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Modeling Family Dynamics in Children with Fragile X Syndrome

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Abstract

Few studies have examined the impact of children with genetic disorders and their unaffected siblings on family functioning. In this study, the reciprocal causal links between problem behaviors and maternal distress were investigated in 150 families containing a child with fragile X syndrome (FXS) and an unaffected sibling. Both children's behavior problems appeared to have strong, direct effects on maternal distress, but maternal distress did not appear to have any reciprocal causal effects on either child's behavior problems. Surprisingly, there were no significant differences in the effects of the two children's behavior problems on maternal distress. These data suggest that the problem behaviors of children with FXS, as well as their unaffected siblings, can have a substantial and additive impact on maternal depression and anxiety. Future research efforts should employ longitudinal research designs to confirm these findings.

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Notes

  1. Some children with FXS also had siblings with FXS, although diagnosis was not always confirmed.

  2. We also performed the analyses treating the lowest scores as missing data. The results of these analyses were very similar.

  3. The correlation between the Conflict subscale of the FES and the CBC-EXT scale of the CBC was 0.23 for children with FXS and 0.46 for unaffected siblings.

  4. This method can provide consistent parameter estimates in the presence of missing data, even when the data are not missing completely at random. Three alternative methods of estimating models with missing data include mean substitution, listwise deletion, and pairwise deletion. These methods are less efficient and provide consistent estimates only under the stronger assumption that any missing data are missing completely at random.

  5. Some investigators prefer to call these terms “Other Causes,” since they contain all the unexplained variance of each observed variable, including unknown systematic causes as well as random measurement errors.

  6. One cannot assume that this is actually a method factor resulting from maternal bias. It could also represent the fact that the two children's behaviors at home may be more highly correlated than their behaviors at school. This would not be surprising, since the home environment as defined here is identical, while the two school environments for the children will be significantly different. This “method factor” could just as easily be represented as a correlated error term. Statistically, this would be an alternative but equivalent representation of the same phenomenon.

  7. In a tau-equivalent factor, the regression coefficient for all the indicators are equal, indicating that they all contain the same amount of factor variance. In a parallel factor, all the error variances are also equal, indicating they all have identical r-square values. In a super parallel factor, the regression coefficients, error variances, and intercepts for all the indicators are equal.

  8. One could argue that the behavior factors might conceivably have causal effects on the IQ factors. In fact, some investigators have proposed such a causal linkage. We tested this possibility in a non-recursive model and found that it was grossly inconsistent with the data, and could be rejected.

  9. This test was performed by subtracting the χ 2 and df of the measurement model from the χ 2 and df of the structural model.

  10. Five females and 15 males with FXS scored in the “autism” range on the Autism Behavior Checklist (Krug, Arick, & Almond, 1993) and these children had significantly elevated scores on the CBC-EXT and TRF-EXT. Inclusion of autism status in the model, however, indicated that children who showed symptoms of autism did not directly influence mothers' level of anxiety or depressive symptoms.

  11. We measured FMR Protein levels in these children, and plan to report those results separately.

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Acknowledgements

The authors would like to thank David Hessl, Jennifer Dyer-Friedman, Jacob Wisbeck, Bronwyn Glaser, Donna Mumme, and Cindy Johnston for their participation in this project. This research was supported by NIH grants MH50047 and MH01142.

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Authors and Affiliations

  1. Department of Psychiatry and Behavioral Sciences, Stanford University, School of Medicine, 401 Quarry Road, Stanford, CA, 94305-5719, USA

    Scott S. Hall, David D. Burns & Allan L. Reiss

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  1. Scott S. Hall
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Correspondence to Scott S. Hall.

 

 

Appendix 1 Variance-covariance matrix
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Hall, S.S., Burns, D.D. & Reiss, A.L. Modeling Family Dynamics in Children with Fragile X Syndrome. J Abnorm Child Psychol 35, 29–42 (2007). https://doi.org/10.1007/s10802-006-9081-4

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