Mining health app data to find more and less successful weight loss subgroups

Journal of Medical Internet Research

Volumn 18, Issue 6, 2016, Pages

  Serrano, Katrina J ^a   Yu, Mandi ^a   Coa, Kisha I ^b   Collins, Linda M ^c   Atienza, Audie A ^b  

^a NATIONAL CANCER INSTITUTE   (United States)

^b ICF INTERNATIONAL   (United States)

^c PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Classification; Data mining; Mobile app; Mobile health; Weight loss

Indexed keywords

ADOLESCENT; ADULT; AGED; BODY WEIGHT; CROSS-SECTIONAL STUDY; DATA MINING; DIET; EXERCISE; FEMALE; HUMAN; INFORMATION PROCESSING; MALE; MIDDLE AGED; MOBILE APPLICATION; MOBILE PHONE; PHYSIOLOGY; PROCEDURES; RANDOMIZATION; STATISTICS AND NUMERICAL DATA; WEIGHT REDUCTION; YOUNG ADULT;

ADOLESCENT; ADULT; AGED; BODY WEIGHT; CELL PHONES; CROSS-SECTIONAL STUDIES; DATA MINING; DATASETS AS TOPIC; DIET; EXERCISE; FEMALE; HUMANS; MALE; MIDDLE AGED; MOBILE APPLICATIONS; RANDOM ALLOCATION; WEIGHT LOSS; YOUNG ADULT;

EID: 84977527075     PISSN: None     EISSN: 14388871     Source Type: Journal    
DOI: 10.2196/jmir.5473     Document Type: Article

References (40)

