Autism Screening With Online Decision Support by Primary Care Pediatricians Aided by M-CHAT/F

A Study on the Screening of Children at Risk for Developmental Disabilities Using Facial Landmarks Derived From a Mobile-Based Application

OBJECTIVE

Early detection and intervention of developmental disabilities (DDs) are critical to improving the long-term outcomes of afflicted children. In this study, our objective was to utilize facial landmark features from mobile application to distinguish between children with DDs and typically developing (TD) children.

METHODS

The present study recruited 89 children, including 33 diagnosed with DD, and 56 TD children. The aim was to examine the effectiveness of a deep learning classification model using facial video collected from children through mobile-based application. The study participants underwent comprehensive developmental assessments, which included the child completion of the Korean Psychoeducational Profile-Revised and caregiver completing the Korean versions of Vineland Adaptive Behavior Scale, Korean version of the Childhood Autism Rating Scale, Social Responsiveness Scale, and Child Behavior Checklist. We extracted facial landmarks from recorded videos using mobile application and performed DDs classification using long short-term memory with stratified 5-fold cross-validation.

RESULTS

The classification model shows an average accuracy of 0.88 (range: 0.78-1.00), an average precision of 0.91 (range: 0.75-1.00), and an average F1-score of 0.80 (range: 0.60-1.00). Upon interpreting prediction results using SHapley Additive exPlanations (SHAP), we verified that the most crucial variable was the nodding head angle variable, with a median SHAP score of 2.6. All the top 10 contributing variables exhibited significant differences in distribution between children with DD and TD (p<0.05).

CONCLUSION

The results of this study provide evidence that facial landmarks, utilizing readily available mobile-based video data, can be used to detect DD at an early stage.

Validation of the Electronic Modified Checklist for Autism in Toddlers, Revised with Follow-Up: A Nonrandomized Controlled Trial

OBJECTIVE

To examine the classification rates and screening properties, including sensitivity and specificity, of the web-based Modified Checklist for Autism in Toddler, Revised with Follow-Up (M-CHAT-R/F) compared with paper-phone administration, and to determine the extent to which electronic M-CHAT-R/F streamlines screening, increases screening fidelity, increases diagnostic evaluation participation, and decreases waiting time from screening to evaluation compared with paper-phone modality.

STUDY DESIGN

Primary-care practices in urban and suburban settings administered either the web-based or paper-phone M-CHAT-R/F using a prospective nonrandomized control design. Toddlers (n = 17 900) were screened between 2009 and 2016 at routine well-child check-ups. Toddlers who screened at risk on the M-CHAT-R/F were invited to complete diagnostic evaluations; 176 children were diagnosed with autism. The χ2, Fisher exact, and t-tests, as well as regression and screening properties, were used to compare outcome distributions, screening properties, and implementation by modality.

RESULTS

Classification rates of the initial M-CHAT-R into low, medium, and high risk were significantly different across modalities with very small effect sizes. Sensitivity and specificity were high across both modalities. For children in the medium-risk range, the web-based modality had a greater rate of predicting risk for autism after Follow-Up compared with the paper-phone modality, and the web eliminated delay between initial screen and Follow-Up. The web-based modality showed increased screening fidelity, no data loss, and similar rates of evaluation attendance and time to evaluation from Follow-Up administration.

CONCLUSIONS

The web-based M-CHAT-R/F is a valid tool for universal autism screening. Systems-level decisions should balance the increased feasibility of the electronic administration with the increase in Follow-Up accuracy provided by skilled clinician interview.

Sensitivity and Specificity of the Modified Checklist for Autism in Toddlers (Original and Revised): A Systematic Review and Meta-analysis

Importance

The Modified Checklist for Autism in Toddlers (M-CHAT) and the M-CHAT, Revised With Follow-up (M-CHAT-R/F)-henceforth referred to as M-CHAT(-R/F)-are the most commonly used toddler screeners for autism spectrum disorder (ASD). Their use often differs from that in the original validation studies, resulting in a range of estimates of sensitivity and specificity. Also, given the variability in reports of the clinical utility of the M-CHAT(-R/F), researchers and practitioners lack guidance to inform autism screening protocols.

Objective

To synthesize variability in sensitivity and specificity of M-CHAT(-R/F) across multiple factors, including procedures for identifying missed cases, likelihood level, screening age, and single compared with repeated screenings.

Data Sources

A literature search was conducted with PubMed, Web of Science, and Scopus to identify studies published between January 1, 2001, and August 31, 2022.

