Latent Class Analysis of Gambling Activities among Korean Adolescents

Kyonghwa Kang; Hyeongsu Kim; Ae Ran Park; Hee-Young Kim; Kunsei Lee

doi:10.4040/jkan.2018.48.2.232

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Kang, Kim, Park, Kim, and Lee: Latent Class Analysis of Gambling Activities among Korean Adolescents

Original Article

J Korean Acad Nurs 2018;48(2):232-240.

Published online: 15 January 2018

DOI: https://doi.org/10.4040/jkan.2018.48.2.232

Latent Class Analysis of Gambling Activities among Korean Adolescents

Kyonghwa Kang¹, Hyeongsu Kim^2,, Ae Ran Park³, Hee-Young Kim⁴, Kunsei Lee²

¹The Research Institute of Nursing Science, Seoul National University

²Department of Preventive Medicine, School of Medicine, Konkuk University

³Department of Prevention & Public Relations, Korea Center On Gambling Problems, Seoul

⁴Department of Child Welfare, Namseoul University, Cheonan, Korea

Address reprint requests to : Kim, Hyeongsu Department of Preventive Medicine, School of Medicine, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Korea Tel: +82-2-2030-7942 Fax: +82-2-2049-6192 E-mail: mubul@kku.ac.kr

Received 28 December 2017 Revised 4 April 2018 Accepted 12 April 2018

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0) If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium.

Abstract

Purpose

The aim of this study is to identify the types of gambling among adolescents and provide basic prevention information regarding adolescents’ gambling problems.

Methods

Secondary data from representative national survey on 2015 Youth Gambling Problems of Korea Center on Gambling Problems were used. Using latent class analysis (LCA), 13 gambling types such as offline and online games of 14,011 adolescents were classified, and gambling experiences and characteristics were analyzed.

Results

The subgroups of adolescent gambling were identified as four latent classes: a rare group (84.5% of the sample), a risk group (1.0%), an offline group (11.9%), and an expanded group (2.6%). The types and characteristics of gambling among the latent classes differed. In the risk group, adolescents participated in online illegal sports betting and internet casino, and gambling time, gambling expenses, and the number of gambling types were higher than other groups.

Conclusion

Gambling frequently occur among adolescent, and the subtypes of gambling did not reveal homogeneous characteristics. In order to prevent adolescent gambling problems, it is a necessary to develop tailored prevention intervention in the nursing field, which is appropriate to the characteristics of adolescent gambling group and can help with early identification.

Keywords: Adolescent, Gambling, Primary Prevention, Secondary Prevention

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Figure 1.

Youth gambling type by latent classes.

Table 1.

Description of the Study Population

Item	Frequency (n=14,011^†)	Percentag (100.0%)	M±SD
Gender
Male	7,349	52.5
Female	6,662	47.5
Age			14.96±1.43
Home region
Capital	2,357	16.8
Metropolitan	3,664	26.1
Province	7,990	57.1
School year
Middle school 1	2,346	16.7
Middle school 2	2,670	19.1
Middle school 3	3,020	21.6
High school 1	2,974	21.2
High school 2	3,001	21.4
Lifetime gambling behavior experience
Yes	5,895	42.1
No	8,116	57.9
First onset of gambling			12.12±2.71
Number of gambling behavior			0.53±1.22
3 month gambling behavior experience
Yes	3,393	24.2
No	10,618	75.8
Gambling of significant others
Yes	2,216	15.8
No	8,724	62.3
Don’t know	3,071	21.9
Nearby gambling place
Yes	1,123	8.0
No	8,742	62.4
Don’t know	4,146	29.6

M±SD=Mean±standard deviation.

^†The number of samples to which weights are applied after parameter estimation.

Table 2.

Model Fit Indices of the Latent Class Analysis Solutions

Model	AIC	BIC	Entropy	LMR-LRT	p^†
1 classes	53,839.45	53,937.57	−	−
2 classes	43,047.84	43,251.63	0.89	10,819.61	<.001
3 classes	41,968.80	42,278.25	0.89	1,107.04	<.001
4 classes	41,748.91	42,164.03	0.86	247.89	<.001
5 classes	41,628.34	42,149.12	0.87	147.32	.290

AIC=Akaike’s Information Criterion; BIC=Bayesian Information Criterion; LCA=Latent Class Analysis; LMR-LRT=Lo Mendel Rubin Likelihood Ratio Test.

