Abstract:

Given a broad range of changes in cognitive, emotional, and social relationships, adolescence might mark the beginning of a period of significant fluctuations in psychosocial adaptation because it is a period of preparation for the future that requires special attention and protective measures. The developmental characteristics of different aspects of adolescents’ adaptation have been well studied. However, these previous studies, which have tended to explore various aspects of adolescents’ adaptation in isolation, have been unable to reflect the diversity of adolescents’ adaptation patterns and their variability over time. In addition, exploring and determining school situation-related predictors are essential for helping education professionals understand the relevant factors that affect various profiles and transition patterns of adolescents’ adaptation and, thus, formulate effective prevention and intervention programs to maintain and improve adolescents’ psychosocial adaptation. This study uses a person-centered approach to explore the profiles and transition patterns of early adolescents’ psychosocial adaptation and investigate gender differences and the protective role of school assets.
A sample of 1012 junior middle school students was selected as participants and measured three times. The adolescents completed loneliness, depression, happiness, school assets scales, and peer nomination forms during the three measurements. The head teacher assessed the students’ prosocial and externalized problem behaviors. The descriptive statistics and multiple logistic regression were analyzed by SPSS 21.0. In this study, Mplus 7.4 was used to analyze the LPA first, and then the LTA. A series of cross-sectional LPAs were fitted using the samples at T2 and T3 to determine the number of classes to be used in the subsequent LTA.
The results showed that early adolescents’ psychosocial adaptation had two profiles at T1: a well-adapted profile and an internalizing problem profile. Early adolescents at T2 and T3 were divided into four profiles: a well-adapted profile, an internalizing problem profile, an externalizing problem profile, and a peer rejection profile (see Figure 1).
The LTA results are presented in Table 1. The diagonal of the transition matrix indicates the probability that the subject would maintain the original latent state at two adjacent time points. As shown, from T2 to T3, the well-adapted profile showed the highest stability, followed by the internalizing problem profile and the externalizing problem profile, across the one-year period. The peer acceptance profile showed the lowest stability.
Of those students who exhibited instability from T2 to T3, adolescents who initially corresponded to the internalizing problem profile, externalizing problem profile, or peer rejection profile tended to gradually transition to the well-adapted profile over time. Adolescents corresponding to the well-adapted profile had the same probability of transition to the other three profiles.
After district、SES and school type were controlled, at T1, a unit increase in school assets at T1 was associated with 62% (OR = 0.38, p < 0.001) decreases in the odds of membership in the internalizing problem profile at T1, compared to the odds of membership in the well-adapted profile at T1.
At T2, girls were more likely to belong to the internalizing problem profile (OR = 1.78, p < 0.05) than to the well-adapted profile. Additionally, a unit increase in school assets at T2 was associated with 59%, 24%, and 47% decreases in the odds of membership in the internalizing problem profile, externalizing problem profile, and peer rejection profile at T2 (OR = 0.41, p < 0.001; OR = 0.76, p < 0.05; OR = 0.53, p < 0.001), respectively, compared to the odds of membership in the well-adapted profile at T2.
At T3, a unit increase in school assets at T3 was associated with 61%, 45%, and 52% decreases in the odds of membership in the internalizing problem profile, externalizing problem profile, and peer rejection profile at T3 (OR = 0.39, p < 0.001; OR = 0.55, p < 0.001; OR = 0.48, p < 0.001), respectively, compared to the odds of membership in the well-adapted profile at T3.
We further explored the influence of various factors on profile transitions. The subjects in the original latent state were used as the reference group. The occurrence ratio refers to the ratio of the probability of the subject's transition to another group and the change in the probability of maintaining the original group. As shown in Table 2, after district、SES and school type were controlled, from T2 to T3, a unit increase in school assets at T2 significantly decreased the odds of transfer from the well-adapted profile at T2 to the externalizing problem profile or peer rejection profile at T3 by 32% and 47%, respectively (OR = 0.68, p = 0.03, 95% CI [0.48 0.97]; OR = 0.53, p = 0.022, 95% CI [0.31 0.90], respectively). A unit increase in school assets at T2 significantly increased the odds of transfer from the externalizing problem profile or peer rejection profile at T2 to well-adapted profile at T3 (OR = 3.71, p = 0.01, 95% CI [1.40 9.83]; OR = 2.79, p = 0.01, 95% CI [1.33 5.85], respectively). Additionally, a unit increase in school assets at T2 significantly decreased the odds of transfer from the peer rejection profile at T2 to the internalizing problem profile at T3 by 60% (OR = 0.40, p = 0.01, 95% CI [0.20 0.79]).
This study adds to the understanding of the diversity of the psychosocial adaptation development patterns of early adolescents and suggests the need for comprehensive screening and dynamic monitoring of adolescent adaptation and more complex intervention programs tailored to the specific characteristics of the relevant groups and boys and girls. In addition, identifying the protective role of school assets can help mental health professionals understand the supporting factors in the development of individual health, thereby promoting the positive development of adolescents. Moreover, this study provides a reference for school context-based assessment and intervention strategies.

Key words: school assets, early adolescents, psychosocial adaptation, latent profile analysis, latent transition analysis