The Relationship between Internet Use and Health Behaviors among Adolescents

Eun Gyeong Kim

doi:10.12799/jkachn.2015.26.1.52

Articles

Page Path: HOME > J Korean Acad Community Health Nurs > Volume 26(1); 2015 > Article

Original Article
The Relationship between Internet Use and Health Behaviors among Adolescents: Eun Gyeong Kim; Journal of Korean Academy of Community Health Nursing 2015;26(1):52-60.
DOI: https://doi.org/10.12799/jkachn.2015.26.1.52
Published online: March 31, 2015

Department of Nursing, Kunsan National University, Gunsan, Korea.

• Received: November 21, 2014 • Revised: March 14, 2015 • Accepted: March 24, 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

1,331 Views
4 Download
4 Crossref

Full Article

Download PDF

Abstract

Abstract

Purpose
The study was performed in order to identify the relationship between health behaviors and Internet use among adolescents.
Methods
The study used raw data from the Korean Youth Risk Behavior Web-Based Survey that was performed in 2012. Data of a total of 74,186 students were analyzed using SPSS/WIN 18. The data were analyzed using descriptive statistics, t-test, and Pearson's correlation.
Results
Internet use and health behaviors were significantly related to gender, depression, suicidal intent, parents' educational level, cohabitation with parents at home, school location, and grade. There was a significant association between Internet use and health behaviors in adolescents.
Conclusion
Health promotion and education programs need to consider factors found relevant in this study.
Key Words: Adolescent; Internet; Health behaviors

Table 1

Health Behaviors and Internet Use Characteristics (N=74,186)

Variables	Characteristics	Categories	n (%) or M±SD
Health behaviors	Smoking	Yes	8,362 (11.3)
	Smoking	No	65,824 (88.7)
	Drinking	Yes	14,323 (19.3)
	Drinking	No	59,863 (80.7)
	Weight control	Yes	65,687 (90.9)
	Weight control	No	6,542 (9.1)
	Regular exercise	Yes	26,251 (35.4)
	Regular exercise	No	47,935 (64.6)
	Eating breakfast	Yes	35,734 (48.2)
	Eating breakfast	No	38,452 (51.8)
	Sufficient sleep	Yes	22,952 (36.0)
	Sufficient sleep	No	40,734 (64.0)
Internet use	Time (minute)	Weekday	149.0±122.64
	Time (minute)	Weekend	209.7±142.37
	Service	Learning	10,787 (14.5)
		Information retrieval	9,025 (12.2)
		Messenger/chatting	6,989 (9.4)
		Game	23,451 (31.6)
		Movie download	3,052 (4.1)
		MP3/Music download	7,057 (9.5)
		Animation/Story download	4,268 (5.8)
		UCC	673 (0.9)
		Association/community	2,775 (3.7)
		E-mail	159 (0.2)
		On-line shopping	2,054 (2.8)
		Pornography retrieval	531 (0.7)
		Blog/mini homepage	3,216 (4.3)
		Others	152 (0.2)

Table 2

Health Behaviors and Internet Use by General Characteristics (N=74,186)