Study Selection

Articles were included if the studies used the M-CHAT(-R/F) (ie, original or revised version) to identify new ASD cases, were published in English-language peer-reviewed journals, included at least 10 ASD cases, reported procedures for false-negative case identification, screened children by 48 months, and included information (or had information provided by authors when contacted) needed to conduct the meta-analysis.

Data Extraction and Synthesis

The systematic review and meta-analysis was conducted within the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. The Quality Assessment of Diagnostic Accuracy Studies-2 tool evaluated bias in sample selection. Data extraction and quality assessment were performed by 2 authors independently. The overall diagnostic accuracy of the M-CHAT(-R/F) was assessed with the hierarchic summary receiver operating characteristic (HSROC) model.

Main Outcomes and Measures

Sensitivity, specificity, diagnostic odds ratios, and HSROC curves of M-CHAT(-R/F).

Results

The review included 50 studies with 51 samples. The pooled sensitivity of M-CHAT(-R/F) was 0.83 (95% CI, 0.77-0.88), and the pooled specificity was 0.94 (95% CI, 0.89-0.97). Heterogeneity analyses revealed greater diagnostic accuracy for low- vs high-likelihood samples, a concurrent vs prospective case confirmation strategy, a large vs small sample size, use of M-CHAT(-R/F) Follow-up, and non-English vs English only.

Conclusions and Relevance

Overall, results of this study suggest the utility of the M-CHAT(-R/F) as an ASD screener. The wide variability in psychometric properties of M-CHAT(-R/F) highlights differences in screener use that should be considered in research and practice.

Separate scoring algorithms for specific identification priorities optimize the screening properties of the Screening Tool for Autism in Toddlers (STAT)

The Screening Tool for Autism in Toddlers (STAT) is a validated stage-2 autism spectrum disorder (ASD) screening measure that takes 20 minutes to administer and comprises 12 play-based items that are scored according to specific criteria. This study examines an expanded version (STAT-E) that includes the examiner's subjective ratings of children's social engagement (SE) and atypical behaviors (AB) in the scoring algorithm. The sample comprised 238 children who were 24-35 months old. The STAT-E assessors had limited ASD experience to mimic its use by community-based non-specialists, and were trained using a scalable web-based platform. A diagnostic evaluation was completed by clinical experts who were blind to the STAT-E results. Logistic regression, ROC curves, and classification matrices and metrics were used to determine the screening properties of STAT-E when scored using the original STAT scoring algorithm versus a new algorithm that included the SE and AB ratings. Inclusion of the SE and AB ratings improved positive risk classification appreciably, while the specificity declined. These results suggest that the STAT-E using the original STAT scoring algorithm optimizes specificity, while the STAT-E scoring algorithm with the two new ratings optimizes the positive risk classification. Using multiple scoring algorithms on the STAT may provide improved screening accuracy for diverse contexts, and a scalable web-based tutorial may be a pathway for increasing the number of community providers who can administer the STAT and contribute toward increased rates of autism screening.

Do Autism-Specific and General Developmental Screens Have Complementary Clinical Value?

Prior studies suggest autism-specific and general developmental screens are complementary for identifying both autism and developmental delay (DD). Parents completed autism and developmental screens before 18-month visits. Children with failed screens for autism (n = 167) and age, gender, and practice-matched children passing screens (n = 241) completed diagnostic evaluations for autism and developmental delay. When referral for autism and/or DD was considered, overall false positives from the autism screens were less frequent than for referral for autism alone. Presence of a failed communication subscale in the developmental screen was a red flag for autism and/or DD. An ordinally-scored autism screen had more favorable characteristics when considering autism and/or DD, yet none of the screens achieved recommended standards at 18 months, reinforcing the need for recurrent screening as autism emerges in early development.

Reducing Barriers to Autism Screening in Community Primary Care: A Pragmatic Trial Using Web-Based Screening

OBJECTIVE

To determine whether an intervention addressing both logistical and knowledge barriers to early screening for autism spectrum disorder (ASD) increases evidence-based screening during 18-month well-child visits and primary care providers' (PCPs') perceived self-efficacy in caring for children with ASD.

METHODS

Forty-six PCPs from 10 diverse practices across four counties in Washington State participated. PCPs attended a 2-hour training workshop on early recognition and care for toddlers with ASD and use of a REDCap-based version of the Modified Checklist for Autism in Toddlers-Revised with Follow-up (webM-CHAT-R/F) that provided automated presentation and scoring of follow-up questions. Data were collected at baseline and 6 months following each county's training window. PCPs' screening methods and rates and perceived self-efficacy regarding ASD care were measured by self-report and webM-CHAT-R/F use was measured via REDCap records.

