Weight Loss Associated With Different Patterns of Self-Monitoring Using the Mobile Phone App My Meal Mate

Michelle C Carter, Victoria J Burley, Janet E Cade, Michelle C Carter, Victoria J Burley, Janet E Cade

Abstract

Background: Obesity is a major global public health issue due to its association with a number of serious chronic illnesses and its high economic burden to health care providers. Self-monitoring of diet has been consistently linked to weight loss. However, there is limited evidence about how frequently individuals need to monitor their diet for optimal weight loss.

Objective: The aim of this paper is to describe app usage frequency and pattern in the mobile phone arm of a previously conducted randomized controlled trial. The relationship between frequency and pattern of electronic dietary self-monitoring and weight loss is also investigated.

Methods: A randomized pilot trial comparing three methods of self-monitoring (mobile phone app, paper diary, Web-based) was previously conducted. Trial duration was 6 months. The mobile phone app My Meal Mate features an electronic food diary and encourages users to self-monitor their dietary intake. All food consumption data were automatically uploaded with a time and date stamp. Post hoc regression analysis of app usage patterns was undertaken in the My Meal Mate group (n=43; female: 77%, 33/43; white: 100%, 43/43; age: mean 41, SD 9 years; body mass index: mean 34, SD 4 kg/m2) to explore the relationship between frequency and pattern of electronic dietary self-monitoring and weight loss. Baseline characteristics of participants were also investigated to identify any potential predictors of dietary self-monitoring.

Results: Regression analysis showed that those in the highest frequency-of-use category (recorded ≥129 days on the mobile phone app) had a -6.4 kg (95% CI -10.0 to -2.9) lower follow-up weight (adjusted for baseline weight) than those in the lowest frequency-of-use category (recorded ≤42 days; P<.001). Long-term intermittent monitoring over 6 months appeared to facilitate greater mean weight loss than other patterns of electronic self-monitoring (ie, monitoring over the short or moderate term and stopping and consistently monitoring over consecutive days). Participant characteristics such as age, baseline weight, sex, ethnicity, conscientiousness, and consideration of future consequences were not statistically associated with extent of self-monitoring.

Conclusions: The results of this post hoc exploratory analysis indicate that duration and frequency of app use is associated with improved weight loss, but further research is required to identify whether there are participant characteristics that would reliably predict those who are most likely to regularly self-monitor their diet.

Clinicaltrial: ClinicalTrials.gov NCT01744535; https://ichgcp.net/clinical-trials-registry/NCT01744535 (Archived by WebCite at http://www.webcitation.org/6FEtc3PVB).

Keywords: mobile phone; obesity; self-monitoring; weight loss.

Conflict of interest statement

Conflicts of Interest: The University of Leeds is establishing a spin-out company called Dietary Assessment Limited and JC is a director of the company.

©Michelle C Carter, Victoria J Burley, Janet E Cade. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 02.02.2017.

Figures

Figure 1
Figure 1
Distribution of days of dietary recording on My Meal Mate for each participant (n=43) over the course of the 6-month My Meal Mate pilot trial. The x-axis is the My Meal Mate ID number that was automatically assigned to the participant and the y-axis is dietary self-monitoring in days. Each green shaded box is a day with ≥500 and ≤5000 kcal energy recorded on My Meal Mate.