^†p value for the k versus k-1 class solution.

Table 3.

Comparisons among Gambling Subclasses of the Latent Classes Analysis

Item	Class 1 (84.5%)	Class 2 (1.0%)	Class 3 (11.9%)	Class 4 (2.6%)	χ²/F	p
	n (%) or M±SD	n (%) or M±SD	n (%) or M±SD	n (%) or M±SD
Gender
Male	5,980 (50.5)	118 (86.8)	1,001 (60.0)	250 (68.3)	165.83	<.001
Female	5,628 (49.5)	18 (13.2)	668 (40.0)	116 (31.7)
Age (yr)	14.94±1.49^a)	15.64±1.31^b)	15.13±1.41^a)	14.98±1.48^a)	12.10	<.001
Home region
Capital	2,044 (17.3)	13 (9.6)	250 (15.0)	50 (13.7)	14.06	.029
Metropolitan	3,092 (26.1)	38 (27.9)	439 (26.3)	95 (26.0)
Province	6,703 (56.6)	85 (62.5)	981 (58.7)	221 (60.3)
First onset of	12.09±2.79^a)	13.72±2.61^b)	12.66±2.68^a)	12.56±2.54^a)	20.22	<.001
gambling (yr)
First pattern of gambling
Offline	3,618 (97.2)	88 (64.7)	1,531 (91.7)	332 (90.7)	315.94	<.001
Online	106 (2.8)	48 (35.3)	139 (8.3)	34 (9.3)
Frequent pattern of gambling
Offline	1,216 (99.6)	70 (51.5)	1,510 (90.4)	323 (88.3)	330.09	<.001
Online	5 (0.4)	66 (48.5)	132 (9.6)	43 (11.7)
Frequency of gambling (times/week)
≤1	1,192 (97.6)	104 (75.9)	1,516 (90.8)	328 (89.6)	123.57^†	<.001^†
2~6	29 (2.4)	25 (18.3)	132 (7.9)	30 (8.2)
7	0 (0.0)	8 (5.8)	21 (1.3)	8 (2.2)
Number of	0.10±0.30^a)	6.61±2.35^d)	2.12±0.76^b)	4.71±0.81^c)	27,355.91	<.001
gambling behavior
Time used for	21.36±32.20^a)	94.59±99.39^d)	42.33±52.52^b)	55.31±72.48^c)	13.11	<.001
gambling (minute)
Money spent on	4,987.03±14,624.59^a)	220,670.11±60,635.01^b	⁾ 15,320.73±2,560.73^a)	117,209.74±46,421.52^a)	75.32	<.001
gambling (won)
Money lost by	3,761.29±16,790.16^a)	88,817.73±28,034.38^b)	8,013.07±50,901.05^a)	113,330.06±64,092.05^a)	49.49	<.001
gambling (won)
Money won by	11,462.10±89,029.36^a)	253,538.12±50,786.11^b	⁾ 24,745.49±3,657.89^a)	23,687.53±2,385.33^a)	111.99	<.001
betting (won)
Gambling of significant others
Yes	1,531 (12.9)	76 (55.9)	465 (27.9)	144 (39.3)	598.69	<.001
No	7,704 (65.1)	34 (25.0)	849 (50.9)	137 (37.3)
Do not know	2,604 (22.0)	26 (19.1)	355 (21.2)	86 (23.4)
Nearby gambling place					40.19	<.001
Yes	888 (7.5)	23 (16.8)	165 (9.9)	46 (12.6)
No	7,434 (62.8)	77 (56.2)	1,030 (61.7)	202 (55.2)
Do not know	3,517 (29.7)	37 (27.0)	474 (28.4)	118 (32.2)

M±SD=Mean±standard deviation.

^*Except for missing factors, the total number of cases is different.

^†Fisher’s exact test.

^a)~d)Scheffe’s test (mean with the other letter significantly different).

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