RESULTS

At follow-up, 8 of the 10 practices were using the webM-CHAT-R/F routinely at 18-month visits. The proportion of PCPs reporting routine M-CHAT screening increased from 82% at baseline to 98% at follow-up (16% increase, 95% confidence interval [CI] 3%-28%; McNemar exact P = .02). The proportion using the M-CHAT-R/F follow-up interview questions increased from 33% to 82% (49% increase, 95% CI 30%-68%, exact McNemar test, P < .001). Significant increases in self-efficacy were found for all seven areas assessed (Ps ≤ .008).

CONCLUSIONS

This brief intervention increased PCPs' self-reported valid use of the M-CHAT-R/F at 18 months and their self-efficacy regarding ASD care. Combining educational information with a web-based ASD screen incorporating the M-CHAT-R/F follow-up questions may increase universal ASD screening with improved fidelity.

Autism screening at 18 months of age: a comparison of the Q-CHAT-10 and M-CHAT screeners

Background

Autism screening is recommended at 18- and 24-month pediatric well visits. The Modified Checklist for Autism in Toddlers—Revised (M-CHAT-R) authors recommend a follow-up interview (M-CHAT-R/F) when positive. M-CHAT-R/F may be less accurate for 18-month-olds than 24-month-olds and accuracy for identification prior to two years is not known in samples that include children screening negative. Since autism symptoms may emerge gradually, ordinally scoring items based on the full range of response options, such as in the 10-item version of the Quantitative Checklist for Autism in Toddlers (Q-CHAT-10), might better capture autism signs than the dichotomous (i.e., yes/no) items in M-CHAT-R or the pass/fail scoring of Q-CHAT-10 items. The aims of this study were to determine and compare the accuracy of the M-CHAT-R/F and the Q-CHAT-10 and to describe the accuracy of the ordinally scored Q-CHAT-10 (Q-CHAT-10-O) for predicting autism in a sample of children who were screened at 18 months.

Methods

This is a community pediatrics validation study with screen positive (n = 167) and age- and practice-matched screen negative children (n = 241) recruited for diagnostic evaluations completed prior to 2 years old.

Clinical diagnosis of autism was based on results of in-person diagnostic autism evaluations by research reliable testers blind to screening results and using the Autism Diagnostic Observation Schedule—Second Edition (ADOS-2) Toddler Module and Mullen Scales of Early Learning (MSEL) per standard guidelines.

Results

While the M-CHAT-R/F had higher specificity and PPV compared to M-CHAT-R, Q-CHAT-10-O showed higher sensitivity than M-CHAT-R/F and Q-CHAT-10.

Limitations

Many parents declined participation and the sample is over-represented by higher educated parents. Results cannot be extended to older ages.

Conclusions

Limitations of the currently recommended two-stage M-CHAT-R/F at the 18-month visit include low sensitivity with minimal balancing benefit of improved PPV from the follow-up interview. Ordinal, rather than dichotomous, scoring of autism screening items appears to be beneficial at this age. The Q-CHAT-10-O with ordinal scoring shows advantages to M-CHAT-R/F with half the number of items, no requirement for a follow-up interview, and improved sensitivity. Yet, Q-CHAT-10-O sensitivity is less than M-CHAT-R (without follow-up) and specificity is less than the two-stage procedure. Such limitations are consistent with recognition that screening needs to recur beyond this age.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-021-00480-4.

[Value of autism screening checklists in the early identification of autism spectrum disorder]

OBJECTIVE

To evaluate the value of autism screening checklists in the early identification of autism spectrum disorder (ASD).

METHODS

A total of 2 571 children who attended the Children's Hospital of Chongqing Medical University and completed autism screening and diagnostic test were enrolled as subjects, among whom 2 074 were diagnosed with ASD, 261 were diagnosed with global developmental delay (GDD), 206 were diagnosed with developmental language disorder (DLD), and 30 had normal development. The sensitivity, specificity, and optimal threshold value of the Modified Checklist for Autism in Toddlers (M-CHAT) and the Autism Behavior Checklist (ABC) for the early identification of ASD were evaluated by the receiver operating characteristic (ROC) curve.

