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Adherence to self-monitoring healthy lifestyle behaviours through mobile phone-based ecological momentary assessments and photographic food records over 6 months in mostly ethnic minority mothers

  • W Scott Comulada (a1), Dallas Swendeman (a1), Maryann K Koussa (a1), Deborah Mindry (a2), Melissa Medich (a3), Deborah Estrin (a4), Neil Mercer (a5) and Nithya Ramanathan (a6)...
Abstract
Objective

Mobile phones can replace traditional self-monitoring tools through cell phone-based ecological momentary assessment (CEMA) of lifestyle behaviours and camera phone-based images of meals, i.e. photographic food records (PFR). Adherence to mobile self-monitoring needs to be evaluated in real-world treatment settings. Towards this goal, we examine CEMA and PFR adherence to the use of a mobile app designed to help mothers self-monitor lifestyle behaviours and stress.

Design/Setting

In 2012, forty-two mothers recorded CEMA of diet quality, exercise, sleep, stress and mood four times daily and PFR during meals over 6 months in Los Angeles, California, USA.

Subjects

A purposive sample of mothers from mixed ethnicities.

Results

Adherence to recording CEMA at least once daily was higher compared with recording PFR at least once daily over the study period (74 v. 11 %); adherence to both types of reports decreased over time. Participants who recorded PFR for more than a day (n 31) were more likely to be obese v. normal- to overweight and to have higher blood pressure, on average (all P<0·05). Based on random-effects regression, CEMA and PFR adherence was highest during weekdays (both P<0·01). Additionally, PFR adherence was associated with older age (P=0·04). CEMA adherence was highest in the morning (P<0·01). PFR recordings occurred throughout the day.

Conclusions

Variations in population and temporal characteristics should be considered for mobile assessment schedules. Neither CEMA nor PFR alone is ideal over extended periods.