Variables	Categories	n (%)	Internet use time (minute)				Health Practice Index
			Weekday		Weekend		Health Practice Index
			M±SD	t (p)	M±SD	t (p)	M±SD	t (p)
Gender	Male	38,221 (51.5)	154.7±128.89	6.88 (<.001)	223.5±146.25	22.08 (<.001)	4.1±1.72	9.22 (<.001)
Gender	Female	35,965 (48.5)	142.1±120.98	6.88 (<.001)	180.1±135.51	22.08 (<.001)	3.9±1.68	9.22 (<.001)
Depression	Yes	22,745 (30.7)	163.0±141.20	-9.54 (<.001)	222.1±159.10	-9.54 (<.001)	3.5±1.82	39.17 (<.001)
Depression	No	51,441 (69.3)	144.4±118.79	-9.54 (<.001)	202.0±137.14	-9.54 (<.001)	4.3±1.59	39.17 (<.001)
Suicidal intent	Yes	13,635 (18.4)	169.6±154.38	-10.31 (<.001)	228.2±168.90	-9.76 (<.001)	3.3±1.82	36.25 (<.001)
Suicidal intent	No	60,551 (81.6)	145.6±118.69	-10.31 (<.001)	203.5±137.89	-9.76 (<.001)	4.2±1.63	36.25 (<.001)
Father's education (year)	≤12	32,212 (45.3)	144.3±121.47	-3.69 (<.001)	196.0±133,52	-9.51 (<.001)	4.3±1.59	10.17 (<.001)
Father's education (year)	>12	38,915 (54.7)	150.8±122.36	-3.69 (<.001)	214.2±146.26	-9.51 (<.001)	3.9±1.75	10.17 (<.001)
Mother's education (year)	≤12	25,507 (35.8)	144.4±123.15	-3.01 (.003)	194.9±134.23	-8.42 (<.001)	4.4±1.55	22.94 (<.001)
Mother's education (year)	>12	45,792 (64.2)	149.9±121.36	-3.01 (.003)	211.6±143.43	-8.42 (<.001)	3.9±1.74	22.94 (<.001)
Cohabitant	Both-parent	60,490 (87.7)	144.8±119.29	-7.31 (<.001)	201.4±136.96	-10.74 (<.001)	4.2±1.64	20.56 (<.001)
Cohabitant	Single-parent or none-parent	8,500 (12.3)	164.6±133.71	-7.31 (<.001)	233.2±155.93	-10.74 (<.001)	3.6±1.81	20.56 (<.001)
City scale	Big	33,568 (45.2)	149.1±124.46	-0.69 (.492)	202.6±139.03	-4.80 (<.001)	4.1±1.68	4.61 (<.001)
City scale	Middle or small	40,618 (54.8)	150.4±127.36	-0.69 (.492)	211.8±147.68	-4.80 (<.001)	4.0±1.72	4.61 (<.001)
School grade	Middle school	37,297 (50.3)	147.7±121.96	-3.00 (.003)	196.0±136.42	-14.89 (<.001)	4.8±1.28	79.98 (<.001)
School grade	High school or vocational high school	36,889 (49.7)	153.1±131.08	-3.00 (.003)	225.0±152.83	-14.89 (<.001)	3.0±1.72	79.98 (<.001)

Table 3

Internet Use Time by Health Behaviors (N=74,186)

Variables	Categories	Internet use time (minute)
		Weekday			Weekend
		M±SD	t	p	M±SD	t	p
Smoking	Yes	174.1±156.89	12.54	<.001	241.4±175.27	15.57	<.001
Smoking	No	144.7±117.95	12.54	<.001	201.2±136.09	15.57	<.001
Drinking	Yes	169.1±147.80	12.63	<.001	233.9±167.90	15.51	<.001
Drinking	No	143.3±117.08	12.63	<.001	199.4±134.42	15.51	<.001
Weight control	Yes	145.4±118.43	7.18	<.001	200.5±136.23	15.21	<.001
Weight control	No	166.2±139.65	7.18	<.001	248.1±161.29	15.21	<.001
Regular exercise	Yes	147.8±124.04	2.38	.017	203.0±136.60	5.31	<.001
Regular exercise	No	152.1±128.22	2.38	.017	213.2±151.94	5.31	<.001
Eating breakfast	Yes	141.5±119.80	12.06	<.001	196.2±134.92	16.10	<.001
Eating breakfast	No	163.7±134.75	12.06	<.001	228.1±156.61	16.10	<.001
Sufficient sleep	Yes	139.8±108.25	8.50	<.001	191.9±127.18	14.85	<.001
Sufficient sleep	No	154.9±129.80	8.50	<.001	220.9±149.90	14.85	<.001

Table 4

Correlation of Health Practice Index and Internet Use Time

Variables	Categories	HPI	Internet use time
Variables	Categories	HPI	Weekday	Weekend
HPI		1
Internet use time	Weekday	-.11^*	1
Internet use time	Weekend	-.15^*	.61^*	1

^*P<.01 by Pearson Correlation; HPI=Health practice index.

This study was supported by Kunsan National University fond in 2012.

