24937
Birth Order and Sibling Status Impacts Psychometrics of M-CHAT-R with Follow-up (M-CHAT-R/F)

Saturday, May 13, 2017: 12:00 PM-1:40 PM
Golden Gate Ballroom (Marriott Marquis Hotel)
K. R. Bradbury1, D. L. Robins2, M. Barton1, W. L. Stone3, Z. Warren4 and D. A. Fein1, (1)Psychological Sciences, University of Connecticut, Storrs, CT, (2)Drexel University A.J. Drexel Autism Institute, Philadelphia, PA, (3)Psychology, University of Washington, Seattle, WA, (4)Vanderbilt University, Nashville, TN
Background:

The M-CHAT-R/F is a parent-completed, screening instrument to detect autism spectrum disorder (ASD) in toddlers. When a child screens positive on the initial items, the structured follow-up interview confirms responses and reduces false positives. The presence of older siblings as a comparison can impact parent’s perception of development in later-born children. Previous research suggests that parents report developmental concerns about their first-born child significantly later than concerns about later-born children. Furthermore, concerns for later-born children are reported even earlier when there are older ASD-affected siblings. The current study proposes to explore how birth order (first-born vs. later-born) and sibling status (ASD-Sibs vs. NonASD-Sibs) affect performance on the M-CHAT-R/F.

Objectives:

To compare M-CHAT-R/F performance in first-born children (No-Sibs) and later-born children with an older sibling with ASD (ASD-Sibs) or an older sibling without ASD (NonASD-Sibs).

Methods:

Toddlers (n=321; M = 21.4 mos, SD = 3.6) were evaluated after screening positive on the 2-stage M-CHAT-R/F. Diagnostic outcome (ASD vs. non-ASD) was compared across groups using chi square. In a subset of children who received an ASD diagnosis (n=126), total scores and item performance at initial and follow-up screen were compared for first-born children (n=50) and two groups of later-born children (ASD-Sibs, n=30; NonASD-Sibs, n = 46). ASD severity, measured by CARS total scores and ADOS severity scores, was compared across groups using one-way ANOVA.

Results:

Samples did not differ on most demographic variables, although the ASD-Sibs group included fewer minority children than the other groups. Findings held when the confound of race was removed from the model. Children in the ASD-Sibs group were more likely to be diagnosed with ASD (PPVASD-Sibs = .64; PPVNo-Sibs= .55; PPVNonASD-Sibs = .35, p = .001). In the subset of children with ASD, initial screener scores did not differ between groups (F(2,123) = 1.396, p = .251); however, scores after follow-up differed significantly (F(2,123) = 3.684, p = .028). Post-hoc comparisons using the Tukey HSD test indicated that the No-Sibs group (M=4.47, SD=2.89) scored significantly lower after follow-up compared to the ASD-Sibs group (M=6.73, SD=3.01), whereas the NonASD-Sibs group’s (M=5.8, SD=3.72) scores did not differ from either group. Failed items that were more likely to change to pass with further questioning represented subtle social developmental milestones (e.g., showing to share, following gaze, social referencing) as determined by chi square (p’s<.02). No differences were observed between groups on CARS scores and ADOS calibrated severity scores (p’s >.5).

Conclusions:

Birth order may impact parents’ responses on screening measures, such as the M-CHAT-R, particularly when an ASD-affected child is in the household. Parents of first-born children are more likely to change their responses at follow-up, suggesting a decreased awareness of subtle developmental milestones, especially compared to parents of ASD-Sibs. Diminished change between screener and follow-up for the ASD-Sibs group may suggest accurate reporting, although hypervigilance might also play a role. As ASD severity was comparable across groups, these findings are likely representative of differences in parent experience as opposed to differences in ASD symptomatology.