RESULTS

The M-CHAT had a high sensitivity of 88.3% but a low specificity of 36.0% for the identification of ASD. Its sensitivity decreased with age, and was maintained above 80% for children aged 16 to < 48 months. The ABC had a high specificity of 87.3% but a low sensitivity of 27.2%, with an optimal cut-off value of 47.5 based on the ROC curve analysis. The multivariate linear regression model based on a combination of the M-CHAT and ABC for screening of ASD showed a specificity of 85.8% and a sensitivity of 56.6%.

CONCLUSIONS

The M-CHAT has a high sensitivity and a low specificity in the identification of ASD, with a better effect in children aged 16 to < 48 months. The ABC has a high specificity and a low sensitivity. The multiple linear regression model method based on the combined M-CHAT and ABC to screen ASD appears to be effective.

[Value of autism screening checklists in the early identification of autism spectrum disorder]

OBJECTIVE

To evaluate the value of autism screening checklists in the early identification of autism spectrum disorder (ASD).

METHODS

A total of 2 571 children who attended the Children's Hospital of Chongqing Medical University and completed autism screening and diagnostic test were enrolled as subjects, among whom 2 074 were diagnosed with ASD, 261 were diagnosed with global developmental delay (GDD), 206 were diagnosed with developmental language disorder (DLD), and 30 had normal development. The sensitivity, specificity, and optimal threshold value of the Modified Checklist for Autism in Toddlers (M-CHAT) and the Autism Behavior Checklist (ABC) for the early identification of ASD were evaluated by the receiver operating characteristic (ROC) curve.

RESULTS

The M-CHAT had a high sensitivity of 88.3% but a low specificity of 36.0% for the identification of ASD. Its sensitivity decreased with age, and was maintained above 80% for children aged 16 to < 48 months. The ABC had a high specificity of 87.3% but a low sensitivity of 27.2%, with an optimal cut-off value of 47.5 based on the ROC curve analysis. The multivariate linear regression model based on a combination of the M-CHAT and ABC for screening of ASD showed a specificity of 85.8% and a sensitivity of 56.6%.

CONCLUSIONS

The M-CHAT has a high sensitivity and a low specificity in the identification of ASD, with a better effect in children aged 16 to < 48 months. The ABC has a high specificity and a low sensitivity. The multiple linear regression model method based on the combined M-CHAT and ABC to screen ASD appears to be effective.

Detection of Early Warning Signs in Autism Spectrum Disorders: A Systematic Review

Due to the exponential increase of autism spectrum disorders’ prevalence in Western countries, it is necessary to improve early detection and intervention to enhance developmental milestones. This systematic review identified the most effective screening instrument, which can be used at an early age and which identifies the maximum number of autism cases. We identified several instruments with adequate predictive properties—the Autism Parent Screen for Infants (APSI), Battelle Development Inventory, second edition (BDI-2); Brief Infant-Toddler Social and Emotional Assessment (BITSEA); First Year Inventory (FYI); Infant-Toddler Checklist/Communication and Symbolic Behavior Scales Developmental Profile (ITC/CSBS-DP); Program of Research and Studies on AUTISM (PREAUT-Grid); Checklist for Early Signs of Developmental Disorders (CESDD); Social Attention and Communication Study (SACS); and the Screening Tool for Autism in Toddlers and Young Children (STAT)—that can be applied from 12 months of age in Western countries. The ITC/CSBS-DP has been proposed for universal screening from 12 months of age onwards, complemented by the Modified Checklist for Autism in Toddlers, Revised/Revised with Follow-Up (M-CHAT-R/F), which can be used from 15 months of age onwards. This strategy could improve early detection in at-risk children within the current health system, thus allowing for early intervention.

A systematic review of technological approaches for autism spectrum disorder assessment in children: Implications for the COVID-19 pandemic

BACKGROUND

Screening and diagnostic assessments tools for autism spectrum disorder (ASD) are important to administer during childhood to facilitate timely entry into intervention services that can promote developmental outcomes across the lifespan. However, assessment services are not always readily available to families, as they require significant time and resources. Currently, in-person screening and diagnostic assessments for ASD are limited due to the COVID-19 pandemic and will continue to be a concern for situations that limit in-person contact. Thus, it is important to expand the modalities in which child assessments are provided, including the use of technology.

AIMS

This systematic review aims to identify technologies that screen or assess for ASD in 0-12 year-old children, summarizing the current state of the field and suggesting future directions.

METHODS

An electronic database search was conducted to gather relevant articles to synthesize for this review.

