Heterogeneity In Developmental Trajectories Research Articles

Population heterogeneity in developmental trajectories of internalising and externalising mental health symptoms in childhood: differential effects of parenting styles.

Multiple studies have connected parenting styles to children's internalising and externalising mental health symptoms (MHS). However, it is not clear how different parenting styles are jointly influencing the development of children's MHS over the course of childhood. Hence, the differential effects of parenting style on population heterogeneity in the joint developmental trajectories of children's internalising and externalising MHS were examined. A community sample of 7507 young children (ages 3, 5 and 9) from the Growing Up in Ireland cohort study was derived for further analyses. Parallel-process linear growth curve and latent growth mixture modelling were deployed. The results indicated that the linear growth model was a good approximation of children's MHS development (CFI = 0.99, RMSEA = 0.03). The growth mixture modelling revealed three classes of joint internalising and externalising MHS trajectories (VLMR = 92.51, p < 0.01; LMR = 682.19, p < 0.01; E = 0.86). The majority of the children (83.49%) belonged to a low-risk class best described by a decreasing trajectory of externalising symptoms and a flat low trajectory of internalising MHS. In total, 10.07% of the children belonged to a high-risk class described by high internalising and externalising MHS trajectories, whereas 6.43% of the children were probable members of a mild-risk class with slightly improving yet still elevated trajectories of MHS. Adjusting for socio-demographics, child and parental health, multinomial logistic regressions indicated that hostile parenting was a risk factor for membership in the high-risk (OR = 1.47, 95% CI 1.18-1.85) and mild-risk (OR = 1.57, 95% CI 1.21-2.04) classes. Consistent (OR = 0.75, 95% CI 0.62-0.90) parenting style was a protective factor only against membership in the mild-risk class. In short, the findings suggest that a non-negligible proportion of the child population is susceptible to being at high risk for developing MHS. Moreover, a smaller proportion of children was improving but still displayed high symptoms of MHS (mild-risk). Furthermore, hostile parenting style is a substantial risk factor for increments in child MHS, whereas consistent parenting can serve as a protective factor in cases of mild-risk. Evidence-based parent training/management programmes may be needed to reduce the risk of developing MHS.

Distinct Patterns of Cognitive Outcome in Young Children With Autism Spectrum Disorder Receiving the Early Start Denver Model.

Evidence-based, early intervention significantly improves developmental outcome in young children with autism. Nonetheless, there is high interindividual heterogeneity in developmental trajectories during the therapy. It is established that starting intervention as early as possible results in better developmental outcomes. But except for younger age at start, there is no clear consensus about behavioral characteristics that could provide a reliable individual prediction of a child's developmental outcome after receiving an early intervention. In this study, we analyze developmental trajectories of preschoolers with autism who received 2 years of intervention using the Early Start Denver Model (ESDM) approach in Geneva, Switzerland in an individual setting (n = 55, aged 28.7 ± 5.1 months with a range of 15–42). Our aim was to identify early predictors of response to intervention. We applied a cluster analysis to distinguish between 3 groups based on their cognitive level at intake, and rates of cognitive change over the course of intervention. The first group of children only had a mild cognitive delay at intake and nearly no cognitive delay by the end of intervention (Higher Cognitive at baseline: HC). The children in the two other groups all presented with severe cognitive delay at baseline. However, they had two very different patterns of response to intervention. The majority significantly improved developmental scores over the course of intervention (Optimal Responders: OptR) whereas a minority of children showed only modest improvement (Minimal Responders: MinR). Further analyses showed that children who ended up having an optimal 2-year intervention outcome (OptR) were characterized by higher adaptive functioning at baseline combined with rapid developmental improvement during the first 6 months of intervention. Inversely, less significant progress by the sixth month of intervention was associated with a less optimal response to treatment (MinR).

Explaining the Patterns of Bullying Victimization Trajectories: Assessing the Generality of Low Self-Control and Crime Opportunity Models to Bullying Victims.

