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Parental Stress, Parental Efficacy and Problem Behaviors in Children with Autism Spectrum Disorder: A Structural Equation Analysis

Friday, May 12, 2017: 12:00 PM-1:40 PM
Golden Gate Ballroom (Marriott Marquis Hotel)
K. A. Smith1,2, M. Siegel3, S. L. Santangelo4, R. Gabriels5, G. Righi6 and W. L. Cook7, (1)Maine Medical Center Research Institute, Portland, ME, (2)Tufts University School of Medicine, Boston, MA, (3)Maine Medical Center - Tufts School of Medicine - Spring Harbor Hospital, Westbrook, ME, (4)Maine Medical Center, Portland, ME, (5)Children's Hospital Colorado, Aurora, CO, (6)Alpert Medical School of Brown University, Rumford, RI, (7)Center for Excellence in the Neuroscience, University of New England, Biddeford, ME
Background:

Several studies have examined the role of parental stress on child outcomes, however there is little research examining positive parental characteristics, such as self-efficacy, that may reduce the impact of stress on the family. The direction of effects between parental stress, parental efficacy, and child problem behavior is also unclear.

Objectives:

To develop and test a longitudinal model including the latent variables (LVs) parental stress, parental efficacy, and child problem behavior and estimate their effects on each other over time (cross-lagged effects) using structural equation modeling (SEM).

Methods:

The study included 350 hospitalized children and adolescents with an Autism Diagnostic Observation Schedule-2 (ADOS-2) confirmed ASD diagnosis admitted to six specialized inpatient psychiatry units and prospectively enrolled in the Autism Inpatient Collection (AIC) study. Parents (N=323) were administered the Aberrant Behavior Checklist Irritability (ABC-I) subscale, Parent Stress Index Short Form (PSI-SF-4) and Difficult Behavior Self-efficacy Scale (DBSS) at admission, discharge, and 2-month follow-up. The hypothesized model was specified to have both measurement and path model components to make up the overall structural model composite. The measurement model contained three LVs – Parental Stress, Parental Efficacy, and Child Problem Behavior – which were measured using observed variables of each as indicators. The substantive part of the model involved the correlations and possible causal paths between the LVs (see Figure 1). Each LV was specified to be correlated with the other two LVs within a given time period, to predict itself at all later points in time (stability), and to be a predictor of the other two LVs measured at the immediately following time period (cross-lagged effects). Structural equation modeling was conducted using AMOS software version 20.

Results:

There were no significant differences between males and females on any of the demographic (age, ethnicity, race) or clinical variables (length of stay, non-verbal IQ, intellectual disability, expressive communication, adaptive behavior, or self-injurious behavior) (see Table 1). The majority of parents were mothers (84%), married (58%), average age of 42 years old. SEM results indicated the three latent variables were significantly correlated with each other at each respective time point (all p-values < .005) in a manner that supported the validity of each. Parental efficacy was negatively correlated to both parental stress and child problem behavior and parental stress was positively correlated with child problem behavior. The overall model fit the data well, χ² = 229.2, df = 138, p = 0.001; RMSEA = .04; CFI = 0.97. Two cross-lagged effects were found. Parental stress at admission predicted parent self-efficacy at discharge, β= -0.33, p=0.002, and parental stress at discharge predicted parental efficacy at follow up, β= -0.34, p=0.001. There were no other significant cross-lagged effects in this model.

Conclusions:

Results revealed a negative association between parental stress and parental efficacy which was consistent over time. Interventions to develop coping/behavioral management skills to reduce stress related disorders in parents may be important for mitigation of problem behaviors among children with ASD. Employing advanced statistical modeling methods (SEM) advances our knowledge in this field.