1. Lee CY, Kim BI, Yang KH, Yoo JS, Jung US, Jung EN, et al. Epidemiology and health promotion. Paju: Soomoonsa; 2012. p. 484.
2. McGue M, Iacono WG, Krueger R. The association of early adolescent problem behavior and adult psychopathology: A multivariate behavioral genetic perspective. Behav Genet. 2006;36(4):591–602. Article PubMed PMC PDF
3. Park SU. Major health issues in Korea: The results of Korea National Health and Nutrition Examination Surveys (NHANES) and Korea youth risk behavior web-based survey. Paper presented at: Symposium for national health investment and chronic diseases control. Seoul: Korea Human Resource Development Institute for Health & Welfare; 2007. 03 29.
4. Kwak KJ. A review of researches of the impact of computer game and children's and adolescent's development. Korean J Psychol Soc Issues. 2004;10:147–175.
5. Pronk NP, Anderson LH, Crain AL, Martinson BC, O'Connor PJ, Sherwood NE, et al. Meeting recommendations for multiple healthy lifestyle factors. Prevalence, clustering, and predictors among adolescents, adult, and senior health plan members. Am J Prev Med. 2004;27(2):25–33.PubMed
6. Han YR. A survey of the health risk behaviors of middle school students in Kyungju. J Korean Community Nurs. 2001;12(2):468–481.
7. Kim C. A study on teenagers' internet addiction and influencing factors. J Korean Acad Community Health Nurs. 2009;20(3):316–326.
8. Ko YK, Yoo IY, Kang KH, Lim JY, Kim MJ, Yoo HJ. Factors related to high-risk health behavior in middle school adolescents. J Korean Acad Child Health Nurs. 2006;12(3):341–350.
9. Leem HS. The relationship among self-efficacy, family function, and health promoting behaviors of middle school students [master's thesis]. Gwangju: Chonnam National University; 2004. 44 p.
10. June KJ, Sohn SY, So AY, Yi GM, Park SH. A study of factors that influence internet addiction, smoking, and drinking in high school students. J Korean Acad Nurs. 2007;37(6):872–882. Article PDF
11. Byeon YS, Lee HS. The effects of internet addiction on mental health among adolescents. J Korean Acad Community Health Nurs. 2007;18(3):460–468.
12. Korea Agency for Digital Opportunity and Promotion. The survey of 2006 Internet Addiction [Internet] Seoul: Korea Agency for Digital Opportunity and Promotion; 2006;cited 2014 October 31. Available from: https://www.nia.or.kr/bbs/board_view.asp?BoardID=201408061323065914&id=257&Order=020303&search_target=&ke yword=&Flag=020000&nowpage=1&objpage=0
13. Belloc NB, Breslow L. Relationship of physical health status and health practices. Prev Med. 1972;1(3):409–421. Article PubMed
14. Kim KH, Ann SY, Jang SS, Kim ML, Choi DS. International comparative study on the life patterns of youth and children. Seoul: Ministry of Health & Welfare; 2009. 03;Report No.: 11-1351000-000305-01.
15. Korea Centers for Disease Control and Prevention. News release [Internet] Seoul: Korea Centers for Disease Control and Prevention; 2013;cited 2014 November 01. Available from: http://yhs.cdc.go.kr/
16. United States Department of Agriculture. Food Nutrition Service: School breakfast program fact sheet [Internet] Alexandria: Food Nutrition Service; 2007;cited 2014 November 01. Available from: http://www.fns.usda.gov/cud/Breakfast/AboutBFast/bfastfacts.htm
17. National Sleep Foundation Sleep and Teens Task Force. Adolescent sleep needs and patterns. Research Report and Research Guide. Washington, DC: National Sleep Foundation; 2000. p. 30.
18. Choi IJ. Korean youth indicator survey V. Research Report. Seoul: National Youth Policy Institute; 2010. p. 350.
19. Kim EG. Analysis of the risk factors in the health behavior of Korean adolescents [dissertation]. Seoul: Yonsei University; 2011. 100 p.
20. Ko CH, Yen JY, Chen CC, Chen SH, Yen CF. Gender differences and related factors affecting online gaming addiction among Taiwanese adolescents. J Nerv Ment Dis. 2005;193(4):273–277.Article PubMed
21. Kim YA, Kim SS, Jung MS, Han CH. High school students' degree conducting on health promoting behavior and related factors. Korean J Health Educ Promot. 2000;17(1):1–18.
22. Chon MY, Kim MH, Cho CM. Predictors of health promoting lifestyles in Korean undergraduate students. Korean J Health Educ Promot. 2002;19(2):1–13.
23. Song YLA. The factors influencing health behavior [master's thesis]. Seoul: Yonsei University; 2004. 69 p.
24. Siomos KE, Dafouli ED, Braimiotis DA, Mouzas OD, Angelopoulos NV. Internet addiction among Greek adolescent students. Cyberpsychol Behav. 2008;11(6):653–657.Article PubMed
25. Kim KS. An comparative analysis of ecological variable affecting internet addiction tendency of adolescents between metropolitan and rural areas. J Soc Res. 2011;21(1):121–156.
26. Park E. A comparative study of youth health risk behaviors by region: Focused on metropolitan areas, medium sized and small city areas, and rural areas. J Korean Acad Nurs. 2010;40(1):14–23.Article PubMed
27. Yen JY, Ko CH, Yen CF, Chen CS, Chen CC. The association between harmful alcohol use and internet addiction among college students: Comparison of personality. Psychiatry Clin Neurosci. 2009;63(2):218–224.Article PubMed
28. Yoo CH, Han SH, Park YJ, Park JS, Kim JE. Correlation between time using the computer and adolescent obesity-in a boys' middle school students in Busan. Korean J Health Promot Dis Prev. 2006;6(4):207–212.
29. Kim JS, Chun BC. Association of internet addiction with health promotion lifestyle profile and perceived health status in adolescents. J Prev Med Public Health. 2005;38(1):53–60. PubMed
30. Lim JE. A study on the relationship between internet addiction of some high school students and their health behavior [master's thesis]. Seoul: Ewha Womans University; 2012. 69 p.