This study hypothesizes that self-control and opportunity variables affect heterogeneity in developmental trajectories of bullying victimization. Using data from a follow-up study of 2,351 Korean adolescents, the study incorporates a latent class growth analysis approach to identify subgroups, each with a unique pattern of the trajectories. The model yields three subgroups of bullying victims: the early-onset and decreaser, the increaser and late-peak, and the normative groups. Results suggest that, compared to the normative group, the early-onset and decreasing group members manifest lower levels of self-control and engage in a greater range of delinquent behaviors. Also, the impact of low self-control on group membership was attenuated after controlling for those opportunity variables, indicating a partially mediating relationship. Social guardianship variables distinguished normative groups from other victim groups. Further, members of the increaser and late-peak group were more likely than the early-onset and decreaser group members to engage in cyber deviance over the long-term.

Developmental trajectory classes in psychological dysregulation predict later decision-making competence

Adolescence and emerging adulthood are developmental periods associated with increased risk taking, including alcohol and substance use and antisocial behaviors. Typical psychological growth from adolescence into early adulthood reflects increases in traits related to psychological regulation (e.g., greater emotional stability and less impulsivity), which are typically considered protective factors against risk behaviors. However, individuals may vary greatly in their development of these characteristics. This study examines the degree to which heterogeneity in developmental trajectories of psychological regulation are associated with later performance on decision-making skills battery. In this study, psychological regulation was assessed at age 10–12, with follow-up assessments at 14, 16, and 19 years. At age 19, we administered the Youth Decision-Making Competence (DMC; Parker & Fischhoff, 2005) measure. Correlational analyses revealed that lower psychological regulation, as early as age 10, was associated with lower DMC scores. A latent class growth mixture model yielded three distinct developmental trajectory classes of psychological dysregulation: (a) a Moderate-Stable group, a modal class that demonstrated stable and average regulative tendencies throughout adolescence, (b) a Low-Decreasing group, which demonstrated greater self-regulation throughout childhood, and a (c) High-Increasing group, which demonstrated low self-regulative tendencies (higher dysregulation) at age 10 that became increasingly dysregulated throughout adolescence. Individuals in the High-Increasing group demonstrated lower DMC performance than those in the Moderate-Stable and Low-Decreasing groups. Our findings also reinforce past work that indicates considerable individual differences in intra-individual change across adolescence, and that early patterns of psychological dysregulation development can impact later decision-making tendencies.

Development of Dynamic Functional Architecture during Early Infancy.

Uncovering the moment-to-moment dynamics of functional connectivity (FC) in the human brain during early development is crucial for understanding emerging complex cognitive functions and behaviors. To this end, this paper leveraged a longitudinal resting-state functional magnetic resonance imaging dataset from 51 typically developing infants and, for the first time, thoroughly investigated how the temporal variability of the FC architecture develops at the "global" (entire brain), "mesoscale" (functional system), and "local" (brain region) levels in the first 2 years of age. Our results revealed that, in such a pivotal stage, 1) the whole-brain FC dynamic is linearly increased; 2) the high-order functional systems tend to display increased FC dynamics for both within- and between-network connections, while the primary systems show the opposite trajectories; and 3) many frontal regions have increasing FC dynamics despite large heterogeneity in developmental trajectories and velocities. All these findings indicate that the brain is gradually reconfigured toward a more flexible, dynamic, and adaptive system with globally increasing but locally heterogeneous trajectories in the first 2 postnatal years, explaining why infants have rapidly developing high-order cognitive functions and complex behaviors.

Child Maltreatment, Fathers, and Adolescent Alcohol and Marijuana Use Trajectories

Background: Little is known about heterogeneity in developmental trajectories of alcohol and marijuana use among at-risk youth. Objective: This study aims to examine how child maltreatment and father structural factors at different stages in the life course are associated with different patterns of alcohol and marijuana use trajectories. Methods: A sample of youth (N = 903) were drawn from the Longitudinal Studies of Child Abuse and Neglect (LONGSCAN). Latent class growth analysis was employed to assess heterogeneity in patterns of adolescent alcohol and marijuana use. In addition, binary logistic regression analysis was performed to examine child maltreatment and father structural factors across different developmental stages as predictors of membership in the identified alcohol and marijuana use trajectory classes. Results: For both alcohol and marijuana use, two distinct latent classes were identified: stable no/low alcohol use (74%) vs. increasing alcohol use (26%); stable no/low marijuana use (85%) vs. increasing marijuana use (15%). Emotional abuse during early childhood and physical abuse during adolescence predicted membership in the increasing alcohol use and the increasing marijuana use classes. The presence of father in the home during early childhood was associated with lower likelihood of being in the increasing alcohol use class. Conclusions: Our findings highlight the importance of understanding the etiology of adolescent substance use through a developmental lens. Screening of exposure to child maltreatment across different developmental stages and interventions promoting father engagement during early childhood might help mitigate the risk of adolescent alcohol and marijuana use.