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Corresponding author
* Corresponding author: Email wcomulada@mednet.ucla.edu
References
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1. Burke, LE, Wang, J & Sevick, MA (2011) Self-monitoring in weight loss: a systematic review of the literature. J Am Diet Assoc 111, 92102.
2. Beasley, JM, Riley, WT, Davis, A et al. (2008) Evaluation of a PDA-based dietary assessment and intervention program: a randomized controlled trial. J Am Coll Nutr 27, 280286.
3. Burke, LE, Styn, MA, Glanz, K et al. (2009) SMART trial: a randomized clinical trial of self-monitoring in behavioral weight management – design and findings. Contemp Clin Trials 30, 540551.
4. Burke, LE, Conroy, MB, Sereika, SM et al. (2011) The effect of electronic self-monitoring on weight loss and dietary intake: a randomized behavioral weight loss trial. Obesity (Silver Spring) 19, 338344.
5. Turner-McGrievy, GM, Beets, MW, Moore, JB et al. (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. J Am Med Inform Assoc 20, 513518.
6. Free, C, Phillips, G, Galli, L et al. (2013) The effectiveness of mobile-health technology-based health behavior change or disease management interventions for health care consumers: a systematic review. PLoS Med 10, e1001362.
7. Heron, KE & Smyth, JM (2010) Ecological momentary interventions: incorporating mobile technology into psychosocial and health behavior treatments. Br J Health Psychol 15, 139.
8. Thompson, FE, Subar, AF, Loria, CM et al. (2010) Need for technological innovation in dietary assessment. J Am Diet Assoc 110, 4851.
9. Piasecki, TM, Hufford, MR, Solhan, M et al. (2007) Assessing clients in their natural environments with electronic diaries: rationale, benefits, limitations, and barriers. Psychol Assess 19, 2543.
10. Stone, AA & Shiffman, S (1994) Ecological momentary assessment (EMA) in behavioral medicine. Ann Behav Med 16, 199202.
11. Arsand, E, Tufano, JT, Ralston, JD et al. (2008) Designing mobile dietary management support technologies for people with diabetes. J Telemed Telecare 14, 329332.
12. Higgins, JA, LaSalle, AL, Zhaoxing, P et al. (2009) Validation of photographic food records in children: are pictures really worth a thousand words? Eur J Clin Nutr 63, 10251033.
13. Jia, W, Chen, HC, Yue, Y et al. (2014) Accuracy of food portion size estimation from digital pictures acquired by a chest-worn camera. Public Health Nutr 17, 16711681.
14. Kong, FY & Tan, JD. (2012) DietCam: automatic dietary assessment with mobile camera phones. Pervasive Mob Comput 8, 147163.
15. Six, BL, Schap, TE, Zhu, FM et al. (2010) Evidence-based development of a mobile telephone food record. J Am Diet Assoc 110, 7479.
16. Daugherty, BL, Schap, TE, Ettienne-Gittens, R et al. (2012) Novel technologies for assessing dietary intake: evaluating the usability of a mobile telephone food record among adults and adolescents. J Med Internet Res 14, e58.
17. Probst, Y, Nguyen, DT, Tran, MK et al. (2015) Dietary assessment on a mobile phone using image processing and pattern recognition techniques: algorithm design and system prototyping. Nutrients 7, 61286138.
18. Rollo, ME, Ash, S, Lyons-Wall, P et al. (2011) Trial of a mobile phone method for recording dietary intake in adults with type 2 diabetes: evaluation and implications for future applications. J Telemed Telecare 17, 318323.
19. Wang, D-H, Kogashiwa, M, Ohta, S et al. (2002) Validity and reliability of a dietary assessment method: the application of a digital camera with a mobile phone card attachment. J Nutr Sci Vitaminol (Tokyo) 48, 498504.
20. Reeves, MM, Terranova, CO, Eakin, EG et al. (2014) Weight loss intervention trials in women with breast cancer: a systematic review. Obes Rev 15, 749768.
21. Arsand, E, Froisland, DH, Skrovseth, SO et al. (2012) Mobile health applications to assist patients with diabetes: lessons learned and design implications. J Diabetes Sci Technol 6, 11971206.
22. Froisland, DH, Arsand, E & Skarderud, F (2012) Improving diabetes care for young people with type 1 diabetes through visual learning on mobile phones: mixed-methods study. J Med Internet Res 14, e111.
23. Brown, B, Chetty, C, Grimes, A et al. (2006) Reflecting on health: a system for students to monitor diet and exercise. In CHI ’06 Extended Abstracts on Human Factors in Computing Systems, Montréal, Québec, Canada, 22–27 April 2006, pp. 18071812. New York: Association for Computing Machinery.
24. Ehrmann, BJ, Anderson, RM, Piatt, GA et al. (2014) Digital photography as an educational food logging tool in obese patients with type 2 diabetes: lessons learned from a randomized, crossover pilot trial. Diabetes Educ 40, 8999.
25. Kikunaga, S, Tin, T, Ishibashi, G et al. (2007) The application of a handheld personal digital assistant with camera and mobile phone card (Wellnavi) to the general population in a dietary survey. J Nutr Sci Vitaminol (Tokyo) 53, 109116.
26. Wang, D-H, Kogashiwa, M & Kira, S (2006) Development of a new instrument for evaluating individuals’ dietary intakes. J Am Diet Assoc 106, 15881593.
27. Carter, MC, Burley, VJ, Nykjaer, BC et al. (2013) ‘My Meal Mate’ (MMM): validation of the diet measures captured on a smartphone application to facilitate weight loss. Br J Nutr 109, 539546.
28. Tsai, CC, Lee, G, Raab, F et al. (2007) Usability and feasibility of PmEB: a mobile phone application for monitoring real time caloric balance. Mobile Netw Applic 12, 173184.
