School of Psychology, University of Adelaide, Australia.
Adelaide Health Technology Assessment, University of Adelaide, Adelaide, Australia.
J Adolesc. 2020 Dec;85:1-11. doi: 10.1016/j.adolescence.2020.09.004. Epub 2020 Sep 30.
This study explored the extent to which disaggregated support from family, peers, close friendships, teachers, and schools predicted membership into identified, sex-specific trajectories of depressed mood in 3210 Australian adolescents (49% females) based on self-report data collected at four annual time points from school Grade 6 to 9 (ages 10-16).
The sample was initially split by sex. Group-Based Trajectory Modelling was used to identify the trajectory groups using a Censored Normal model, starting with a two-group model and increasing group size in increments of one, up to a six-group model. Overall model-fit and specific model-fit criteria were examined, and participants were allocated to best-fit groups. Multinomial Logistic Regression examined the associations between baseline social supports and allocated trajectory group membership.
For boys, four trajectory groups were identified which were given the qualitative labels; Low Stable, Moderate Stable, Moderate Decreasing, and High Stable. Regression analysis showed that higher rates of peer belonging were associated with membership in the low and moderate groups compared to the High Stable group. For girls, four trajectory groups were identified and labelled as Low Stable, Moderate Decreasing, Moderate Increasing and High Increasing. Regression analysis showed that higher rates of family support, school climate, and peer belonging were associated with membership in the low and moderate groups compared to the High Increasing group.
Implications included the need for school-based early intervention programs to consider disaggregated supports and vary their interventions by sex. Limitations and directions for future research are discussed.
本研究旨在探讨家庭、同伴、亲密友谊、教师和学校提供的支持在多大程度上可以预测 3210 名澳大利亚青少年(49%为女性)在自我报告数据的基础上,按照性别进行分组,基于从六年级到九年级(10-16 岁)的四次年度时间点收集的数据,确定特定性别轨迹的抑郁情绪。
首先按照性别对样本进行分组。使用基于分组的轨迹建模,使用 Censored Normal 模型来识别轨迹组,从两群组模型开始,群组大小递增 1,最多增加到六群组模型。检查了总体模型拟合和特定模型拟合标准,并将参与者分配到最佳拟合组。多变量逻辑回归分析了基线社会支持与分配的轨迹组归属之间的关联。
对于男孩,确定了四个轨迹组,并赋予了定性标签;低稳定、中稳定、中下降和高稳定。回归分析表明,与高稳定组相比,同伴归属感较高的男孩更有可能属于低和中组。对于女孩,确定了四个轨迹组,并分别标记为低稳定、中下降、中增加和高增加。回归分析表明,与高增加组相比,家庭支持、学校氛围和同伴归属感较高的女孩更有可能属于低和中组。
研究结果表明,需要在学校开展早期干预计划,考虑到支持的多样性,并根据性别调整干预措施。讨论了研究的局限性和未来研究方向。