OUTCOMES AND RESULTS

16 studies reported use of novel technology to assess children suspected of ASD.

CONCLUSIONS AND IMPLICATIONS

Results strongly supported live-video evaluations, video observations, and online or phone methods, but there is a need for research targeting the feasibility of these methods as it applies to the stay-at-home orders required by the pandemic, and other situations that limit clients from seeing providers in-person.

Incremental Utility of 24-Month Autism Spectrum Disorder Screening After Negative 18-Month Screening

The American Academy of Pediatrics recommends Autism Spectrum Disorder (ASD) screening at 18 and 24 months. However, utility of rescreening at 24 months, after a negative 18-month screening, remains unknown. We identified cases of ASD detected at 24 months after a negative 18-month screening (i.e., Catch-24 group; n = 10) and compared them to toddlers detected by 18-month screening (i.e., Early Diagnosis group; n = 203). Repeated ASD-specific screening at 24 months detected children who were missed at their 18-month screening. Thus, our findings support repeated screening for ASD at both 18 and 24 months in order to maximize identification of toddlers with ASD and other neurodevelopmental disorders who require intervention.

Primary Care Autism Screening and Later Autism Diagnosis

OBJECTIVES

To describe the proportion of children screened by the Modified Checklist for Autism in Toddlers (M-CHAT), identify characteristics associated with screen completion, and examine associations between autism spectrum disorder (ASD) screening and later ASD diagnosis.

METHODS

We examined data from children attending 18- and 24-month visits between 2013 and 2016 from 20 clinics within a health care system for evidence of screening with the M-CHAT and subsequent coding of ASD diagnosis at age >4.75 years. We interviewed providers for information about usual methods of M-CHAT scoring and ASD referral.

RESULTS

Of 36 233 toddlers, 73% were screened and 1.4% were later diagnosed with ASD. Hispanic children were less likely to be screened (adjusted prevalence ratio [APR]: 0.95, 95% confidence interval [CI]: 0.92-0.98), and family physicians were less likely to screen (APR: 0.12, 95% CI: 0.09-0.15). Compared with unscreened children, screen-positive children were more likely to be diagnosed with ASD (APR: 10.3, 95% CI: 7.6-14.1) and were diagnosed younger (38.5 vs 48.5 months, P < .001). The M-CHAT's sensitivity for ASD diagnosis was 33.1%, and the positive predictive value was 17.8%. Providers routinely omitted the M-CHAT follow-up interview and had uneven referral patterns.

CONCLUSIONS

A majority of children were screened for ASD, but disparities exist among those screened. Benefits for screen-positive children are improved detection and younger age of diagnosis. Performance of the M-CHAT can be improved in real-world health care settings by administering screens with fidelity and facilitating timely ASD evaluations for screen-positive children. Providers should continue to monitor for signs of ASD in screen-negative children.

The Acceptability and Effectiveness of Web-Based Developmental Surveillance Programs: Rapid Review

Background

Web-based developmental surveillance programs may be an innovative solution to improving the early detection of childhood developmental difficulties, especially within disadvantaged populations.

Objective

This review aimed to identify the acceptability and effectiveness of web-based developmental surveillance programs for children aged 0 to 6 years.

Methods

A total of 6 databases and gray literature were searched using a Preferred Reporting Items for Systematic Reviews and Meta-Analyses–informed protocol. Data extraction included variables related to health equity.

Results

In total, 20 studies were identified. Most papers implemented web-based versions of the Modified Checklist for Autism in Toddlers, Revised with Follow-Up screener for autism spectrum disorder or Parent Evaluation of Developmental Status screeners for broad developmental delay. Caregivers and practitioners indicated a preference for web-based screeners, primarily for user-friendliness, improved follow-up accuracy, time, and training efficiencies.

Conclusions

Although evidence is limited as to the necessity of web- versus face-to-face–based developmental screening, there are clear efficiencies in its use.

Trial Registration

PROSPERO CRD42019127894; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=127894

Trends in Pediatricians' Developmental Screening: 2002-2016

BACKGROUND

Current guidelines from the American Academy of Pediatrics recommend screening children for developmental problems by using a standardized screening tool and referring at-risk patients to early intervention (EI) or subspecialists. Adoption of guidelines has been gradual, with research showing many children still not being screened and referred.

