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Latent Class Analysis Reveals Distinct Groups Based on Executive Function and Socioemotional Traits, Developmental Conditions, and Stuttering: A Population Study

Child Psychiatry & Human Development volume 53, pages 684–700 (2022)Cite this article

Abstract

A growing body of research has reported associations between weaker Executive Functions (EF), the set capacities that are needed to manage and allocate one’s cognitive resources during cognitively challenging activities and various neurodevelopmental conditions, including stuttering. The majority of this research has been based on variable-centered approaches, which have the potential to obscure within-population heterogeneity. Person-centered analyses are essential to understanding multifactorial disorders where relationships between indicators have been elusive, such as stuttering. The current study addressed gaps in the literature by using latent class analysis (LCA), a person-centered approach, to identify homogenous subgroups within the National Health Interview Survey (2004–2018) publicly available data set. Using this exploratory approach, we examined the hypothesis that there exist distinct classes (or subgroups) of children based on parent reports of EF, Socioemotional (SE) traits, developmental atypicality, and stuttering. Our analyses revealed distinct subgroups with substantially different likelihoods of parent-reported stuttering behaviors and developmental atypicality. For children with both EF and SE difficulties, the likelihood of parental report of stuttering and atypical development was even higher, in fact this likelihood (of stuttering and not-typically developing) was highest among all subgroups. In contrast, children without difficulties were the least likely to be reported with stuttering or not-typically developing. Our findings are consistent with theoretical frameworks for stuttering, which cite EF as a crucial component in the disorder. Additionally, our findings suggest within-population heterogeneity among children with EF difficulties and, specifically, EF and SE heterogeneity among children who stutter.

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Notes

  1. Preliminary analyses suggested that participant’s sex was minimally associated with parent report of stuttering (rSpearman = -0.054). In addition, LCAs with participant sex included as an indicator evidenced convergence issues and fit more poorly than the corresponding LCAs without sex (see Appendix A). Participant’s sex was therefore not included in our final LCAs.

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Authors and Affiliations

  1. College of Education, University of South Florida, 4202 East Fowler Ave., EDU 302H, Tampa, FL, 33620, USA

    Sara Ashley Smith

  2. Department of Communication Sciences and Disorders, Georgia State University, 30 Pryor St. SW, Atlanta, GA, 30303, USA

    Ai Leen Choo

  3. Rightpath Research and Innovation Center, University of South Florida, 13301 Bruce B. Downs Blvd., MHC 1721, Tampa, FL, 33602, USA

    Matthew E. Foster

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Secondary data analysis of publicly available data set, the National Health Interview Survey (2004–2018).

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Appendix A

Appendix A

See Table 5 and 6.

Table 5 Model fit statistics for latent class solution with participant’s sex as an indicator
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Table 6 Correlations among latent class indicators, group, and developmental status
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Smith, S.A., Choo, A.L. & Foster, M.E. Latent Class Analysis Reveals Distinct Groups Based on Executive Function and Socioemotional Traits, Developmental Conditions, and Stuttering: A Population Study. Child Psychiatry Hum Dev 53, 684–700 (2022). https://doi.org/10.1007/s10578-021-01160-3

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Keywords

  • Latent profile analysis
  • Children
  • Executive function
  • Emotion regulation
  • Stuttering