Psychometric Analysis of the Mental Health Crisis Assessment Scale in Youth with Autism Spectrum Disorder

Background: Population-based research has shown that three quarters of youth with autism spectrum disorder (ASD) suffer from a co-occurring psychiatric disorder (Simonoff et al., 2008) and data from a clinic-based sample indicated that over 90% of referred youth with ASD have 3 or more psychiatric disorders (Joshi et al., 2010). Despite this burden, outpatient mental health providers who are available to work with this this population are scarce (Brookman-Frazee et al., 2012). This gap in care, along with clinical experience, suggests youth with ASD are risk for experiencing a mental health crisis. However, no measures of mental health crisis exist for this population.

Objectives: To examine the reliability and validity of a novel measure, the Mental Health Crisis Assessment Scale (MCAS).

Methods: Data used for this study were gathered from the Interactive Autism Network (IAN), an online US based research registry. Prior studies have established the validity of the ASD diagnosis in IAN (Daniels et al., 2011; Lee et al., 2010). For this study, parents had to report that their child was between 3-24 years of age and met the cutoff on the Social Communication Questionnaire (Rutter et al., 2003). A mental health crisis was defined as “an acute disturbance of though, mood, or behavior that requires immediate intervention” (APA, 2002). Mental health crisis was measured by the MCAS, a 28-item parent reported crisis measure made up of three sections, including a 14-item list of mental health symptoms, 7 items measuring acuity of symptoms, and 5 items assessing parental management of symptoms. Data were collected in three waves. The first wave (n = 121) were gathered to establish criterion validity by examining the association between the MCAS and a custom, semi-structured clinician interview. Construct validity was established through exploratory factor analysis (EFA; n = 229), in the first two waves of data collection, and independently corroborated through confirmatory factor analysis (CFA; n = 352) in the third wave of data collection. Convergent validity was determined by assessing the association between the MCAS and family distress (Weiss & Lunsky, 2010), parental stress (Macomber et al., 2006), and use of emergency psychiatric services in the third wave of data collection.

Results: Results from the EFA and parallel analysis identified a two-factor structure (Factor 1: behavioral acuity and Factor 2: behavioral management) of the MCAS. The CFA confirmed that the two factor model fit the third wave of data well (RMSEA = 0.10, CFI = 0.96, TLI = 0.95). The measure also demonstrated strong internal consistency values across all study waves (α ranged from 0.80-0.90). Results from the clinician interview analyses suggested a strong association between the MCAS and clinician opinion (ROC = 0.85). Lastly, positive associations were found between the MCAS and family distress (r = 0.57), parental stress (r = 0.48), and use of emergency psychiatric services (r = 0.67; all p<.05).

Conclusions: Results from this study support the MCAS as a psychometrically robust tool that can characterize a unique, important, and heavily understudied dimension of mental health among youth with ASD.