Jeffrey D. Long

Developmental cascades : Linking academic achievement and externalizing and internalizing symptoms over 20 years

A developmental cascade model linking competence and symptoms was tested in a study of a normative, urban school sample of 205 children (initially 8 to 12 years old). Internalizing and externalizing symptoms and academic competence were assessed by multiple methods at the study outset and after 7, 10, and 20 years. A series of nested cascade models was tested through structural equation modeling. The final model indicated 2 hypothesized cascade effects: Externalizing problems evident in childhood appeared to undermine academic competence by adolescence, which subsequently showed a negative effect on internalizing problems in young adulthood. A significant exploratory effect was consistent with internalizing symptoms containing or lowering the net risk for externalizing problems under some conditions. These 3 cascade effects did not differ by gender and were not attributable to effects of IQ, parenting quality, or socioeconomic differences. Implications are discussed for developmental models of cascades, progressions, and preventive interventions.

Developmental changes in hypothalamus–pituitary–adrenal activity over the transition to adolescence: Normative changes and associations with puberty

Home baseline and laboratory stressor (Trier Social Stress Test for Children) measures of salivary cortisol were obtained from 82 participants (40 girls) aged 9, 11, 13, and 15 years. Measures of pubertal development, self-reported stress, parent reports of child depressive symptoms and fearful temperament, and cardiac measures of sympathetic and parasympathetic activity were also obtained. Significant increases in the home cortisol baselines were found with age and pubertal development. Cortisol stress reactivity differed by age group with 11-year-olds and 13-year-old boys showing blunted reactivity and 9-year-olds, 13-year-old girls, and 15-year-olds showing significant cortisol reactions. Cortisol reactivity correlated marginally with sexual maturation. Measures of sympathetic activity revealed increased sympathetic modulation with age. Higher sympathetic tone was associated with more fearful temperament, whereas greater cortisol reactivity was associated with more anxious and depressed symptoms for girls. The importance of these findings for the hypothesis that puberty-associated increases in hypothalamic-pituitary-adrenal axis activity heightens the risk of psychopathology is discussed.

Resources and resilience in the transition to adulthood: continuity and change.

Patterns of continuity and change in competence and resilience over the transition to adulthood were examined in relation to adversity and psychosocial resources, with a focus on adaptive resources that may be particularly important for this transition. Variable-focused and person-focused analyses drew on data from the Project Competence longitudinal study of a school cohort followed over 20 years from childhood through emerging adulthood (EA) into the young adulthood (YA) years with excellent retention (90%). Success in age-salient and emerging developmental tasks from EA to YA was examined in a sample of 173 of the original participants with complete data on adversity, competence, and key resources. Regressions and extreme-group analyses indicated striking continuity in competence and resilience, yet also predictable change. Success in developmental tasks in EA and YA was related to core resources originating in childhood (IQ, parenting quality, socioeconomic status) and also to a set of EA adaptive resources that included planfulness/future motivation, autonomy, adult support, and coping skills. EA adaptive resources had unique predictive significance for successful transitions to adulthood, both overall and for the small group of individuals whose pattern of adaptation changed dramatically from maladaptive to resilient over the transition. Results are discussed in relation to the possibility that the transition to adulthood is a window of opportunity for changing the life course.

The Interplay of Social Competence and Psychopathology Over 20 Years: Testing Transactional and Cascade Models

Associations among internalizing, externalizing, and social competence were examined in a longitudinal cohort (N = 205) of 8- to 12-year-old children reassessed after 7, 10, and 20 years. Theoretically informed nested structural equation models tested interconnections among broad multi-informant constructs across four developmental periods. Follow-up analyses examined gender invariance, measurement and age effects, and putative common causes. Key model comparisons indicated robust negative paths from social competence to internalizing problems from childhood to adolescence and from emerging adulthood to young adulthood. Social competence and externalizing problems showed strong initial associations in childhood but no longitudinal cross-domain paths. Using a developmental psychopathology framework, results are discussed in relation to cascade and transactional effects and the interplay between competence and symptoms over time.

Curriculum-Based Measurement Oral Reading as an indicator of reading achievement: A meta-analysis of the correlational evidence

This meta-analysis summarized the correlational evidence of the association between the CBM Oral Reading measure (R-CBM) and other standardized measures of reading achievement for students in grades 1-6. Potential moderating variables were also examined (source of criterion test, administration format, grade level, length of time, and type of reading subtest score). Results indicated a significant, strong overall correlation among R-CBM and other standardized tests of reading achievement and differences in correlations as a function of source of test, administration format, and reading subtest type. No differences in the magnitude of correlations were found across grade levels. In addition, there was minimal evidence of publication bias. Results are discussed in terms of existing literature and directions for future research.

