Paternal autonomy restriction,neighborhood safety,and child anxiety trajectory in community youth

Intrusive parenting, primarily examined among middle to upper-middle class mothers, has been positively associated with the presence and severity of anxiety in children. This study employed cross-sectional linear regression and longitudinal latent growth curve analyses to evaluate the main and interactive effects of early childhood paternal autonomy restriction (AR) and neighborhood safety (NS) on the trajectory of child anxiety in a sample of 596 community children and fathers from the NICHD SECYD. Longitudinal analyses revealed that greater paternal AR at age 6 was actually associated with greater decreases in child anxiety in later childhood. Cross-sectional analyses revealed main effects for NS across childhood, and interactive effects of paternal AR and NS that were present only in early childhood, whereby children living in safer neighborhoods demonstrated increased anxiety when experiencing lower levels of paternal AR. Findings further clarify for whom and when paternal AR impacts child anxiety in community youth.     

Latent growth curve analysis with dichotomous items: Comparing four approaches

A Monte Carlo study was used to compare four approaches to growth curve analysis of subjects assessed repeatedly with the same set of dichotomous items: A two‐step procedure first estimating latent trait measures using MULTILOG and then using a hierarchical linear model to examine the changing trajectories with the estimated abilities as the outcome variable; a structural equation model using modified weighted least squares (WLSMV) estimation; and two approaches in the framework of multilevel item response models, including a hierarchical generalized linear model using Laplace estimation, and Bayesian analysis using Markov chain Monte Carlo (MCMC). These four methods have similar power in detecting the average linear slope across time. MCMC and Laplace estimates perform relatively better on the bias of the average linear slope and corresponding standard error, as well as the item location parameters. For the variance of the random intercept, and the covariance between the random intercept and slope, all estimates are biased in most conditions. For the random slope variance, only Laplace estimates are unbiased when there are eight time points.     

Specifying Ability Growth Models Using a Multidimensional Item Response Model for Repeated Measures Categorical Ordinal Item Response Data

When categorical ordinal item response data are collected over multiple timepoints from a repeated measures design, an item response theory (IRT) modeling approach whose unit of analysis is an item response is suitable. This study proposes a few longitudinal IRT models and illustrates how a popular compensatory multidimensional IRT model can be utilized to formulate such longitudinal IRT models, which permits an investigation of ability growth at both individual and population levels. The equivalence of an existing multidimensional IRT model and those longitudinal IRT models is also elaborated so that one can make use of an existing multidimensional IRT model to implement the longitudinal IRT models.     

重大突发事件下价值观与幸福感的变化:基于潜变量增长和交叉滞后模型

对1495名被试的价值观与幸福感进行了三个时间点的追踪研究,通过潜变量增长模型和交叉滞后回归模型,考察重大突发事件下价值观与幸福感的变化及其相互作用。结果发现:(1)T1到T3民众的自我超越价值观显著下降,保守和开放价值观显著上升;(2)T2到T3民众的幸福感显著下降;(3)T2自我超越价值观正向预测T3幸福感,T2自我增强价值观负向预测T3幸福感;(4)T2幸福感正向预测T3自我超越和保守价值观,负向预测T3自我增强和开放价值观。该结果为今后重大突发事件下的价值观引导提供了实证依据。     

正念与大学生智慧推理的关系：个人成长主动性的部分中介作用

为了考察正念、个人成长主动性(PGI)与智慧推理之间的关系,采用五因素正念量表、个人成长主动性量表与智慧推理量表对242名18-27岁成年早期的大学生进行调查,探讨正念对智慧推理的影响,并检验个人成长主动性的中介效应模型。结果发现：（1）正念对智慧推理水平具有显著的正向影响;（2）个人成长主动性在正念对智慧推理的影响中发挥部分中介作用。     

From “blessing in disguise” to “what do I do now?”: How Canadian Olympic and Paralympic hopefuls perceived,experienced, and coped with the postponement of the Tokyo 2020 Games

The purpose of this study was to explore how Canadian elite athletes perceived, experienced, and coped with the Covid-19 pandemic and postponement of the Tokyo 2020 Games. We conducted semi-structured interviews with seven Paralympic and 14 Olympic hopefuls (n = 21). Data were analyzed using reflexive thematic analysis. Due to halting of training and competition and inabilities to live out the coveted performance narrative emphasizing winning above all, participants experienced complex emotional webs and questioned their purpose as athletes, which catalyzed psychological disruption. They coped by reframing the postponement as an opportunity for growth and risk-free chance to challenge the performance narrative through the embodiment of a reclaimed time narrative and associated attempts to diversify identities in non-sport domains. The findings highlight how the sociocultural environment impacts athletes’ agency to self-regulate in response to unexpected and dynamic athletic career-related events, thereby prompting the negotiation of concomitant psychological (dis)stress and growth.     

Implementing continuous non-normal skewed distributions in latent growth mixture modeling: An assessment of specification errors and class enumeration

Abstract

Recent advances have allowed for modeling mixture components within latent growth modeling using robust, skewed mixture distributions rather than normal distributions. This feature adds flexibility in handling non-normality in longitudinal data, through manifest or latent variables, by directly modeling skewed or heavy-tailed latent classes rather than assuming a mixture of normal distributions. The aim of this study was to assess through simulation the potential under- or over-extraction of latent classes in a growth mixture model when underlying data follow either normal, skewed-normal, or skewed-t distributions. In order to assess this, we implement skewed-t, skewed-normal, and conventional normal (i.e., not skewed) forms of the growth mixture model. The skewed-t and skewed-normal versions of this model have only recently been implemented, and relatively little is known about their performance. Model comparison, fit, and classification of correctly specified and mis-specified models were assessed through various indices. Findings suggest that the accuracy of model comparison and fit measures are dependent on the type of (mis)specification, as well as the amount of class separation between the latent classes. A secondary simulation exposed computation and accuracy difficulties under some skewed modeling contexts. Implications of findings, recommendations for applied researchers, and future directions are discussed; a motivating example is presented using education data.     

Beyond Resilience: Glimpses into Women’s Posttraumatic Growth after Experiencing Intimate Partner Violence

Abstract

Little focus is given to the pathways victims of intimate partner violence (IPV) use to move toward posttraumatic growth. A sample of 32 female participants was recruited through advertising in domestic violence shelters. Women were interviewed about their experiences with four main themes emerging from women’s narratives related to posttraumatic growth: deliberateness of action, ending the cycle for the children, a changed perspective on life, and alternative perceptions of social support. Opportunities for professions working with this population in a number of various of settings is presented to promote long-term changes for women affected by IPV.