders, 18(4), 339–349. doi:10.1007/s40519-013-0049-4 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  23. Gustafson, D. H., Boyle, M. G., Shaw, B. R., Isham, A., McTavish, F., Richards, S., & Johnson, K. (2011). An e-health solution for people with alcohol problems. Alcohol Research & Health, 33(4), 327–337. [Web of Science ®][Google Scholar]
  24. Haapala, I., Barengo, N. C., Biggs, S., Surakka, L., & Manninen, P. (2009). Weight loss by mobile phone: A 1-year effectiveness study. Public Health Nutrition, 12, 2382–2391. doi:10.1017/S1368980009005230 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  25. Hull, S. J., Abril, E. P., Shah, D. V., Choi, M., Chih, M. Y., Kim, S. C., … Gustafson, D. H. (2016). Self-determination theory and computer-mediated support: Modeling effects on breast cancer patient’s quality-of-life.. Health Communication, 31, 1205–1214. [PubMed][Google Scholar]
  26. Hurling, R., Catt, M., De Boni, M., Fairley, B. W., Hurst, T., Murray, P., … Sodhi, J. S. (2007). Using Internet and mobile phone technology to deliver an automated physical activity program: Randomized controlled trial. Journal of Medical Internet Research, 9, e7. doi:10.2196/jmir.9.2.e7 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  27. Idler, E. L., & Benyamini, Y. (1997). Self-rated health and mortality: A review of twenty-seven community studies. Journal of Health and Social Behavior, 38, 21–37. doi:10.2307/2955359 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  28. Imayama, I., Alfano, C. M., Kong, A., Foster-Schubert, K. E., Bain, C. E., Xiao, L., … McTiernan, A. (2011). Dietary weight loss and exercise interventions effects on quality of life in overweight/obese postmenopausal women: A randomized controlled trial. International Journal of Behavioral Nutrition and Physical Activity, 8(1), 118. doi:10.1186/1479-5868-8-118 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  29. Kailas, A., Chong, C.-C., & Watanabe, F. (2010). From mobile phones to personal wellness dashboards. IEEE Pulse, 1(1), 57–63. doi:10.1109/MPUL.2010.937244 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  30. Khaylis, A., Yiaslas, T., Bergstrom, J., & Gore-Felton, C. (2010). A review of efficacious technology-based weight-loss interventions: Five key components. Telemedicine and E-Health, 16(9), 931–938. doi:10.1089/tmj.2010.0065 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  31. King, A. C., Taylor, C. B., Haskell, W. L., & Debusk, R. F. (1988). Strategies for increasing early adherence to and long-term maintenance of home-based exercise training in healthy middle-aged men and women. American Journal of Cardiology, 61(8), 628–632. doi:10.1016/0002-9149(88)90778-3 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  32. Klasnja, P., & Pratt, W. (2012). Healthcare in the pocket: Mapping the space of mobile-phone health interventions. Journal of Biomedical Informatics, 45(1), 184–198. doi:10.1016/j.jbi.2011.08.017 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  33. Kumanyika, S. K., Bowen, D., Van Horn, L., Perri, M. G., Czajkowski, S. M., & Schron, E. (2000). Maintenance of dietary behavior change. Health Psychology, 19(1, Suppl.), 42–56. doi:10.1037/0278-6133.19.Suppl1.42 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  34. Lane, S. J., Heddle, N. M., Arnold, E., & Walker, I. (2006). A review of randomized controlled trials comparing the effectiveness of hand held computers with paper methods for data collection. BMC Medical Informatics and Decision Making, 6, 23–33. doi:10.1186/1472-6947-6-23 [Crossref], [PubMed][Google Scholar]
  35. Lee, V. R. (2014). What’s happening in the “quantified self” movement? (Paper No. 491). Retrieved from http://digitalcommons.usu.edu/itls_facpub/491 [Google Scholar]
  36. Lichtman, S. W., Pisarska, K., Berman, E. R., Pestone, M., Dowling, H., Offenbacher, E., … Heymsfield, S. B. (1992). Discrepancy between self-reported and actual caloric intake and exercise in obese subjects. The New England Journal of Medicine, 327(27), 1893–1898. doi:10.1056/NEJM199212313272701 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  37. Linde, J. A., Jeffery, R. W., French, S. A., Pronk, N. P., & Boyle, R. G. (2005). Self-weighing in weight gain prevention and weight loss trials. Annals of Behavioral Medicine, 30(3), 210–216. doi:10.1207/s15324796abm3003_5 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  38. Mattila, E., Parkka, J., Hermersdorf, M., Kaasinen, J., Vainio, J., Samposalo, K., … Korhonen, I. (2008). Mobile diary for wellness management—Results on usage and usability in two user studies. IEEE Transactions on Information Technology in Biomedicine, 12(4), 501–512. doi:10.1109/TITB.2007.908237 [Crossref], [PubMed][Google Scholar]
  39. McClendon, M. J. (1994). Multiple regression and causal analysis. Itasca, IL: Peacock. [Google Scholar]
  40. McFedries, P. (2013). Tracking the quantified self [technically speaking]. Spectrum, IEEE, 50(8), 24. [Crossref], [Web of Science ®][Google Scholar]
  41. O’Neil, P. M., & Brown, J. D. (2005). Weighing the evidence: Benefits of regular weight monitoring for weight control. Journal of Nutrition Education and Behavior, 37(6), 319–322. doi:10.1016/S1499-4046(06)60163-2 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  42. Office of Disease Prevention and Health Promotion. (2016). Dietary guidelines. Retrieved from www.dietaryguidelines.gov [Google Scholar]
  43. Ogden, C. L., Carroll, M. D., Kit, B. K., & Flegal, K. M. (2013). Prevalence of obesity among adults: United States 2011–2012. Journal of the American Medical Association, 311(8), 806–814. doi:10.1001/jama.2014.732 [Crossref], [Web of Science ®][Google Scholar]