Children’s Temperament and Maternal Behavioral Control: Origins of Heterogeneity in Developmental Trajectories of Committed Compliance from Infancy to Age 3

Temperament and parental control are two important factors that influence the early development of children’s committed compliance. However, there is a need to comprehensively depict the developmental profiles of committed compliance across the first 3 years and further examine the impacts of these two factors on the profiles. Thus, the current study examined how 92 participants (39 boys) differed in their trajectories of committed compliance throughout toddlerhood and how these individual variances were underpinning of their temperament fearfulness and distractibility in infancy and maternal behavioral control from infancy to toddlerhood. According to children’s committed compliance observed in the clean-up task from 14 to 38 months, three groups with different developmental trajectories were identified: the high-level group, the low-level group, and the developmental group. Compared with the high-level group, the mothers reported that the low-level group displayed higher distractibility and lower fearfulness at 6 months. Maternal behavioral control was coded from two 5-min mother-child free plays at each age of 10, 14, 25 and 38 months. Results indicated that though the initial level of committed compliance of the two groups were similar at 14 months, the developmental group mothers had a lower mean intercept of behavioral control than the low-level group mothers at 10 months. Moreover, the developmental group mothers tended to decrease their use of behavioral control more slowly than the high-level group mothers. Limitations and implication for future research were discussed.

Power and Sample Size Computation for Wald Tests in Latent Class Models

Latent class (LC) analysis is used by social, behavioral, and medical science researchers among others as a tool for clustering (or unsupervised classification) with categorical response variables, for analyzing the agreement between multiple raters, for evaluating the sensitivity and specificity of diagnostic tests in the absence of a gold standard, and for modeling heterogeneity in developmental trajectories. Despite the increased popularity of LC analysis, little is known about statistical power and required sample size in LC modeling. This paper shows how to perform power and sample size computations in LC models using Wald tests for the parameters describing association between the categorical latent variable and the response variables. Moreover, the design factors affecting the statistical power of these Wald tests are studied. More specifically, we show how design factors which are specific for LC analysis, such as the number of classes, the class proportions, and the number of response variables, affect the information matrix. The proposed power computation approach is illustrated using realistic scenarios for the design factors. A simulation study conducted to assess the performance of the proposed power analysis procedure shows that it performs well in all situations one may encounter in practice.

Heterogeneity in Subcortical Brain Development: A Structural Magnetic Resonance Imaging Study of Brain Maturation from 8 to 30 Years

Brain development during late childhood and adolescence is characterized by decreases in gray matter (GM) and increases in white matter (WM) and ventricular volume. The dynamic nature of development across different structures is, however, not well understood, and the present magnetic resonance imaging study took advantage of a whole-brain segmentation approach to describe the developmental trajectories of 16 neuroanatomical volumes in the same sample of children, adolescents, and young adults (n = 171; range, 8-30 years). The cerebral cortex, cerebral WM, caudate, putamen, pallidum, accumbens area, hippocampus, amygdala, thalamus, brainstem, cerebellar GM, cerebellar WM, lateral ventricles, inferior lateral ventricles, third ventricle, and fourth ventricle were studied. The cerebral cortex was further analyzed in terms of lobar thickness and surface area. The results revealed substantial heterogeneity in developmental trajectories. GM decreased nonlinearly in the cerebral cortex and linearly in the caudate, putamen, pallidum, accumbens, and cerebellar GM, whereas the amygdala and hippocampus showed slight, nonlinear increases in GM volume. WM increased nonlinearly in both the cerebrum and cerebellum, with an earlier maturation in cerebellar WM. In addition to similarities in developmental trajectories within subcortical regions, our results also point to differences between structures within the same regions: among the basal ganglia, the caudate showed a weaker relationship with age than the putamen and pallidum, and in the cerebellum, differences were found between GM and WM development. These results emphasize the importance of studying a wide range of structural variables in the same sample, for a broader understanding of brain developmental principles.