Figure & Data

References

Citations

Citations to this article as recorded by

Effect of Health Behaviors Practice on Mental Health in Adolescents
Hyun Jung Yun
Journal of Health Informatics and Statistics.2022; 47(3): 199. CrossRef
Impact of Internet usage time on mental health in adolescents: Using the 14th Korea Youth Risk Behavior Web-Based Survey 2018
Yeunhee Kwak, Hyejin Kim, Jung-Won Ahn, Sergio A. Useche
PLOS ONE.2022; 17(3): e0264948. CrossRef
Effect of Body Image Distortion on Health Behaviors Practice in High School Students
Hyun Jung Yun
Stress.2020; 28(2): 98. CrossRef
Daily Smoking Girls' Tobacco Use, Health Behaviors and Family Factors : Analysis of 2015 Korean Youth Risk Behavior Web-based Survey
Youngjin Lee
Journal of Digital Convergence.2016; 14(5): 377. CrossRef

PubReader
Cite

CITE

export Copy Format

Close

XML Download

We recommend

The Relationship between Internet Use and Health Behaviors among Adolescents

Variables	Characteristics	Categories	n (%) or M±SD
Health behaviors	Smoking	Yes	8,362 (11.3)
	Smoking	No	65,824 (88.7)
	Drinking	Yes	14,323 (19.3)
	Drinking	No	59,863 (80.7)
	Weight control	Yes	65,687 (90.9)
	Weight control	No	6,542 (9.1)
	Regular exercise	Yes	26,251 (35.4)
	Regular exercise	No	47,935 (64.6)
	Eating breakfast	Yes	35,734 (48.2)
	Eating breakfast	No	38,452 (51.8)
	Sufficient sleep	Yes	22,952 (36.0)
	Sufficient sleep	No	40,734 (64.0)
Internet use	Time (minute)	Weekday	149.0±122.64
	Time (minute)	Weekend	209.7±142.37
	Service	Learning	10,787 (14.5)
		Information retrieval	9,025 (12.2)
		Messenger/chatting	6,989 (9.4)
		Game	23,451 (31.6)
		Movie download	3,052 (4.1)
		MP3/Music download	7,057 (9.5)
		Animation/Story download	4,268 (5.8)
		UCC	673 (0.9)
		Association/community	2,775 (3.7)
		E-mail	159 (0.2)
		On-line shopping	2,054 (2.8)
		Pornography retrieval	531 (0.7)
		Blog/mini homepage	3,216 (4.3)
		Others	152 (0.2)