The Assessment of Newborn Iron Stores at Birth: A Review of the Literature and Standards for Ferritin Concentrations

Background: Serum ferritin measurements are used in clinical populations to estimate total body iron stores and the risk of subsequent iron deficiency or overload. The lack of normative newborn serum ferritin concentration data between 23 and 41 weeks has led to difficulty in establishing the incidence and degree of abnormal iron status in the neonatal period. Objectives: The primary objective of this review was to summarize the maternal and gestational factors that determine ferritin concentrations in full-term and pre-term newborn infants and to generate comprehensive reference values. The secondary objective was to assess serum ferritin concentrations in newborn infants at risk for abnormal fetal iron metabolism, including maternal diabetes mellitus, intrauterine growth restriction and maternal smoking during pregnancy. Methods: Serum ferritin and gestational age data at birth from 457 low-risk pre-term and term infants of 23–41 weeks gestation obtained from 35 published studies reviewed from a period of 25 years and from recently collected data from our centers were assessed by regression analysis. Slopes and intercepts of the high-risk groups were compared with the standard curve. Results: Umbilical cord serum ferritin concentrations increased with advancing gestational age, from a mean of 63 µg/l at 23 weeks to 171 µg/l at 41 weeks gestation (p < 0.001). The infants of diabetic mothers had a lower intercept than the control infants (p < 0.001). Conclusions: Iron deficiency and overload have been implicated in neurodevelopmental impairments. Normative cord serum ferritin data may permit a more precise assessment of infants who are at risk for abnormal iron status at birth.

Correlates of levels and patterns of positive life changes following sexual assault.

This study builds on previous work suggesting that many survivors report positive life changes soon after a sexual assault and that those who retain those changes over time report the least distress 1 year post-assault (P. Frazier, A. Conlon, & T. Glaser, 2001). The purposes of this study were to assess correlates of early reports of positive life changes and individual trajectories of self-reported positive changes over time among female sexual assault survivors (n = 171) using hierarchical linear modeling. The factors most related to reporting positive life change soon after the assault were social support, approach and religious coping, and perceived control over the recovery process. Increases in these factors also were associated with increases in self-reported positive life changes over time. The relations between social support and positive change also were mediated by coping strategies and control appraisals, particularly perceived control over the recovery process.

Measuring Interpersonal Callousness in Boys From Childhood to Adolescence: An Examination of Longitudinal Invariance and Temporal Stability

Studies show interpersonal callousness (IC) plays an important role in understanding persistent antisocial behaviors; however, it remains unclear whether IC is a unidimensional construct, represented by invariant behavioral indexes and stable across different developmental periods. This study explores the structure and stability of IC using parent and teacher reports of IC behaviors in a cohort of 506 inner-city boys assessed annually from ages 8 to 16. Results support the unidimensionality of the IC construct from childhood to adolescence and reveal longitudinal invariance between ages 8 to 11 and 12 to 16 in the case of parent report and from age 11 to 16 in the case of teacher report. Findings reveal significant stability of IC across 9 years of assessment. This study emphasizes the importance of testing the longitudinal invariance of constructs that span multiple developmental periods to promote a more unambiguous understanding of developmental stability and change.

Goodness-of-Fit Testing for Latent Class Models

Latent class models with sparse contingency tables can present problems for model comparison and selection, because under these conditions the distributions of goodness-of-fit indices are often unknown. This causes inaccuracies both in hypothesis testing and in model comparisons based on normed indices. In order to assess the extent of this problem, we carried out a simulation investigating the distributions of the likelihood ratio statistic G(2), the Pearson statistic ⊃(2), and a new goodness-of-fit index suggested by Read and Cressie (1988). There were substantial deviations between the expectation of the chi-squared distribution and the means of the G(2) and Read and Cressie distributions. In general, the mean of the distribution of a statistic was closer to the expectation of the chi-squared distribution when the average cell expectation was large, there were fewer indicator items, and the latent class measurement parameters were less extreme. It was found that the mean of the χ(2) distribution is generally closer to the expectation of the chi-squared distribution than are the means of the other two indices we examined, but the standard deviation of the χ(2) distribution is considerably larger than that of the other two indices and larger than the standard deviation of the chi-squared distribution. We argue that a possible solution is to forgo reliance on theoretical distributions for expectations and quantiles of goodness-of-fit statistics. Instead, Monte Carlo sampling (Noreen, 1989) can be used to arrive at an empirical central or noncentral distribution.

Deep learning for neuroimaging: a validation study

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimagers toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data.