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Modified Checklist for Autism in Toddlers, Revised with Follow-Up

The Modified Checklist for Autism in Toddlers, Revised with Follow-Up (MCHAT-R/F; Robbins, Fein, & Barton, 2009), designed to screen for autism in toddlers from 16 to 30 months, was developed for use during well-child checkups.

Available from M-CHAT

Overview

The Modified Checklist for Autism in Toddlers, Revised with Follow-Up (MCHAT-R/F; Robbins, Fein, & Barton, 2009), was revised slightly in 2018 to reflect minor corrections. This widely-used, free instrument was designed to screen for autism in toddlers from 16 to 30 months, and it was developed primarily by pediatricians and other primary care providers for use during well-child checkups. It is a two-stage parent-report screening tool to assess risk of autism spectrum disorder (ASD). The first step is a 20-item yes/no parent/caregiver questionnaire that yields Low, Medium, or High Risk classifications. The M-CHAT was designed to maximize sensitivity (i.e., detect as many cases of ASD as possible), which means that the false positive rate is high in that not all children who score at-risk will be diagnosed with ASD. For children at medium risk or above, the second step of the process is a follow-up questionnaire. The Follow-Up questions (M-CHAT-R/F) consists of 20 pass/fail items used to gather further information for classification into High Risk or Low Risk categories. Notably, even with the Follow-Up, a significant number of children who screen positive on the M-CHAT-R will not be diagnosed with ASD but these children are at high risk for other developmental disorders or delays and warrant further evaluation. The authors note that it is freely available but must be used in its entirety and with no modifications. The M-CHAT-R can be scored in less than two minutes.

Summary

Age: 16 to 30 months

Time to Administer: 10-15 minutes

Method of Administration: A two-stage autism screening tool:
1. 20-item yes/no parent/caregiver questionnaire; yields Low, Medium, or High Risk classifications
2. 20-item follow-up questionnaire given for a child found to be at medium risk to gather further information for classification into High Risk or Low Risk categories.

Subscales: N/A
Screening/Diagnosis: S

Autism Related Research

Kim et al. (2016)

Age Range: 2 years, 10 years

Sample Size: 827

Topics Addressed:

Validity of M-CHAT in children born very preterm

Outcome:Kim et al. (2016)

Among 2 year-olds/followed-up at 10-years-old, the likelihood ratio for a positive M-CHAT was 3.3 (95% CI, 2.4-4.4). Hearing and vision impairment increased false positives and negatives. High false-positive rates were also associated with lower SES, motor and cognitive impairments, and emotional/behavioral dysregulation at age 2.

Robbins, Casagrande, Barton, Chen, Dumont-Mathieu & Fein (2014)

Age Range: 16-30.95 months

Sample Size: 15.612

Topics Addressed:

Revision of the M-CHAT to reduce initial positive screens and need for follow-up while maintaining high sensitivity

Outcome:Robbins, Casagrande, Barton, Chen, Dumont-Mathieu & Fein (2014)

The study validated the M-CHAT-R/F. Analyses indicated that optimal scoring relies only on total, rather than alternate, scoring. Children who score in the low-risk range (93% of cases) are not in need of the M-CHAT-R/F or additional evaluation unless there are other data to suggest ASD risk. Children in the medium-risk range (6% of cases) require administration of the M-CHAT-R/F. Approximately one-thd of children continue to show ASD risk and require evaluation referral. Children who score in the high-risk range (1% of cases) on the M-CHAT-R may bypass the follow-up and be referred immediately for evaluation and possible early intervention. Children who screened positive on the M-CHAT-R/F were 114 times more likely to receive an ASD diagnosis than those who screened negative. 94.6% of those evaluated for ASD risk on the 2-stage M-CHAT-R/F showed developmental delay or concern warranting referrals.

Conclusion: The M-CHAT-R/F is an effective tool to screen for ASD in low-risk pediatric samples. Implementation is facilitated by simplified scoring and specific algorithms based on outcome.