  44. Patrick, K., Griswold, W. G., Raab, F., & Intille, S. S. (2008). Health and the mobile phone. American Journal of Preventive Medicine, 35, 177–181. doi:10.1016/j.amepre.2008.05.001 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  45. Pew Research Center. (2016). Our survey methodology in detail. Retrieved from http://www.people-press.org/methodology/our-survey-methodology-in-detail [Google Scholar]
  46. Pingree, S., Hawkins, R., Baker, T., DuBenske, L., Roberts, L. J., & Gustafson, D. H. (2010). The value of theory for enhancing and understanding e-health interventions. American Journal of Preventive Medicine, 38(1), 103–109. doi:10.1016/j.amepre.2009.09.035 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  47. Prince, S. A., Adamo, K. B., Hamel, M. E., Hardt, J., Connor Gorber, S., & Tremblay, M. (2008). A comparison of direct versus self-report measures for assessing physical activity in adults: A systematic review. International Journal of Behavioral Nutrition and Physical Activity, 5, 56. doi:10.1186/1479-5868-5-56 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  48. Rosnow, R. L., & Rosenthal, R. (1996). Computing contrasts, effect sizes, and counternulls on other people’s published data: General procedures for research consumers. Psychological Methods, 1(4), 331–340. doi:10.1037/1082-989X.1.4.331 [Crossref], [Web of Science ®][Google Scholar]
  49. Seals, J. G. (2007). Integrating the transtheoretical model into the management of overweight and obese adults. Journal of the American Academy of Nurse Practitioners, 19(2), 63–71. doi:10.1111/j.1745-7599.2006.00196.x [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  50. Seaman, M. A., Levin, J. R., & Serlin, R. C. (1991). New developments in pairwise multiple comparisons: Some powerful and practicable procedures. Psychological Bulletin, 110(3), 577–586. doi:10.1037/0033-2909.110.3.577 [Crossref], [Web of Science ®][Google Scholar]
  51. Sherry, J. M., & Ratzan, S. C. (2012). Measurement and evaluation outcomes for mHealth communication: Don’t we have an app for that? Journal of Health Communication, 17(Suppl. 1), 1–3. doi:10.1080/10810730.2012.670563 [Taylor & Francis Online], [Web of Science ®][Google Scholar]
  52. Smarr, L. (2012). Quantifying your body: A how-to guide from a systems biology perspective. Biotechnology Journal, 7(8), 980–991. doi:10.1002/biot.201100495 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  53. Spring, B., Duncan, J. M., & Janke, E. (2013). Integrating technology into standard weight loss treatment: A randomized controlled trial. JAMA Internal Medicine, 173(2), 105–111. doi:10.1001/jamainternmed.2013.1221 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  54. Swan, M. (2009). Emerging patient-driven health care models: An examination of health social networks, consumer personalized medicine and quantified self-tracking. International Journal of Environmental Research and Public Health, 6(2), 492–525. doi:10.3390/ijerph6020492 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  55. Tsai, C. C., Lee, G., Raab, F., Norman, G. J., Sohn, T., Griswold, W. G., & Patrick, K. (2007). Usability and feasibility of PmEB: A mobile phone application for monitoring real time caloric balance. Mobile Networks and Applications, 12, 173–184. doi:10.1007/s11036-007-0014-4 [Crossref], [Web of Science ®][Google Scholar]
  56. Turner-McGrievy, G. M., Beets, M. W., Moore, J. B., Kaczynski, A. T., Barr-Anderson, D. J., & Tate, D. F. (2013). Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program. Journal of the American Medical Informatics Association, 20(3), 513–518. doi:10.1136/amiajnl-2012-001510 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  57. Ventä, L., Isomursu, M., Ahtinen, A., & Ramiah, S. (2008). “My phone is a part of my soul”—How people bond with their mobile phones. In Proceedings of the Second International Conference on Mobile Ubiquitous Computing, Systems, Services, and Technologies, 2008 (UBICOMM ’08), Sep. 29–Oct. 4, Valencia, Spain (pp. 311–317). IEEE. doi:10.1109/UBICOMM.2008.48. [Crossref][Google Scholar]
  58. Williams, G. C., Minicucci, D. S., Kouides, R. W., Levesque, C. S., Chirkov, V. I., Ryan, R. M., & Deci, E. L. (2002). Self-determination, smoking, diet and health. Health Education Research, 17, 512–521. doi:10.1093/her/17.5.512 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  59. Wing, R. R., & Hill, J. O. (2001). Successful weight loss maintenance. Annual Review of Nutrition, 21(1), 323–341. doi:10.1146/annurev.nutr.21.1.323 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  60. Wing, R. R., & Phelan, S. (2005). Long-term weight loss maintenance. American Journal of Clinical Nutrition, 82(1 Suppl.), 222S–225S. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  61. Wing, R. R., Tate, D. F., Gorin, A. A., Raynor, H. A., & Fava, J. L. (2006). A self-regulation program for maintenance of weight loss. The New England Journal of Medicine, 355(15), 1563–1571. doi:10.1056/NEJMoa061883 [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  62. World Health Organization. (2016). BMI classification. Retrieved from www.who.int/bmi/index.jsp [Google Scholar]
  63. Zickuhr, K. (2013). Location-based services. Retrieved from http://www.pewinternet.org/~/media//Files/Reports/2013/PIP_Location-based services 2013.pdf [Google Scholar]
  64. Zweifel, M. J. (2014). The power and Type I error rate of Holm’s procedure when the assumptions of normality and variance homogeneity are violated. Retrieved from http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1225&context=cehsdiss [Google Scholar]