Variables	Categories	n (%)	Internet use time (minute)				Health Practice Index
			Weekday		Weekend		Health Practice Index
			M±SD	t (p)	M±SD	t (p)	M±SD	t (p)
Gender	Male	38,221 (51.5)	154.7±128.89	6.88 (<.001)	223.5±146.25	22.08 (<.001)	4.1±1.72	9.22 (<.001)
Gender	Female	35,965 (48.5)	142.1±120.98	6.88 (<.001)	180.1±135.51	22.08 (<.001)	3.9±1.68	9.22 (<.001)
Depression	Yes	22,745 (30.7)	163.0±141.20	-9.54 (<.001)	222.1±159.10	-9.54 (<.001)	3.5±1.82	39.17 (<.001)
Depression	No	51,441 (69.3)	144.4±118.79	-9.54 (<.001)	202.0±137.14	-9.54 (<.001)	4.3±1.59	39.17 (<.001)
Suicidal intent	Yes	13,635 (18.4)	169.6±154.38	-10.31 (<.001)	228.2±168.90	-9.76 (<.001)	3.3±1.82	36.25 (<.001)
Suicidal intent	No	60,551 (81.6)	145.6±118.69	-10.31 (<.001)	203.5±137.89	-9.76 (<.001)	4.2±1.63	36.25 (<.001)
Father's education (year)	≤12	32,212 (45.3)	144.3±121.47	-3.69 (<.001)	196.0±133,52	-9.51 (<.001)	4.3±1.59	10.17 (<.001)
Father's education (year)	>12	38,915 (54.7)	150.8±122.36	-3.69 (<.001)	214.2±146.26	-9.51 (<.001)	3.9±1.75	10.17 (<.001)
Mother's education (year)	≤12	25,507 (35.8)	144.4±123.15	-3.01 (.003)	194.9±134.23	-8.42 (<.001)	4.4±1.55	22.94 (<.001)
Mother's education (year)	>12	45,792 (64.2)	149.9±121.36	-3.01 (.003)	211.6±143.43	-8.42 (<.001)	3.9±1.74	22.94 (<.001)
Cohabitant	Both-parent	60,490 (87.7)	144.8±119.29	-7.31 (<.001)	201.4±136.96	-10.74 (<.001)	4.2±1.64	20.56 (<.001)
Cohabitant	Single-parent or none-parent	8,500 (12.3)	164.6±133.71	-7.31 (<.001)	233.2±155.93	-10.74 (<.001)	3.6±1.81	20.56 (<.001)
City scale	Big	33,568 (45.2)	149.1±124.46	-0.69 (.492)	202.6±139.03	-4.80 (<.001)	4.1±1.68	4.61 (<.001)
City scale	Middle or small	40,618 (54.8)	150.4±127.36	-0.69 (.492)	211.8±147.68	-4.80 (<.001)	4.0±1.72	4.61 (<.001)
School grade	Middle school	37,297 (50.3)	147.7±121.96	-3.00 (.003)	196.0±136.42	-14.89 (<.001)	4.8±1.28	79.98 (<.001)
School grade	High school or vocational high school	36,889 (49.7)	153.1±131.08	-3.00 (.003)	225.0±152.83	-14.89 (<.001)	3.0±1.72	79.98 (<.001)

Variables	Categories	Internet use time (minute)
		Weekday			Weekend
		M±SD	t	p	M±SD	t	p
Smoking	Yes	174.1±156.89	12.54	<.001	241.4±175.27	15.57	<.001
Smoking	No	144.7±117.95	12.54	<.001	201.2±136.09	15.57	<.001
Drinking	Yes	169.1±147.80	12.63	<.001	233.9±167.90	15.51	<.001
Drinking	No	143.3±117.08	12.63	<.001	199.4±134.42	15.51	<.001
Weight control	Yes	145.4±118.43	7.18	<.001	200.5±136.23	15.21	<.001
Weight control	No	166.2±139.65	7.18	<.001	248.1±161.29	15.21	<.001
Regular exercise	Yes	147.8±124.04	2.38	.017	203.0±136.60	5.31	<.001
Regular exercise	No	152.1±128.22	2.38	.017	213.2±151.94	5.31	<.001
Eating breakfast	Yes	141.5±119.80	12.06	<.001	196.2±134.92	16.10	<.001
Eating breakfast	No	163.7±134.75	12.06	<.001	228.1±156.61	16.10	<.001
Sufficient sleep	Yes	139.8±108.25	8.50	<.001	191.9±127.18	14.85	<.001
Sufficient sleep	No	154.9±129.80	8.50	<.001	220.9±149.90	14.85	<.001

Variables	Categories	HPI	Internet use time
Variables	Categories	HPI	Weekday	Weekend
HPI		1
Internet use time	Weekday	-.11^*	1
Internet use time	Weekend	-.15^*	.61^*	1

Table 1 Health Behaviors and Internet Use Characteristics (N=74,186)

Table 2 Health Behaviors and Internet Use by General Characteristics (N=74,186)

Table 3 Internet Use Time by Health Behaviors (N=74,186)

Table 4 Correlation of Health Practice Index and Internet Use Time

^*P<.01 by Pearson Correlation; HPI=Health practice index.