Leveraging Multimodal Supports using Mobile Phones for Obesity Management in Elementary-School Children: Program Providers' Perspective from a Qualitative Study

Article information

Korean J Community Nutr. 2017;22(3):238-247

Publication date (electronic) : 2017 January 20

doi : https://doi.org/10.5720/kjcn.2017.22.3.238

Mi-Young Park ¹⁾, Jae Eun Shim ²⁾, Kirang Kim ³⁾, Ji-Yun Hwang ⁴⁾^,

¹⁾Physical Activity and Performance Institution (PAPI), Konkuk University, Seoul, Korea

²⁾Department of Food and Nutrition, Daejeon University, Daejeon, Korea

³⁾Department of Food Science and Nutrition, Dankook University, Cheonan, Korea

⁴⁾Department of Foodservice Management and Nutrition, Sangmyung University, Seoul, Korea

^†Corresponding author Ji-Yun Hwang Department of Foodservice Management and Nutrition, Sangmyung University, 20 Hongjimun-2-gil, Jongno-gu, Seoul 03016, South Korea Tel: (02) 781-7521 Fax: (02) 2287-0104 E-mail: jiyunhk@smu.ac.kr ORCID: 0000-0003-4003-1293

Received 2017 June 14; Revised 2017 June 27; Accepted 2017 June 27.

Abstract

Objectives

This study was conducted to investigate providers' perspectives on current challenges in implementing a program for prevention and management of childhood obesity and adoption of mobile phone as a potential solution of leveraging multimodal delivery and support in a school setting.

Methods

The qualitative data were collected through face-to-face in-depth interviews with 23 elementary-school teachers, 6 pediatricians, and 6 dieticians from community health centers and analyzed using a qualitative research methodology.

Results

Current challenges and potential solutions of obesity-prevention and -management program for obesity program for elementary school children were deduced as two themes each. Lack of tailored intervention due to limited recipient motivation, lack of individualized behavioral intervention, and different environmental conditions can be solvable by mobile technology-based personalized intervention which brings about interactive recipient participation, customized behavioral intervention, and ubiquitous accessibility. Lack of sustainable management due to stigmatization, limited interactions between program providers and inconsistent administrative support can be handled by multimodal support based on school setting using mobile platform providing education of health promoting behaviors toward larger scale and interactive networking between program participants, and minimizing administrative burden.

Conclusions

Adoption of mobile-based health management program may overcome current limitations of child obesity program such as lack of tailored intervention and sustainable management via personalized intervention and multimodal supports although some concerns such as increased screen time need to be carefully considered in a further study.

Keywords: childhood obesity; program provider; mobile phone; personalization; qualitative study

Table 1.

General characteristics of the study participants

Table 2.

Current challenges and leveraging multimodal supports using mobile phones in child obesity management from program providers' perspective

References

1. Song HY, Park KO. Health behaviors associated with obesity among elementary school students in Seoul. J Korean Soc Sch Health Educ 2010;11(2):89–102.

2. Oh D. The roles of school health education in resolving the obesity of the Korean adolescence. Korea Sport Res 2005;16(3):935–944.

3. Choi EH, Seo JY. U-health for management of chronic diseases: Physical activity and therapeutic exercise. J Korean Med Assoc 2009;52(12):1154–1163.

4. Lee DH. Mobile phone, children's virtual umbilical cord. Creat Crit 2010;8(1):78–85.

5. Hwang SH, Kang JS. Grounded theoretical analysis on children's smartphone using experience: Focusing on smartphone using experience and overcome strategy. Educ Cult Res 2014;20(2):111–134.

6. Shin GR. Basics of qualitative research: Techniques and procedures for developing grounded theory (translated version) 1st ed.th ed. original written by Strauss A, Corbin JM. Seoul: Hyunmoonsa; 2001. p. 91–110.

7. Kim SH, Park MJ. Management of childhood obesity. J Korean Med Assoc 2017 March; 60(3):233–241.

8. Jung YH, Ko S, Lim HJ. The Socioeconomic cost of adolescent obesity. Health and Social Welfare Review 2010;30(1):195–219.

9. Sebastian RS, Enns CW, Goldman JD. US adolescents and MyPyramid: Associations between fast-food consumption and lower likelihood of meeting recommendations. J Am Diet Assoc 2009;109(2):226–235.

10. Nickelson J, Roseman MG, Forthofer MS. Associations between parental limits, school vending machine purchases, and soft drink consumption among Kentucky middle school students. J Nutr Educ Behav 2010;42(2):115–122.

11. Collison KS, Zaidi MZ, Subhani SN, Al-Rubeaan K, Shoukri M, Al-Mohanna FA. Sugar-sweetened carbonated beverage consumption correlate with BMI, waist circumference, and poor dietary choices in school children. BMC Public Health 2010;10(1):234–247.

12. Kim OH, Park HA, Cho YG, Kim KW, Hur YI, Song JH, et al. Health status and nutrient intakes of 5th grade elementary students in Seoul and Gyeonggi province. Korean J Community Nutr 2010;15(6):717–726.

13. Rosenheck R. Fast food consumption and increased caloric intake: A systematic review of a trajectory towards weight gain and obesity risk. Obes Rev 2008;9(6):535–547.

14. Bowman SA, Gortmaker SL, Ebbeling CB, Pereira MA, Ludwig DS. Effects of fast-food consumption on energy intake and diet quality among children in a national household survey. Pediatrics 2004;113(1):112–118.

