Mobile Networks and Applications

, Volume 12, Issue 2–3, pp 173–184 | Cite as

Usability and Feasibility of PmEB: A Mobile Phone Application for Monitoring Real Time Caloric Balance

  • Christopher C. TsaiEmail author
  • Gunny Lee
  • Fred Raab
  • Gregory J. Norman
  • Timothy Sohn
  • William G. Griswold
  • Kevin Patrick


Obesity is a major public health challenge with over 65% of US adults either overweight or obese. Estimated annual costs of obesity are $78.5 billion. Self-monitoring is a critical skill for successful weight management. However, self-monitoring is labor-intensive, and compliance is often difficult. In this paper, the authors describe the Patient-Centered Assessment and Counseling Mobile Energy Balance (PmEB) mobile phone application that allows users to self-monitor caloric balance in real time. The application was developed and applied in a four-phase iterative research and development methodology. A usability study and a preliminary feasibility study were conducted. The 1 month feasibility study measured compliance and satisfaction among a sample of 15 participants randomized to one of three groups: (1) a paper diary group, (2) a PmEB group with one daily prompt, and (3) a PmEB group with three daily prompts. PmEB scored highly on usability, compliance, and satisfaction. In addition, mobile phone group users scored PmEB the same as or better than Paper Group members scored the paper diary in nearly all categories. Thematic analysis of comments revealed very positive reviews of PmEB as well as areas for improvement. PmEB is both usable and feasible for weight management self-monitoring, and the iterative pilot study methodology was effective in improving its usability.


behavioral science mobile communication software prototyping user centered design methodology 


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  1. 1.
    Finkelstein EA, Fiebelkorn IC, Wang G (2003) National medical spending attributable to overweight and obesity: how much, and who’s paying? Health Aff W3:219–226Google Scholar
  2. 2.
    Center for Disease Control and Prevention. Available: (accessed July 7, 2005)
  3. 3.
    Wing RR, Hill JO (2001) Successful weight loss maintenance. Annu Rev Nutr 21:323–341CrossRefGoogle Scholar
  4. 4.
    Qi BB, Dennis KE (2000) The adoption of eating behaviors conducive to weight loss. Eat Behav 1:23–31CrossRefGoogle Scholar
  5. 5.
    Mattfeldt-Beman M, Corrigan SA, Stevens VJ, Sugars CP, Dalcin AT, Givig MJ, Copeland KC (1999) Participants evaluation of a weight-loss program. J Am Diet Assoc 99:66–71CrossRefGoogle Scholar
  6. 6.
    Stone A, Turkkan J, Jobe J et al (2000) The science of self report. Lawrence Erlbaum Associates, Inc., Mahwah, NJGoogle Scholar
  7. 7.
    Stone A, Shiffman S (2002) Capturing momentary self-report data: a proposal for reporting guidelines. Ann Behav Med 24:236–243CrossRefGoogle Scholar
  8. 8.
    Smyth JM, Stone AA (2003) Ecological momentary assessment research in behavioral medicine. J Happiness Stud 4:35–52CrossRefGoogle Scholar
  9. 9.
    Stone AA, Shiffman S, Schwartz JE, Broderick JE, Hufford MR (2003) Patient compliance with paper and electronic diaries. Control Clin Trials 24:182–199CrossRefGoogle Scholar
  10. 10.
    Patrick K, Intille SS, Zabinski MF (2005) An ecological framework for cancer communication: implications for research. J Med Internet Res 7(3):e23, Jul 1CrossRefGoogle Scholar
  11. 11.
    Intille SS, Kukla C, Farzanfar R, Bakr W (2003) Just-in-time technology to encourage incremental, dietary behavior change. In Proc. American Medical Informatics Association (AMIA) SympGoogle Scholar
  12. 12.
    Lee G, Tsai C, Griswold WG, Raab F, Patrick K (2006) PmEB: a mobile phone application for monitoring caloric balance. In CHI’06 extended abstracts on human factors in computing systems, pp 1013–1018Google Scholar
  13. 13.
    Collins RL, Kashdan TB, Gollnisch G (2003) The feasibility of using cellular phones to collect ecological momentary assessment data: application to alcohol consumption. Exp Clin Psychopharmacol 11:73–78CrossRefGoogle Scholar
  14. 14.
    Scholtz J, Consolvo S (2004) Towards a discipline for evaluating ubiquitous computing applications. Intel Corporation, All rights reservedGoogle Scholar
  15. 15.
    Brown B, Chetty M, Grimes A, Harmon E (2006) Reflecting on health: a system for students to monitor diet and exercise. In CHI’06 extended abstracts on human factors in computing systems, pp 1807–1812Google Scholar
  16. 16.
    Siek KA, Connelly KH, Rogers Y. Pride and prejudice: learning how chronically ill people think about food. In Proc. CHI 2006, ACM, pp 947–950Google Scholar
  17. 17.
    Toscos T, Faber A, An S, Gandhi MP (2006) Chick clique: persuasive technology to motivate teenage girls to exercise. In CHI’06 extended abstracts on human factors in computing systems, pp 1873–1878Google Scholar
  18. 18.
    Frankenfield D, Muth ER, Rowe WA (1998) The Harris-Benedict studies of human basal metabolism: history and limitations. J Am Diet Assoc 98:439–445CrossRefGoogle Scholar
  19. 19.
    Ainsworth BE, Haskell WL, Whitt MC et al (2000) Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 32(9 Suppl):S498–S516Google Scholar
  20. 20.
    Shortliffe EH, Perreault LE, Wiederhold G, Fagan LM (2001) Medical informatics: computer applications in health care and biomedicine. Springer, New YorkGoogle Scholar
  21. 21.
    Nielsen J, Mack R (1994) Usability inspection methods. Wiley, New YorkGoogle Scholar
  22. 22.
    Palmblad M, Tiplady B (2004) Electronic diaries and questionnaires: designing user interfaces that are easy for all patients to use. Qual Life Res 13:1199–1207CrossRefGoogle Scholar
  23. 23.
    Hufford MR, Shiffman S (2003) Assessment methods for patient-reported outcomes. Dis Manag Health Outcomes 11(2):77–86CrossRefGoogle Scholar
  24. 24.
    Rubin J (1994) Handbook of usability testing: how to plan, design, and conduct effective tests. Wiley, New YorkGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Christopher C. Tsai
    • 1
    Email author
  • Gunny Lee
    • 2
  • Fred Raab
    • 3
  • Gregory J. Norman
    • 3
  • Timothy Sohn
    • 4
  • William G. Griswold
    • 4
  • Kevin Patrick
    • 3
  1. 1.Decision Systems GroupBrigham & Women’s HospitalBostonUSA
  2. 2.SCIL GroupStanford UniversityStanfordUSA
  3. 3.Family and Preventive MedicineUniversity of CaliforniaSan DiegoUSA
  4. 4.Computer Science and EngineeringUniversity of CaliforniaSan DiegoUSA

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