29. Mattila, E, Parkka, J, Hermersdorf, M et al. (2008) Mobile diary for wellness management – results on usage and usability in two user studies. IEEE Trans Inf Technol Biomed 12, 501512.
30. Flegal, KM, Carroll, MD, Kit, BK et al. (2012) Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010. JAMA 307, 491497.
31. Narayan, KM, Boyle, JP, Thompson, TJ et al. (2003) Lifetime risk for diabetes mellitus in the United States. JAMA 290, 18841890.
32. Shai, I, Jiang, R, Manson, JE et al. (2006) Ethnicity, obesity, and risk of type 2 diabetes in women: a 20-year follow-up study. Diabetes Care 29, 15851590.
33. Arab, L, Tseng, CH, Ang, A et al. (2011) Validity of a multipass, web-based, 24-hour self-administered recall for assessment of total energy intake in blacks and whites. Am J Epidemiol 174, 12561265.
34. Broderick, JE, Schwartz, JE, Shiffman, S et al. (2003) Signaling does not adequately improve diary compliance. Ann Behav Med 26, 139148.
35. Comulada, WS, Lightfoot, M, Swendeman, D et al. (2015) Compliance to cell phone-based EMA among Latino youth in outpatient treatment. J Ethn Subst Abuse 14, 232250.
36. Courvoisier, DS, Eid, M & Lischetzke, T (2012) Compliance to a cell phone-based ecological momentary assessment study: the effect of time and personality characteristics. Psychol Assess 24, 713720.
37. Fitzpatrick, SL, Jeffery, R, Johnson, KC et al. (2014) Baseline predictors of missed visits in the Look AHEAD study. Obesity (Silver Spring) 22, 131140.
38. Hongu, N, Pope, BT, Bilgic, P et al. (2015) Usability of a smartphone food picture app for assisting 24-hour dietary recall: a pilot study. Nutr Res Pract 9, 207212.
39. Freedman, MJ, Lester, KM, McNamara, C et al. (2006) Cell phones for ecological momentary assessment with cocaine-addicted homeless patients in treatment. J Subst Abuse Treat 30, 105111.
40. Kauer, SD, Reid, SC, Sanci, L et al. (2009) Investigating the utility of mobile phones for collecting data about adolescent alcohol use and related mood, stress and coping behaviours: lessons and recommendations. Drug Alcohol Rev 28, 2530.
41. Comulada, WS (2014) Mobile phone assessment in egocentric networks: a pilot study on gay men and their peers. Connect 34, 4351.
42. Swendeman, D, Comulada, WS, Ramanathan, N et al. (2015) Reliability and validity of daily self-monitoring by smartphone application for health-related quality-of-life, antiretroviral adherence, substance use, and sexual behaviors among people living with HIV. AIDS Behav 19, 330340.
43. Reddy, S, Shilton, K, Burke, J et al. (2008) Evaluating participation and performance in participatory sensing. Presented at International Workshop on Urban, Community, and Social Applications of Networked Sensing Systems (UrbanSense08), Raleigh, North Carolina, USA, 4 November 2008.
44. Ramanathan, N, Swendeman, D, Comulada, WS et al. (2013) Identifying preferences for mobile health applications for self-monitoring and self-management: focus group findings from HIV-positive persons and young mothers. Int J Med Inform 82, e38e46.
45. National Heart, Lung, and Blood Institute (2017) Calculate Your Body Mass Index. https://www.nhlbi.nih.gov/health/educational/lose_wt/BMI/bmicalc.htm (accessed June 2017).
46. Kyle, UG, Bosaeus, I, De Lorenzo, AD et al. (2004) Bioelectrical impedance analysis – part I: review of principles and methods. Clin Nutr 23, 12261243.
47. Kyle, UG, Bosaeus, I, De Lorenzo, AD et al. (2004) Bioelectrical impedance analysis – part II: utilization in clinical practice. Clin Nutr 23, 14301453.
48. Parker, ED, Schmitz, KH, Jacobs, DR Jr. et al. (2007) Physical activity in young adults and incident hypertension over 15 years of follow-up: the CARDIA study. Am J Public Health 97, 703709.
49. Copeland, WE, Shanahan, L, Worthman, CM et al. (2011) Cumulative depression exposure predicts later C-reactive protein levels: a prospective analysis. Biol Psychiatry 42, 26412650.
50. Yeh, ET & Willerson, JT (2003) Coming of age of C-reactive protein: using inflammation markers in cardiology. Circulation 107, 370371.
51. Ansar, W & Ghosh, S (2013) C-reactive protein and the biology of disease. Immunol Res 56, 131142.
52. McDade, TW, Stallings, JF, Angold, A et al. (2000) Epstein-Barr virus antibodies in whole blood spots: a minimally invasive method for assessing an aspect of cell-mediated immunity. Psychosom Med 62, 560567.
53. Herbert, TB & Cohen, S. (1993) Stress and immunity in humans: a meta-analytic review. Psychosom Med 55, 364379.
54. Borders, AEB, Grobman, WA, Amsden, LB et al. (2010) The relationship between self-report and biomarkers of stress in low-income reproductive-age women. Am J Obstet Gynecol 203, 577, e1e8.
55. Graham, JW & Shevock, AE (2012) Planned missing data design 2: two-method measurement. In Missing Data: Analysis and Design, Statistics for Social and Behavioral Sciences , pp. 295322 [JW Graham, editor]. New York: Springer Science and Business.
56. Zawadzki, MJ, Graham, JW & Gerin, W (2012) Increasing the validity and efficiency of blood pressure estimates using ambulatory and clinic measurements and modern missing data methods. Am J Hypertens 25, 764769.
57. Graham, JW, Taylor, BJ, Olchowski, AE et al. (2006) Planned missing data designs in psychological research. Psychol Methods 11, 323343.
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