Skip to main content

Advertisement

Log in

Youth-centered design and usage results of the iN Touch mobile self-management program for overweight/obesity

  • Original Article
  • Published:
Personal and Ubiquitous Computing Aims and scope Submit manuscript

Abstract

Overweight/obesity among youth is a grave concern in the USA due to its potential impact on illness such as hypertension, high cholesterol, type 2 diabetes and asthma. This paper reports on the design and usage of iN Touch, a mobile self-management application for tracking observations of daily living (ODLs) in a health coaching program for low-income, urban, minority youth 13–24 years with overweight/obesity. We applied a youth-centered, participatory design approach to design and implementation of the technology and intervention with a representative 10-member youth advisory board. The recommendations were implemented prior to launching the technology in an intervention phase. The application with food, exercise, mood and socializing trackers along with pictures and notes was delivered on an iPod Touch to 24 participants. Mixed methods were applied to evaluate technology acceptance including system-generated data, questionnaires and exit interviews. There was good engagement among participants who recorded 2,117 ODLs over 6 months. The mean rating for usefulness was 3.50/5, SD = 1.18 and for ease of use, 3.83/5, SD = 1.27. Qualitative analysis of exit interviews found that design recommendations were fulfilled and the resulting technology was compelling. Future papers will report on the health impacts of iN Touch.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Janssen I, Katzmarzyk PT, Boyce WF, Vereecken C, Mulvihill C, Roberts C, Currie C, Pickett W (2005) Comparison of overweight and obesity prevalence in school-aged youth from 34 countries and their relationships with physical activity and dietary patterns. Obes Rev 6(2):123–132. doi:10.1111/j.1467-789X.2005.00176.x

    Article  Google Scholar 

  2. Bethell C, Simpson L, Stumbo S, Carle AC, Gombojav N (2010) National, state, and local disparities in childhood obesity. Health Aff (Millwood) 29(3):347–356. doi:10.1377/hlthaff.2009.0762

    Article  Google Scholar 

  3. Skelton JA, Cook SR, Auinger P, Klein JD, Barlow SE (2009) Prevalence and trends of severe obesity among US children and adolescents. Acad Pediatr 9(5):322–329. doi:10.1016/j.acap.2009.04.005

    Article  Google Scholar 

  4. Rossen LM, Schoendorf KC (2012) Measuring health disparities: trends in racial-ethnic and socioeconomic disparities in obesity among 2- to 18-year old youth in the United States, 2001–2010. Ann Epidemiol 22(10):698–704. doi:10.1016/j.annepidem.2012.07.005

    Article  Google Scholar 

  5. Ball K, Brown W, Crawford D (2002) Who does not gain weight? Prevalence and predictors of weight maintenance in young women. Int J Obes Relat Metab Disord 26(12):1570–1578

    Article  Google Scholar 

  6. Gordon-Larsen P, Adair LS, Nelson MC, Popkin BM (2004) Five-year obesity incidence in the transition period between adolescence and adulthood: the National Longitudinal Study of Adolescent Health. Am J Clin Nutr 80(3):569–575

    Google Scholar 

  7. Ogden CL, Carroll MD, Kit BK, Flegal KM (2012) Prevalence of obesity and trends in body mass index among US children and adolescents, 1999–2010. JAMA 307(5):483–490. doi:10.1001/jama.2012.40

    Article  Google Scholar 

  8. Poobalan A, Aucott L, Precious E, Crombie I, Smith W (2010) Weight loss interventions in young people (18 to 25 year olds): a systematic review. Obes Rev 11(8):580–592

    Article  Google Scholar 

  9. Melnyk BM, Jacobson D, Kelly S, Belyea M, Shaibi G, Small L, O’Haver J, Marsiglia FF (2013) Promoting healthy lifestyles in high school adolescents. Am J Prev Med 45(4):407–415

    Article  Google Scholar 

  10. Savoye M, Nowicka P, Shaw M, Yu S, Dziura J, Chavent G, O’Malley G, Serrecchia JB, Tamborlane WV, Caprio S (2011) Long-term results of an obesity program in an ethnically diverse pediatric population. Pediatrics 127(3):402–410

    Article  Google Scholar 

  11. Kirschenbaum DS, Germann JN, Rich BH (2005) Treatment of morbid obesity in low-income adolescents: effects of parental self-monitoring. Obes Res 13(9):1527–1529. doi:10.1038/oby.2005.187

    Article  Google Scholar 

  12. Holzinger A, Dorner S, Födinger M, Valdez AC, Ziefle M (2010) Chances of increasing youth health awareness through mobile wellness applications. In: Leitner G, Hitz M, Holzinger A (eds) HCI in work and learning, life and leisure. Springer, Heidelberg, pp 71–81

