The influence of school assets on the development of well-being during early adolescence: Longitudinal mediating effect of intentional self-regulation

doi:10.3724/SP.J.1041.2020.00874

Abstract

Abstract:

Well-being is an important aspect of an adolescent’s mental health, which has been recognized by a majority of developmental psychologists. Relatively few studies, however, have examined the latent growth of well-being, particularly during early adolescence. School assets include the school environment, relationships with teachers, and the young person’s attitude toward school. Existing research has shown that school assets are closely related to the current and future well-being of adolescents. However, little is known about the longitudinal mediating mechanism between the two variables. The current study used latent growth curve modeling to examine developmental trends in school assets, intentional self-regulation and well-being, incorporating a three-wave longitudinal design. On this basis, a longitudinal mediation model was constructed to examine the effect and longitudinal mediation of the level and slope of intentional self-regulation between school assets and the development of well-being.

A sample of 1214 schoolchildren (mean age = 12.89 years, SD = 0.51) was followed up for three years from the first year of junior high school to the third year of junior high school. In three waves, they anonymously filled out questionnaires regarding school assets, intentional self-regulation and well-being. All of the measures showed good reliability and validity. The adolescents’ socio-demographic information was collected at the first wave. We used SPSS 21.0 and Mplus 7.4 to analyze the data. A series of models were tested in the following sequence. First, we used the latent growth models to examine the development trend of each variable; second, we examined the effects of school assets on well-being by using the parallel process models; third, we used a longitudinal mediating model to examine the mediation hypothesis. In this model, we first used a causal-step strategy to inspect the specific paths, and used the bootstrap method to test the indirect effects.

Results showed that, during early adolescence, school assets remained stable, self-regulation and well-being increased in a linear manner during the follow-up period. However, the higher the initial level, the slower the growth rate. After controlling for gender and district, the structural equation model showed that school assets had a positive effect on the level of well-being, but it could not directly predict the growth rate of well-being. School assets can indirectly affect the initial level of well-being through the initial level of intentional self-regulation.

These findings suggested that early adolescence may be a critical period for the development of intentional self-regulation and well-being. They not only highlighted the importance of school assets for the growth of intentional self-regulation and well-being during early adolescence, but also confirmed the indirect role of the adolescent’s own developmental strength in the relationship between school assets and well-being.

Key words: school assets, intentional self-regulation, well-being, early adolescence, latent growth modeling

CHANG Shumin, GUO Mingyu, WANG Jingmin, WANG Lingxiao, ZHANG Wenxin. (2020). The influence of school assets on the development of well-being during early adolescence: Longitudinal mediating effect of intentional self-regulation. Acta Psychologica Sinica, 52(7), 874-885.

Figures/Tables 6

References 70

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Variables	1	2	3	4	5	6	7	8	9
1 School assets T1	1
2 School assets T2	0.57^***	1
3 School assets T3	0.49^***	0.56^***	1
4 ISR T1	0.40^***	0.23^***	0.21^***	1
5 ISR T2	0.29^***	0.36^***	0.27^***	0.32^***	1
6 ISR T3	0.31^***	0.29^***	0.40^***	0.22^***	0.34^***	1
7 Well-being T1	0.54^***	0.35^***	0.31^***	0.32^***	0.27^***	0.28^***	1
8 Well-being T2	0.37^***	0.48^***	0.34^***	0.26^***	0.32^***	0.28^***	0.51^***	1
9 Well-being T3	0.31^***	0.31^***	0.50^***	0.17^***	0.21^***	0.35^***	0.41^***	0.54^***	1
M	20.78	20.95	20.90	33.13	33.63	34.75	34.45	34.22	34.85
SD	5.30	5.49	5.50	5.28	5.61	5.38	6.37	6.42	6.55

Variables	1	2	3	4	5	6	7	8	9
1 School assets T1	1
2 School assets T2	0.57^***	1
3 School assets T3	0.49^***	0.56^***	1
4 ISR T1	0.40^***	0.23^***	0.21^***	1
5 ISR T2	0.29^***	0.36^***	0.27^***	0.32^***	1
6 ISR T3	0.31^***	0.29^***	0.40^***	0.22^***	0.34^***	1
7 Well-being T1	0.54^***	0.35^***	0.31^***	0.32^***	0.27^***	0.28^***	1
8 Well-being T2	0.37^***	0.48^***	0.34^***	0.26^***	0.32^***	0.28^***	0.51^***	1
9 Well-being T3	0.31^***	0.31^***	0.50^***	0.17^***	0.21^***	0.35^***	0.41^***	0.54^***	1
M	20.78	20.95	20.90	33.13	33.63	34.75	34.45	34.22	34.85
SD	5.30	5.49	5.50	5.28	5.61	5.38	6.37	6.42	6.55

Variables	χ2	df	RMSEA	CFI	TLI	Mean		Correlations
Variables	χ2	df	RMSEA	CFI	TLI	Intercept	Slope	Correlations
ISR	3.83	1	0.051	0.992	0.977	33.03^***	0.44^***	-0.24^*
Well-being	5.05	1	0.014	0.995	0.986	34.16^***	0.11^*	-0.20^*
School assets	0.19	1	0.001	1.000	1.003

Variables	χ2	df	RMSEA	CFI	TLI	Mean		Correlations
Variables	χ2	df	RMSEA	CFI	TLI	Intercept	Slope	Correlations
ISR	3.83	1	0.051	0.992	0.977	33.03^***	0.44^***	-0.24^*
Well-being	5.05	1	0.014	0.995	0.986	34.16^***	0.11^*	-0.20^*
School assets	0.19	1	0.001	1.000	1.003

Pathways	β	B	SE	p
SA → ISR intercept	0.63	0.39	0.04	0.000
SA → ISR slope	0.52	0.52	0.07	0.000
SA → WB intercept	0.29	0.30	0.07	0.000
SA → WB slope	0.19	0.09	0.19	0.296
ISR intercept → WB intercept	0.53	0.87	0.09	0.000
ISR intercept → WB slope	-0.67	-0.51	0.17	0.000
ISR slope → WB slope	0.74	0.92	0.19	0.000