References

    1. World Health Organization. 2013. [2016-12-20]. Obesity and overweight
    1. Foresight . Tackling Obesities: Future Choices-Project Report (2nd edition) London: Department of Innovation Universities and Skills; 2007. Oct, [2017-01-12]. .
    1. Wing RP. Behavioural treatment of obesity: strategies to improve outcome and predictors of success. In: Eckel RH, editor. Obesity: Mechanisms and Clinical Management. Philadelphia, PA: Lippincott Williams & Wilkins; 2003. p. 227.
    1. Wadden TA, Butryn ML, Wilson C. Lifestyle modification for the management of obesity. Gastroenterology. 2007 May;132(6):2226–2238. doi: 10.1053/j.gastro.2007.03.051.
    1. Burke L, Wang J, Sevick Ma. Self-monitoring in weight loss: a systematic review of the literature. J Am Diet Assoc. 2011 Jan;111(1):92–102. doi: 10.1016/j.jada.2010.10.008.
    1. Febrero GA, Clum GA. Self regulation theories and self-help therapies. In: Watkins PA, Clum GA, editors. Handbook of Self-Help Therapies. New York: Routledge; 2008. p. 59.
    1. Baker R, Kirschenbaum Ds. Self-monitoring may be necessary for successful weight control. Behav Ther. 1993 Apr 15;24(3):377–394. doi: 10.1016/S0005-7894(05)80212-6.
    1. Boutelle KN, Kirschenbaum DS. Further support for consistent self-monitoring as a vital component of successful weight control. Obes Res. 1998 May;6(3):219–224.
    1. Burnett K, Taylor CB, Agras WS. Ambulatory computer-assisted therapy for obesity: a new frontier for behavior therapy. J Consult Clin Psychol. 1985 Oct;53(5):698–703.
    1. Agras W, Taylor CB, Feldman DE, Losch M, Burnett KF. Developing computer-assisted therapy for the treatment of obesity. Behav Ther. 1990 Dec;21(1):99–109. doi: 10.1016/S0005-7894(05)80191-1.
    1. Taylor CB. Improving the effectiveness of computer-assisted weight loss. Behav Ther. 1991;22(2):229–236. doi: 10.1016/S0005-7894(05)80178-9.
    1. Yon BA. The use of a personal digital assistant for dietary self-monitoring does not improve the validity of self-reports of energy intake. J Am Diet Assoc. 2007;106(8):1256–1259. doi: 10.1016/j.jada.2006.05.004.
    1. Burke LE. SMART trial: a randomized clinical trial of self-monitoring in behavioral weight management-design and baseline findings. Contemp Clin Trials. 2009;30(6):1–51. doi: 10.1016/j.cct.2009.07.003.
    1. Wang D, Kogashiwa M, Kira S. Development of a new instrument for evaluating individuals' dietary intakes. J Am Diet Assoc. 2006 Oct;106(10):1588–1593. doi: 10.1016/j.jada.2006.07.004.
    1. Kikunaga S, Tin T, Ishibashi G, Wang D, Kira S. 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) 2007 Apr;53(2):109–116.
    1. Six BL, Schap TE, Zhu FM, Mariappan A, Bosch M, Delp EJ, Ebert DS, Kerr DA, Boushey CJ. Evidence-based development of a mobile telephone food record. J Am Diet Assoc. 2010 Jan;110(1):74–79. doi: 10.1016/j.jada.2009.10.010.
    1. Burke LE, Styn MA, Sereika SM, Conroy MB, Ye L, Glanz K, Sevick MA, Ewing LJ. Using mHealth technology to enhance self-monitoring for weight loss: a randomized trial. Am J Prev Med. 2012 Jul;43(1):20–26. doi: 10.1016/j.amepre.2012.03.016.
    1. Carter MC, Burley VJ, Nykjaer C, Cade JE. Adherence to a smartphone application for weight loss compared to website and paper diary: pilot randomized controlled trial. J Med Internet Res. 2013 Apr;15(4):e32. doi: 10.2196/jmir.2283.
    1. Carter M, Burley VJ, Cade JE. Development of ‘My Meal Mate’ - a smartphone intervention for weight loss. Nutr Bull. 2013 Feb 07;38(1):80–84. doi: 10.1111/nbu.12016.
    1. Weight Loss Resources. [2017-01-12]. .
    1. Terracciano A, Sutin AR, McCrae RR, Deiana B, Ferrucci L, Schlessinger D, Uda M, Costa PT. Facets of personality linked to underweight and overweight. Psychosom Med. 2009 Jul;71(6):682–689. doi: 10.1097/PSY.0b013e3181a2925b.
    1. Goldberg L, Johnson JA, Eber HW, Hogan R, Ashton MC, Cloninger CR, Gough HG. The international personality item pool and the future of public-domain personality measures. J Res Pers. 2006 Feb;40(1):84–96. doi: 10.1016/j.jrp.2005.08.007.
    1. International Personality Item Pool. [2017-01-12]. A scientific collaboratory for the development of advanced measures of personality traits and other individual differences
    1. McCrae RR, John OP. An introduction to the five-factor model and its applications. J Pers. 1992 Jun;60(2):175–215.
    1. Bogg T, Roberts BW. Conscientiousness and health-related behaviors: a meta-analysis of the leading behavioral contributors to mortality. Psychol Bull. 2004 Nov;130(6):887–919. doi: 10.1037/0033-2909.130.6.887.
    1. Strathman A. The consideration of future consequences: weighing immediate and distant outcomes of behavior. J Pers Soc Psychol. 1994;66(4):742–752. doi: 10.1037/0022-3514.66.4.742.
    1. Wadden TA, Berkowitz RI, Womble LG, Sarwer DB, Phelan S, Cato RK, Hesson LA, Osei SY, Kaplan R, Stunkard AJ. Randomized trial of lifestyle modification and pharmacotherapy for obesity. N Engl J Med. 2005 Nov 17;353(20):2111–2120. doi: 10.1056/NEJMoa050156.
    1. Burnett K, Taylor C, Agras W. Ambulatory computer-assisted behavior therapy for obesity: An empirical model for examining behavioral correlates of treatment outcome. Comput Hum Behav. 1992 Jan;8(2-3):239–248. doi: 10.1016/0747-5632(92)90008-3.
    1. Burke L, Conroy MB, Sereika SM, Elci OU, Styn MA, Acharya SD, Sevick MA, Ewing LJ, Glanz K. The effect of electronic self-monitoring on weight loss and dietary intake: a randomized behavioral weight loss trial. Obesity (Silver Spring) 2011 Feb;19(2):338–344. doi: 10.1038/oby.2010.208. doi: 10.1038/oby.2010.208.
    1. Beasley J, Riley WT, Davis A, Singh J. Evaluation of a PDA-based dietary assessment and intervention program: a randomized controlled trial. J Am Coll Nutr. 2008 Apr;27(2):280–286.
    1. Turner-McGrievy G, Tate D. Tweets, apps, and pods: results of the 6-month mobile pounds off digitally (Mobile POD) randomized weight-loss intervention among adults. J Med Internet Res. 2011 Dec;13(4):e120. doi: 10.2196/jmir.1841.
    1. Konstantinidis EI, Billis AS, Mouzakidis CA, Zilidou VI, Antoniou PE, Bamidis PD. Design, implementation, and wide pilot deployment of FitForAll: an easy to use exergaming platform improving physical fitness and life quality of senior citizens. IEEE J Biomed Health Inform. 2016 Jan;20(1):189–200. doi: 10.1109/JBHI.2014.2378814.

Source: PubMed

Sponsorzy i współpracownicy

Warunki medyczne

Interwencje lekowe

3
Subskrybuj