Growth mixture modelling in developmental psychology: overview and demonstration of heterogeneity in developmental trajectories of adolescent antisocial behaviour

AbstractRecent advances in statistical techniques for longitudinal data analysis have provided increased capabilities for elucidating individual differences in trajectories of change in child behaviours and abilities. However, most techniques still assume that there is a single underlying distribution with respect to changes over time, about which children are normally distributed. If there are multiple subgroups of youth following distinct developmental trajectories with unique predictors, however, the results of these statistical techniques may provide an incomplete analysis of the data. A newer class of statistical techniques, latent growth mixture modelling, provides a robust framework for examining heterogeneity in patterns of development. This paper illustrates the use of latent growth mixture modelling for examining heterogeneity in developmental trajectories of adolescent antisocial behaviour. Copyright © 2006 John Wiley &amp; Sons, Ltd.

Integrating Person-Centered and Variable-Centered Analyses: Growth Mixture Modeling With Latent Trajectory Classes

Background: Many alcohol research questions require methods that take a person-centered approach because the interest is in finding heterogeneous groups of individuals, such as those who are susceptible to alcohol dependence and those who are not. A person-centered focus also is useful with longitudinal data to represent heterogeneity in developmental trajectories. In alcohol, drug, and mental health research the recognition of heterogeneity has led to theories of multiple developmental pathways. Methods: This paper gives a brief overview of new methods that integrate variable- and person-centered analyses. Methods discussed include latent class analysis, latent transition analysis, latent class growth analysis, growth mixture modeling, and general growth mixture modeling. These methods are presented in a general latent variable modeling framework that expands traditional latent variable modeling by including not only continuous latent variables but also categorical latent variables. Results: Four examples that use the National Longitudinal Survey of Youth (NLSY) data are presented to illustrate latent class analysis, latent class growth analysis, growth mixture modeling, and general growth mixture modeling. Latent class analysis of antisocial behavior found four classes. Four heavy drinking trajectory classes were found. The relationship between the latent classes and background variables and consequences was studied. Conclusions: Person-centered and variable-centered analyses typically have been seen as different activities that use different types of models and software. This paper gives a brief overview of new methods that integrate variable- and person-centered analyses. The general framework makes it possible to combine these models and to study new models serving as a stimulus for asking research questions that have both person- and variable-centered aspects.

Integrating Person‐Centered and Variable‐Centered Analyses: Growth Mixture Modeling With Latent Trajectory Classes

Many alcohol research questions require methods that take a person-centered approach because the interest is in finding heterogeneous groups of individuals, such as those who are susceptible to alcohol dependence and those who are not. A person-centered focus also is useful with longitudinal data to represent heterogeneity in developmental trajectories. In alcohol, drug, and mental health research the recognition of heterogeneity has led to theories of multiple developmental pathways. This paper gives a brief overview of new methods that integrate variable- and person-centered analyses. Methods discussed include latent class analysis, latent transition analysis, latent class growth analysis, growth mixture modeling, and general growth mixture modeling. These methods are presented in a general latent variable modeling framework that expands traditional latent variable modeling by including not only continuous latent variables but also categorical latent variables. Four examples that use the National Longitudinal Survey of Youth (NLSY) data are presented to illustrate latent class analysis, latent class growth analysis, growth mixture modeling, and general growth mixture modeling. Latent class analysis of antisocial behavior found four classes. Four heavy drinking trajectory classes were found. The relationship between the latent classes and background variables and consequences was studied. Person-centered and variable-centered analyses typically have been seen as different activities that use different types of models and software. This paper gives a brief overview of new methods that integrate variable- and person-centered analyses. The general framework makes it possible to combine these models and to study new models serving as a stimulus for asking research questions that have both person- and variable-centered aspects.