Department of Psychological Sciences, Case Western Reserve University, Cleveland, USA.
Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA.
Prev Sci. 2023 Nov;24(8):1499-1509. doi: 10.1007/s11121-022-01441-w. Epub 2022 Oct 13.
Integrative data analysis (IDA) was used to derive developmental models of depression, externalizing problems, and self-regulatory processes in three prevention trials of the Family Check-Up and one longitudinal, community-based study of girls over a 10-year span covering early to late adolescence (N = 4,773; 74.9% female, 41.7% white). We used moderated nonlinear factor analysis to create harmonized scores based on all available items for a given participant in the pooled dataset while accounting for potential differences in both the latent factor and the individual items as a function of observed covariates. We also conducted latent growth model analyses to examine developmental trajectories of risk. Results indicated a bidirectional relationship between depression and externalizing problems, with greater baseline externalizing problems and depression predicting growth in inhibitory control difficulties. Furthermore, initial level of inhibitory control difficulties was associated with growth in depression. We did not, however, find a relationship between early inhibitory control difficulties and growth in externalizing problems. This work illustrates the utility of IDA techniques to harmonize data across multiple studies to identify risk factors for the development of depression and externalizing problems that can be targeted by prevention efforts.
综合数据分析(IDA)被用于推导三个预防试验(家庭检查和一个纵向的、基于社区的女孩研究)和一个长达 10 年的、涵盖早期到晚期青春期的研究中的抑郁、外化问题和自我调节过程的发展模型,共涉及 4773 名参与者(74.9%为女性,41.7%为白人)。我们使用了适度的非线性因子分析,在汇总数据集的所有可用项的基础上创建了协调分数,同时考虑了潜在因子和作为观察协变量函数的个体项的潜在差异。我们还进行了潜在增长模型分析,以研究风险的发展轨迹。结果表明,抑郁和外化问题之间存在双向关系,较大的基线外化问题和抑郁预测抑制控制困难的增长。此外,初始抑制控制困难水平与抑郁的增长有关。然而,我们并没有发现早期抑制控制困难与外化问题的增长之间存在关系。这项工作说明了 IDA 技术在协调多个研究数据以识别抑郁和外化问题发展的风险因素方面的实用性,这些因素可以成为预防工作的目标。