1. Anderson M. Pew Research Center. 2015. Technology Device Ownership: 2015 URL: http://www.pewinternet.org/2015/10/29/technology-device-ownership-2015/[accessed 2016-04-03] [WebCite Cache ID 6gVHeTuP7]
2. Fox S, Duggan M. Pew Research Center. Mobile Health 2012 URL: http://www.pewinternet.org/2012/11/08/mobile-health-2012/[accessed 2015-12-21] [WebCite Cache ID 6dwglz4aG]
3. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA 2014 Feb 26;311(8):806-814. [doi: 10.1001/jama.2014.732] [Medline: 24570244]
4. 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;15(4):e32 [FREE Full text] [doi: 10.2196/jmir.2283] [Medline: 23587561]
5. Stephens J, Allen J. Mobile phone interventions to increase physical activity and reduce weight: a systematic review. J Cardiovasc Nurs 2013;28(4):320-329 [FREE Full text] [doi: 10.1097/JCN.0b013e318250a3e7] [Medline: 22635061]
6. Stephens J, Allen JK, Dennison Himmelfarb Cheryl R. "Smart" coaching to promote physical activity, diet change, and cardiovascular health. J Cardiovasc Nurs 2011;26(4):282-284 [FREE Full text] [doi: 10.1097/JCN.0b013e31821ddd76] [Medline: 21666418]
7. Pagoto S, Schneider K, Jojic M, DeBiasse M, Mann D. Evidence-based strategies in weight-loss mobile apps. Am J Prev Med 2013 Nov;45(5):576-582. [doi: 10.1016/j.amepre.2013.04.025] [Medline: 24139770]
8. Hammond RA, Levine R. The economic impact of obesity in the United States. Diabetes Metab Syndr Obes 2010;3:285-295 [FREE Full text] [doi: 10.2147/DMSOTT.S7384] [Medline: 21437097]
9. Wang YC, McPherson K, Marsh T, Gortmaker SL, Brown M. Health and economic burden of the projected obesity trends in the USA and the UK. The Lancet 2011 Aug;378(9793):815-825. [doi: 10.1016/S0140-6736(11)60814-3]
10. Withrow D, Alter D. The economic burden of obesity worldwide: a systematic review of the direct costs of obesity. Obes Rev 2011 Feb;12(2):131-141. [doi: 10.1111/j.1467-789X.2009.00712.x] [Medline: 20122135]
11. Behrens J. Principles and procedures of exploratory data analysis. Psychological Methods 1997;2(2):131-160. [doi: 10.1037/1082-989X.2.2.131]
12. Greenhouse J. Exploratory statistical methods, with applications to psychiatric research. Psychoneuroendocrinology 1992 Oct;17(5):423-441. [doi: 10.1016/0306-4530(92)90001-N]
13. Tukey J. Exploratory Data Analysis. Reading, MA: Addison-Wesley; 1977.
14. Raubertas RF, Rodewald LE, Humiston SG, Szilagyi PG. ROC curves for classification trees. Med Decis Making 1994;14(2):169-174. [Medline: 8028469]
15. Bradley A. The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition 1997 Jul;30(7):1145-1159. [doi: 10.1016/S0031-3203(96)00142-2]
16. Centers for Disease Control and Prevention. Losing Weight URL: http://www.cdc.gov/healthyweight/losing-weight/[accessed 2015-12-21] [WebCite Cache ID 6dwgtMghx]
17. Mertens I, Van Gaal L F. Overweight, obesity, and blood pressure: the effects of modest weight reduction. Obes Res 2000 May;8(3):270-278 [FREE Full text] [doi: 10.1038/oby.2000.32] [Medline: 10832771]
18. Look AHEAD Research Group, Wing RR. Long-term effects of a lifestyle intervention on weight and cardiovascular risk factors in individuals with type 2 diabetes mellitus: four-year results of the Look AHEAD trial. Arch Intern Med 2010 Sep 27;170(17):1566-1575 [FREE Full text] [doi: 10.1001/archinternmed.2010.334] [Medline: 20876408]
19. Lemon S, Roy J, Clark M, Friedmann P, Rakowski W. Classification and regression tree analysis in public health: methodological review and comparison with logistic regression. Ann Behav Med 2003 Dec;26(3):172-181. [Medline: 14644693]
20. McArdle J. Exploratory data mining using CART in the behavioral sciences. In: Cooper H, Camic P, Long D, Panter A, Rindskopf D, Sher K, editors. APA Handbook of Research Methods in Psychology. Washington, DC: American Psychological Association; 2012:405-421.
21. Atienza AA, Yaroch AL, Mãsse LC, Moser RP, Hesse BW, King AC. Identifying sedentary subgroups: the National Cancer Institute's Health Information National Trends Survey. Am J Prev Med 2006 Nov;31(5):383-390 [FREE Full text] [doi: 10.1016/j.amepre.2006.07.024] [Medline: 17046409]
22. Dunton GF, Atienza AA, Tscherne J, Rodriguez D. Identifying combinations of risk and protective factors predicting physical activity change in high school students. Pediatr Exerc Sci 2011 Feb;23(1):106-121. [Medline: 21467595]
23. King A, Goldberg J, Salmon J, Owen N, Dunstan D, Weber D, et al. Identifying subgroups of U.S. adults at risk for prolonged television viewing to inform program development. Am J Prev Med 2010 Jan;38(1):17-26. [doi: 10.1016/j.amepre.2009.08.032] [Medline: 20117553]
24. Loh W. Classification and regression trees. WIREs Data Mining Knowl Discov 2011 Jan 06;1(1):14-23. [doi: 10.1002/widm.8]
25. Breiman L. Classification and regression trees. New York: Chapman & Hall; 1984.
26. Kraemer H. Evaluating medical tests: objective and quantitative guidelines. Newbury Park, CA: Sage Publications; 1992.
27. Lewis R. An Introduction to Classification and Regression Tree (CART) Analysis. 2000 Presented at: Annual Meeting of the Society for Academic Emergency Medicine; 2000; San Francisco, CA URL: http://www.researchgate.net/publication/240719582 [WebCite Cache ID 6i4Dbhm5H]
28. Therneau T, Atkinson E. Mayo Foundation. 2015 Jun. An Introduction to Recursive Partitioning Using the RPART Routines URL: https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf [WebCite Cache ID 6dwgz2E6v]
29. Robin X, Turck N, Hainard A, Tiberti N, Lisacek F. R-project. Package 'pROC' URL: https://cran.r-project.org/web/packages/pROC/pROC.pdf [accessed 2015-12-21] [WebCite Cache ID 6dwh187PZ]
30. Wharton C, Johnston C, Cunningham B, Sterner D. Dietary self-monitoring, but not dietary quality, improves with use of smartphone app technology in an 8-week weight loss trial. J Nutr Educ Behav 2014;46(5):440-444. [doi: 10.1016/j.jneb.2014.04.291] [Medline: 25220777]
31. Burke L, Conroy M, Sereika S, Elci O, Styn M, Acharya S, et al. 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 [FREE Full text] [doi: 10.1038/oby.2010.208] [Medline: 20847736]
32. Burke L, Wang J, Sevick M. Self-monitoring in weight loss: a systematic review of the literature. J Am Diet Assoc 2011 Jan;111(1):92-102 [FREE Full text] [doi: 10.1016/j.jada.2010.10.008] [Medline: 21185970]
33. Linde J, Jeffery R, French S, Pronk N, Boyle R. Self-weighing in weight gain prevention and weight loss trials. Ann Behav Med 2005 Dec;30(3):210-216. [doi: 10.1207/s15324796abm3003-5] [Medline: 16336072]
34. Wing RR, Tate DF, Gorin AA, Raynor HA, Fava JL. A self-regulation program for maintenance of weight loss. N Engl J Med 2006 Oct 12;355(15):1563-1571. [doi: 10.1056/NEJMoa061883] [Medline: 17035649]
35. Ballantine P, Stephenson R. Help me, I'm fat! Social support in online weight loss networks. J. Consumer Behav 2011 Dec 23;10(6):332-337. [doi: 10.1002/cb.374]
36. Li V, McDonald D, Eikey E, Sweeney J, Escajeda J, Dubey G. Losing It Online: Characterizing Participation in an Online Weight Loss Community. USA; 2014 Presented at: GROUP '14 Proceedings of the 18th International ACM Conference on Supporting Group Work; 2014; Sanibel, FL p. 35-45. [doi: 10.1145/2660398.2660416]
37. Hwang KO, Farheen K, Johnson CW, Thomas EJ, Barnes AS, Bernstam EV. Quality of weight loss advice on internet forums. Am J Med 2007 Jul;120(7):604-609 [FREE Full text] [doi: 10.1016/j.amjmed.2007.04.017] [Medline: 17602934]
38. Hwang KO, Ning J, Trickey AW, Sciamanna CN. Website usage and weight loss in a free commercial online weight loss program: retrospective cohort study. J Med Internet Res 2013;15(1):e11 [FREE Full text] [doi: 10.2196/jmir.2195] [Medline: 23322819]
39. Neve M, Morgan PJ, Jones PR, Collins CE. Effectiveness of web-based interventions in achieving weight loss and weight loss maintenance in overweight and obese adults: a systematic review with meta-analysis. Obes Rev 2010 Apr;11(4):306-321. [doi: 10.1111/j.1467-789X.2009.00646.x] [Medline: 19754633]
40. Weinstein PK. A review of weight loss programs delivered via the Internet. J Cardiovasc Nurs 2006;21(4):251-8; quiz 259. [Medline: 16823276]