  13. Kauer SD, Reid SC, Crooke AH, Khor A, Hearps SJ, Jorm AF, Sanci L, Patton G (2012) Self-monitoring using mobile phones in the early stages of adolescent depression: randomized controlled trial. J Med Internet Res 14(3):e67. doi:10.2196/jmir.1858

    Article  Google Scholar 

  14. Swan M (2013) The quantified self: fundamental disruption in big data science and biological discovery. Big Data 1(2):85–99. doi:10.1089/big.2012.0002

    Article  Google Scholar 

  15. Namioka A, Schuler D (1993) Participatory design: principles and practices. Lawrence Earlbaum, Hillsdale, NJ

  16. Storni C (2013) Design challenges for ubiquitous and personal computing in chronic disease care and patient empowerment: a case study rethinking diabetes self-monitoring. Pers Ubiquitous Comput 1–14. doi:10.1007/s00779-013-0707-6

  17. Orel T (1995) Designing self-diagnostic devices. In: Buchanan R, Margolin V (eds) Discovering design. The University of Chicago Press, Chicago, pp 77–102

    Google Scholar 

  18. Mamykina L, Mynatt ED, Kaufman DR (2006) Investigating health management practices of individuals with diabetes. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 927–936

  19. Kaplan B, Brennan PF (2001) Consumer informatics supporting patients as co-producers of quality. J Am Med Inform Assoc 8(4):309–316

    Article  Google Scholar 

  20. Ballegaard SA, Hansen TR, Kyng M (2008) Healthcare in everyday life: designing healthcare services for daily life. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 1807–1816

  21. Storni C (2010) Multiple forms of appropriation in self-monitoring technology: reflections on the role of evaluation in future self-care. Int J Hum Comput Interact 26(5):537–561

    Article  Google Scholar 

  22. Nollen NL, Hutcheson T, Carlson S, Rapoff M, Goggin K, Mayfield C, Ellerbeck E (2013) Development and functionality of a handheld computer program to improve fruit and vegetable intake among low-income youth. Health Educ Res 28(2):249–264. doi:10.1093/her/cys099

    Article  Google Scholar 

  23. Reid SC, Kauer SD, Hearps SJ, Crooke AH, Khor AS, Sanci LA, Patton GC (2011) A mobile phone application for the assessment and management of youth mental health problems in primary care: a randomised controlled trial. BMC Fam Pract 12:131. doi:10.1186/1471-2296-12-131

    Article  Google Scholar 

  24. Brennan PF, Downs SJ (2009) Project HealthDesign: rethinking the power and potential of personal health records. Round one final report. Robert Wood Johnson Foundation. http://www.projecthealthdesign.org/media/file/Round%20One%20PHD%20Final%20Report6.17.09.pdf

  25. Miller W, Rollnick S (2002) Motivational interviewing: preparing people for change, 2nd edn. Guillford Press, New York

    Google Scholar 

  26. Flattum C, Friend S, Neumark-Sztainer D, Story M (2009) Motivational interviewing as a component of a school-based obesity prevention program for adolescent girls. J Am Diet Assoc 109(1):91–94

    Article  Google Scholar 

  27. Brennan L, Walkley J, Fraser SF, Greenway K, Wilks R (2008) Motivational interviewing and cognitive behaviour therapy in the treatment of adolescent overweight and obesity: study design and methodology. Contemp Clin Trials 29(3):359–375

    Article  Google Scholar 

  28. Resnicow K, Davis R, Rollnick S (2006) Motivational interviewing for pediatric obesity: conceptual issues and evidence review. J Am Diet Assoc 106(12):2024–2033

    Article  Google Scholar 

  29. Davis FD (1986) A technology acceptance model for empirically testing new end-user information systems: theory and results. Doctoral dissertation, Massachusetts Institute of Technology, Cambridge

Download references

Acknowledgments

The iN Touch study was funded by the Robert Wood Johnson Foundation and is a project of Project HealthDesign. We thank Hali Hammer, MD, and Aisha Mays, MD, from San Francisco General Hospital for assisting with recruitment and providing clinical supervision for the study, David Guldmann, LCSW, from San Francisco General Hospital for advice on the mood and socializing trackers, Janelle Charles from San Francisco State University for assisting with recruitment and data collection, Douglas Trauner of TheCarrot for collaborating on development and implementation of the iN Touch application.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Katherine K. Kim.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, K.K., Logan, H.C., Young, E. et al. Youth-centered design and usage results of the iN Touch mobile self-management program for overweight/obesity. Pers Ubiquit Comput 19, 59–68 (2015). https://doi.org/10.1007/s00779-014-0808-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00779-014-0808-x

Keywords

Navigation