Accurate Autism Screening at the 18-Month Well-Child Visit Requires Different Strategies than at 24 Months

Sturner, Raymond A.; Howard, Barbara J.; Bergmann, Paul; Morrel, Tanya M.; Landa, Rebecca; Walton, Kejuana; Marks, David H.

doi:10.1007/s10803-017-3231-0

Cited by 26 publications

(22 citation statements)

References 35 publications

(52 reference statements)

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“…M-CHAT authors found lower PPV in younger low risk toddlers (0.28) compared to older ones (0.61) even using the recommended follow-up interview (M-CHAT/F) (Pandey et al, 2008) and recent studies have reported similar findings (Sturner et al, 2013). Another study by the M-CHAT authors suggested that younger toddlers may have a lower PPV, though that difference was not statistically significant (Robins et al, 2014).…”

Section: Introductionmentioning

confidence: 79%

“…This finding adds to the impression that higher item failures in younger toddlers are: more likely to be due to developmental immaturity than to ASD symptoms than for older toddlers; potential reasons that the M-CHAT is a more definitive screen for older toddlers than younger ones, and that screening accuracy is lower in the younger group in some studies (Pandey et. al., 2008; Sturner et. al., 2013).…”

Section: Discussionmentioning

confidence: 99%

“…Data was collected between September 2009 and February 2014. The screenings were split into two age groups: younger (<20 months; n = 33,908) and older (20+ months; n=39,656) toddlers using an age cut-off of 20 months, which was found in a previous study to be the point at which age became an important predictor variable to autism diagnosis (Sturner et al, 2013). Figure 1 presents the sample selection procedure.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Comparison of Autism Screening in Younger and Older Toddlers

Sturner

Howard

Bergmann

et al. 2017

J Autism Dev Disord

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This study examined the effect of age at completion of an autism screening test on item failure rates contrasting older (>20 months) with younger (<20 months) toddlers in a community primary care sample of 73,564 children. Items related to social development were categorized into one of three age sets per criteria from Inada, Kamio & Koyama (2010). Younger toddlers produced higher rates of item failure than older toddlers and items in both of the later acquired item sets had higher probability rates for failure than the earliest acquired item set (prior to 8 months). Use of the same items and the same scoring throughout the target age range for autism screening may not be the best strategy for identifying the youngest toddlers at risk for autism.

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Section: Introductionmentioning

confidence: 79%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Comparison of Autism Screening in Younger and Older Toddlers

Sturner

Howard

Bergmann

et al. 2017

J Autism Dev Disord

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“…Since we know from prospective studies [55] that autism symptoms are just emerging at this age, one approach we have explored was to use items that were unlike the yes/no format of the M-CHAT but rather asked the parents “how much”. When we rescored two very brief existing tools and used them together the result was better sensitivity (0.62) for autism diagnoses than the M-CHAT-R/F (sensitivity of 0.48) without the need for a follow-up interview and this is the best current alternative[56]. Yet the positive predictive value problem has not been solved (only 0.37 and 0.32)[56].…”

Section: Introductionmentioning

confidence: 99%

“…When we rescored two very brief existing tools and used them together the result was better sensitivity (0.62) for autism diagnoses than the M-CHAT-R/F (sensitivity of 0.48) without the need for a follow-up interview and this is the best current alternative[56]. Yet the positive predictive value problem has not been solved (only 0.37 and 0.32)[56]. However, our preliminary studies show predictive validities equal to the 24 month visit using an algorithm featuring the addition of some standard language items with varying pathways depending ongoing item scoring by the computer [57].…”

Section: Introductionmentioning

confidence: 99%

Use of an Online Clinical Process Support System as an Aid to Identification and Management of Developmental and Mental Health Problems

Howard

Sturner

2017

Curr Dev Disord Rep

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Purpose of review To describe benefits and problems with screening and addressing developmental and behavioral problems in primary care and using an online clinical process support system as a solution. Recent findings Screening has been found to have various implementation barriers including time costs, accuracy, workflow and knowledge of tools. In addition, training of clinicians in dealing with identified issues is lacking. Patients disclose more to and prefer computerized screening. An online clinical process support system (CHADIS) shows promise in addressing these issues. Summary Use of a comprehensive panel of online pre-visit screens; linked decision support to provide moment-of-care training; and post-visit activities and resources for patient-specific education, monitoring and care coordination is an efficient way to make the entire process of screening and follow up care feasible in primary care. CHADIS fulfills these requirements and provides Maintenance of Certification credit to physicians as well as added income for screening efforts.

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What are we optimizing for in autism screening? Examination of algorithmic changes in the M‐CHAT

et al. 2021

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The present study objectives were to examine the performance of the new M‐CHAT‐R algorithm to the original M‐CHAT algorithm. The main purpose was to examine if the algorithmic changes increase identification of children later diagnosed with ASD, and to examine if there is a trade‐off when changing algorithms. We included 54,463 screened cases from the Norwegian Mother and Child Cohort Study. Children were screened using the 23 items of the M‐CHAT at 18 months. Further, the performance of the M‐CHAT‐R algorithm was compared to the M‐CHAT algorithm on the 23‐items. In total, 337 individuals were later diagnosed with ASD. Using M‐CHAT‐R algorithm decreased the number of correctly identified ASD children by 12 compared to M‐CHAT, with no children with ASD screening negative on the M‐CHAT criteria subsequently screening positive utilizing the M‐CHAT‐R algorithm. A nonparametric McNemar's test determined a statistically significant difference in identifying ASD utilizing the M‐CHAT‐R algorithm. The present study examined the application of 20‐item MCHAT‐R scoring criterion to the 23‐item MCHAT. We found that this resulted in decreased sensitivity and increased specificity for identifying children with ASD, which is a trade‐off that needs further investigation in terms of cost‐effectiveness. However, further research is needed to optimize screening for ASD in the early developmental period to increase identification of false negatives.

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Accurate Autism Screening at the 18-Month Well-Child Visit Requires Different Strategies than at 24 Months

Cited by 26 publications

References 35 publications

Comparison of Autism Screening in Younger and Older Toddlers

Comparison of Autism Screening in Younger and Older Toddlers

Use of an Online Clinical Process Support System as an Aid to Identification and Management of Developmental and Mental Health Problems

What are we optimizing for in autism screening? Examination of algorithmic changes in the M‐CHAT

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