The latent trait-state-error model (TSE) and the latent state-trait model with autoregression (LST-AR) represent creative structural equation methods for examining the longitudinal structure of psychological constructs. Application of these models has been somewhat limited by empirical or conceptual problems. In the present study, Monte Carlo analysis revealed that TSE models tend to generate improper solutions when N is too small, when waves are too few, and when occasion factor stability is either too large or too small. Mathematical analysis of the LST-AR model revealed its limitation to constructs that become more highly auto-correlated over time. The trait-state-occasion model has fewer empirical problems than does the TSE model and is more broadly applicable than is the LST-AR model.

The utility and flexibility of recent advances in statistical methods for the quantitative analysis of developmental data—in particular, the methods of individual growth modeling and survival analysis—are unquestioned by methodologists, but have yet to have a major impact on empirical research within the field of developmental psychopathology and elsewhere. In this paper, we show how these new methods provide developmental psychpathologists with powerful ways of answering their research questions about systematic changes over time in individual behavior and about the occurrence and timing of life events. In the first section, we present a descriptive overview of each method by illustrating the types of research questions that each method can address, introducing the statistical models, and commenting on methods of model fitting, estimation, and interpretation. In the following three sections, we offer six concrete recommendations for developmental psychopathologists hoping to use these methods. First, we recommend that when designing studies, investigators should increase the number of waves of data they collect and consider the use of accelerated longitudinal designs. Second, we recommend that when selecting measurement strategies, investigators should strive to collect equatable data prospectively on all time-varying measures and should never standardize their measures before analysis. Third, we recommend that when specifying statistical models, researchers should consider a variety of alternative specifications for the time predictor and should test for interactions among predictors, particularly interactions between substantive predictors and time. Our goal throughout is to show that these methods are essential tools for answering questions about life-span developmental processes in both normal and atypical populations and that their proper use will help developmental psychopathologists and others illuminate how important contextual variables contribute to various pathways of development.

In a sample of 240 adolescents assessed annually in Grades 6 through 11, the developmental trajectories of their depressive symptoms were examined using latent factor growth modeling. Growth in mother-reported adolescent depressive symptoms was quadratic; growth in adolescent-reported symptoms was linear. In the model with gender and maternal depression, girls reported a greater increase in depressive symptoms over time than boys, and adolescents of mothers with histories of mood disorders had higher initial levels of depressive symptoms than offspring of never-depressed mothers. After gender and maternal depression were controlled, initial levels of negative attributions and stressors significantly predicted initial levels of adolescent- and mother-reported depressive symptoms. Attributional styles that were increasingly negative across time were associated with significantly higher initial levels (mother reported) and increasing growth (adolescent reported) of depressive symptoms. Reciprocal models in which development of depressive symptoms predicted the development of attributions and stress also were examined.

Prevention of obesity during childhood is critical for children in underserved populations, for whom obesity prevalence and risk of chronic disease are highest. OBJECTIVE To test the effect of a multicomponent behavioral intervention on child body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) growth trajectories over 36 months among preschool-age children at risk for obesity. DESIGN, SETTING, AND PARTICIPANTS A randomized clinical trial assigned 610 parent-child pairs from underserved communities in Nashville, Tennessee, to a 36-month intervention targeting health behaviors or a school-readiness control. Eligible children were between ages 3 and 5 years and at risk for obesity but not yet obese. Enrollment occurred from August 2012 to May 2014; 36-month follow-up occurred from October 2015 to June 2017. INTERVENTIONS The intervention (n = 304 pairs) was a 36-month family-based, community-centered program, consisting of 12 weekly skills-building sessions, followed by monthly coaching telephone calls for 9 months, and a 24-month sustainability phase providing cues to action. The control (n = 306 pairs) consisted of 6 school-readiness sessions delivered over the 36-month study, conducted by the Nashville Public Library. MAIN OUTCOMES AND MEASURES The primary outcome was child BMI trajectory over 36 months. Seven prespecified secondary outcomes included parent-reported child dietary intake and community center use. The Benjamini-Hochberg procedure corrected for multiple comparisons. RESULTS Participants were predominantly Latino (91.4%). At baseline, the mean (SD) child age was 4.3 (0.9) years; 51.9% were female. Household income was below $25 000 for 56.7% of families. Retention was 90.2%. At 36 months, the mean (SD) child BMI was 17.8 (2.2) in the intervention group and 17.8 (2.1) in the control group. No significant difference existed in the primary outcome of BMI trajectory over 36 months (P = .39). The intervention group children had a lower mean caloric intake (1227 kcal/d) compared with control group children (1323 kcal/d) (adjusted difference, −99.4 kcal [95% CI, −160.7 to −38.0]; corrected P = .003). Intervention group parents used community centers with their children more than control group parents (56.8% in intervention; 44.4% in control) (risk ratio, 1.29 [95% CI, 1.08 to 1.53]; corrected P = .006). CONCLUSIONS AND RELEVANCE A 36-month multicomponent behavioral intervention did not change BMI trajectory among underserved preschool-age children in Nashville, Tennessee, compared with a control program. Whether there would be effectiveness for other types of behavioral interventions or implementation in other cities would require further research.

Goals of the paper were to use item response theory (IRT) to assess the relation of depressive symptoms to the underlying dimension of depression and to demonstrate how IRT-based measurement strategies can yield more reliable data about depression severity than conventional symptom counts. Participants were 3403 clinic and nonclinic children and adolescents from 12 contributing samples, all of whom received the Kiddie Schedule of Affective Disorders and Schizophrenia for school-aged children. Results revealed that some symptoms reflected higher levels of depression and were more discriminating than others. Results further demonstrated that utilization of IRT-based information about symptom severity and discriminability in the measurement of depression severity can reduce measurement error and increase measurement fidelity.