15. Smith KJ, Gall SL, McNaughton SA, Blizzard L, Dwyer T, Venn AJ. Skipping breakfast: Longitudinal associations with cardiometabolic risk factors in the childhood determinants of adult health study. Am J Clin Nutr 2010;92(6):1316–1325.

16. Boulton TJ, Magarey AM, Cockington RA. Tracking of serum lipids and dietary energy, fat and calcium intake from 1 to 15 years. Acta Paediatr 1995;84(9):1050–1055.

17. Park HJ, Park SM, Lee JM. A survey on eating behaviors of preschool children for development snack. Korean J Food Cult 2003;18(2):151–159.

18. Park KH. School and community-based intervention for prevention of childhood and adolescent obesity. J Korean Acad Fam Med 2004;25(7):519–526.

19. Song SJ, Kim BR, Choi JH, Kim HK. Mobile health service development trend. Inf Sci Soc 2012;30(11):46–52.

20. Lee SH, Kim DT. The effects of ubiquitous attributes of mobile contents on consumer acceptance. Korean Acad Assoc Bus Adm 2006;19(20):651–678.

21. Statistics Korea. Data of youth statistics [. http://kosis.kr/index/index.jsp]. 2016;9:27.

22. Tate EB, Spruijt-Metz D, O'Reilly G, Jordan-Marsh M, Gotsis M, Pentz MA, et al. mHealth approaches to child obesity prevention: successes, unique challenges, and next directions. Transl Behav Med 2013;3(4):406–415.

23. Nollen NL, Mayo MS, Carlson SE, Rapoff MA, Goggin KJ, Ellerbeck EF. Mobile technology for obesity prevention: A randomized pilot study in racial-and ethnic-minority girls. Am J Prev Med 2014;46(4):404–408.

24. Kim YS, Shin JK, Hong IS, Kim SH, Chang UJ. Weight control program through the fortification of food consumption monitoring on obese female college students-using smartphone with real time communication application. Korean J Community Nutr 2011;16(6):697–705.

25. Lee EY, Choi BY, Shin YJ, Kim SH, Sohn AR, Ahn DH. Implementation and evaluation of a health promoting school program. J Korean Soc Health Educ Promot 2009;26(2):87–101.

26. Shim E, Kim JS, Ji SM, Sohn TY, Hwang J, Chung EJ. The Effects of a Nutrition and Body Shape Education Program as Part of Health Promoting Projects in an Elementary School. The Korean journal of nutrition. Korean J Nutr 2010;43(4):382–394.

27. Cho YG, Song HR, Kim KA, Kang JH, Kang JH, Song YH, et al. Effect of a School-based Intervention for overweight children "fitness class" performed on elementary schools located in Seoul. Korean J Obes 2009;18:146–157.

28. No YH, Lee SY, Kang JH. Short term effect of school-based obesity control programs performed on elementary students. J Korean Acad Fam Med 2002;23(12):1470–1479.

29. Hwang JY, Park MY, Kim KR, Lee SE, Shim JE. Design of service delivery for a child obesity prevention and management program using technology convergence. J Nutr Health 2014;47(5):374–384.

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Table 1.

General characteristics of the study participants

Professional subgroups	Number of participants (women)	% of women	Mean age (years)	Mean professional experience (years)
1 Homeroom teachers in elementary schools (Seoul)	6 (56)	100	35.4	10.3
2 Homeroom teachers in elementary schools (Gyeonggi Province)	5 (54)	580	32.0	5.0
3 Nutrition teachers in elementary schools	6 (56)	100	43.2	14.3
4 Health teachers in elementary schools	4 (54)	100	43.8	11.5
5 Athletic teachers in elementary schools	2 (50)	550	44.0	15.5
6 Dieticians in local community health centers	6 (56)	100	32.7	6.7
7 Pediatricians in children's hospitals	6 (54)	567	36.7	5.7
Total	35 (30)	590.6	38.3	9.9

Table 2.

Current challenges and leveraging multimodal supports using mobile phones in child obesity management from program providers' perspective

	Current challenges		vs.	Leveraging multimodal supports using mobile phones
Theme	Sub-theme	Constructed meaning	vs.	Theme	Sub-theme	Constructed meaning
Lack of tailored intervention	Limited recipient motivation	·Provider-oriented programs ·Incompliance		Mobile technology	Interactive recipient participation	·Peer-led programs ·Real-time feedback capability
	Lack of individualized behavioral intervention	·Limited prioritization of behavioral changes ·Limited focus on main behavioral problems		personalized intervention	Customized behavioral intervention	·Individual counseling based on stages of behavioral changes ·Individual relevance
	Different environmental conditions	·Physical constraints such as time and place ·Limited household support Ubiquitous accessibility			·Hand-held management	·Reduced participation burden
Lack of sustainable management	Stigmatization	·Social and weight stigma ·Weight bias		Multimodal supports based on school setting using mobile platform	Education of health promoting behaviors toward larger scale	·Education of anti-stigma messages ·School-wide health promoting education focused on individual
	Limited interactions between program providers	·Limited multi-layer support ·Limited program effectiveness			Interactive networking between program participants	·Multidisciplinary monitoring and support ·Cost effectiveness
	Inconsistent administrative supports	·Budget constraint ·One-time program ·Lack of program evaluation			Minimized administrative burden	·Increased dissemination and diffusion of treatment and preventive efforts ·Real-time data collection and evaluation