Society for Research on Adolescence (SRA) Biennial Meeting
April 12-14, 2018
Presentation Title: "School Connectedness and Chinese Adolescents’ Sleep Problems: A Cross-Lagged Panel Analysis" (poster)
Authors: Zhenzhou Bao (Gannan Normal University), Chuansheng Chen, Wei Zhang (South China Normal University), Yanping Jiang (University of South Carolina), Jianjun Zhu (South China Normal University), Xuefen Lai (Jiaying University), Jintao Xing (South China Normal University)
Previous studies have focused on the roles of school structural factors (e.g., school start time, the demands of homework) in adolescents’ sleep quality, however, social and psychological factors, such as school connectedness, are underemphasized parameters in adolescents’ sleep (Maume, 2013).
School connectedness refers to a students’ relationship to school and his or her feelings about school (Libbey, 2004). Adolescents who are connected to school are likely to form supportive interpersonal relationships with teachers and peers, the possibilities of emotional problems and physical symptoms are reduced (Cohen, 2004), which may facilitate better sleep quality. Thus, we proposed the hypothesis 1: higher level of school connectedness would predict better adolescents’ sleep quality.
Does better sleep quality also predict more school connectedness among adolescents? Poor sleep quality may hinder individuals’ affective functioning or emotion regulation skills, which could make it more difficult for adolescents to establish social connectedness to school (Tavernier & Willoughby, 2015). Accordingly, we proposed the hypothesis 2: better sleep quality would predict more school connectedness among adolescents.
At the beginning of academic year (September, 2014), 1053 adolescents (45.20% boys, Mage = 14.95) were recruited from two public schools in Southern China. At the end of academic year (June, 2015), a total of 888 adolescents (43.80% boys; Mage = 14.93) took part in the second waves of data collection. Participants completed the questionnaire of school connectedness and Pittsburgh Sleep Quality Index (PSQI).
Structural equation modeling (SEM) was conducted to test this cross-lagged model using Mplus 7.0. The model fit the data well: χ2(183) = 444.61; CFI = .97; TLI = .96; RMSEA = .04; SRMR = .04. As shown in Figure 1, more sleep problems at Time 1 predicted lower level of school connectedness at Time 2 (b = –.26, SE = .13, β = –.10, p < .05), but higher school connectedness at Time 1 did not predict lower level of sleep problems at Time 2 (b = .05, SE = .03, β = .09, p > .05). Separate analyses by sex showed that the above pattern of results was mainly driven by the boys (see Table 1).
Our results imply that adolescents who have sleeping problems are at increased risks for having low level of school connectedness. Previous research has indicated that sleep-related deficits in emotional functioning and self-regulation skill may disrupt the formation of connectedness to school (Tavernier & Willoughby, 2015). Thus, we can improve adolescents’ sleep quality to boost their connectedness to school.
However, we did not found evidence to support the hypothesis that school connectedness would be predictive of adolescents’ sleep problems. Umberson, Crosnoe, and Reczek (2010) proposed that “it is the constellation of social ties, not any single tie, [that] matters most for health habits in adolescence”. Thus, various social connectednesses, including ties with family, school, peers, and neighborhood should be measured in future research.
In summary, the current study is an important step towards a better understanding of the relation between school connectedness and adolescents’ sleep quality. It shows that better sleep quality boost male adolescents’ school connectedness, rather than the reversed direction.