METHODS

We analyzed American Academy of Pediatrics Periodic Survey data from 2002 (response rate = 58%; N = 562), 2009 (response rate = 57%; N = 532), and 2016 (response rate = 47%, N = 469). Surveys included items on pediatricians' knowledge, attitudes, and practices regarding screening and referring children for developmental problems. We used descriptive statistics and a multivariable logistic regression model to examine trends in screening and referral practices and attitudes.

RESULTS

Pediatricians' reported use of developmental screening tools increased from 21% in 2002 to 63% in 2016 (P < .001). In 2016, on average pediatricians reported referring 59% of their at-risk patients to EI, up from 41% in 2002 (P < .001), and pediatricians in 2016 were more likely than in 2002 to report being "very likely" to refer a patient with global developmental delay, milestone loss, language delay, sensory impairment, motor delays, and family concern to EI.

CONCLUSIONS

Pediatricians' reported use of a standardized developmental screening tool has tripled from 2002 to 2016, and more pediatricians are self-reporting making referrals for children with concerns in developmental screening. To sustain this progress, additional efforts are needed to enhance referral systems, improve EI programs, and provide better tracking of child outcomes.

Screening Tools for Autism Spectrum Disorder in Primary Care: A Systematic Evidence Review

CONTEXT

Recommendations conflict regarding universal application of formal screening instruments in primary care (PC) and PC-like settings for autism spectrum disorder (ASD).

OBJECTIVES

We systematically reviewed evidence for universal screening of children for ASD in PC.

DATA SOURCES

We searched Medline, PsychInfo, Educational Resources Informational Clearinghouse, and Cumulative Index of Nursing and Allied Health Literature.

STUDY SELECTION

We included studies in which researchers report psychometric properties of screening tools in unselected populations across PC and PC-like settings.

DATA EXTRACTION

At least 2 authors reviewed each study, extracted data, checked accuracy, and assigned quality ratings using predefined criteria.

RESULTS

We found evidence for moderate to high positive predictive values for ASD screening tools to identify children aged 16 to 40 months and 1 study for ≥48 months in PC and PC-like settings. Limited evidence evaluating sensitivity, specificity, and negative predictive value of instruments was available. No studies directly evaluated the impact of screening on treatment or harm.

LIMITATIONS

Potential limitations include publication bias, selective reporting within studies, and a constrained search.

CONCLUSIONS

ASD screening tools can be used to accurately identify percentages of unselected populations of young children for ASD in PC and PC-like settings. The scope of challenges associated with establishing direct linkage suggests that clinical and policy groups will likely continue to guide screening practices. ASD is a common neurodevelopmental disorder associated with significant life span costs.^1,2 Growing evidence supports functional gains and improved outcomes for young children receiving intensive intervention, so early identification on a population level is a pressing public health challenge.^3,4.

Autism spectrum disorder: psychological and functional assessment, and behavioral treatment approaches

There have been significant changes in the way Autism has been defined especially in the last decade. The changes encompass criteria over a spectrum rather than individual diagnoses based on clusters of criteria. With these changes, there has been a push for earlier screening and diagnosis to be made to ensure individual impacted by the deficits have ample time and opportunity to receive the services they need. Additionally, with the changes that have come up, screening tools and assessments have also been changed and improved to assist with the increasing demand of early screening. Screeners have been created to help in primary care settings so physicians can gauge the severity of symptoms and refer patients to the appropriate resources. The assessment and diagnostic process for Autism involves a large battery including parental interviews and forms, the ADOS-II, and a multitude of other intellectual assessments to get a full picture of what the individual is experiencing. Once an individual is diagnosed with Autism, the interventionist team, physicians, and clinicians assist the family in finding the appropriate resources and treatment plan. There are several evidence-based therapies that exist that have been effective in improving the quality of life of individuals with Autism Spectrum Disorder diagnoses. Although several interventions and therapies exist, there are some potential interventions some use that need to more research to know how truly effective they are.

Effect of a Computer-Based Decision Support Intervention on Autism Spectrum Disorder Screening in Pediatric Primary Care Clinics: A Cluster Randomized Clinical Trial

IMPORTANCE

Universal early screening for autism spectrum disorder (ASD) is recommended but not routinely performed.

OBJECTIVE

To determine whether computer-automated screening and clinical decision support can improve ASD screening rates in pediatric primary care practices.

DESIGN, SETTING, AND PARTICIPANTS

This cluster randomized clinical trial, conducted between November 16, 2010, and November 21, 2012, compared ASD screening rates among a random sample of 274 children aged 18 to 24 months in urban pediatric clinics of an inner-city county hospital system with or without an ASD screening module built into an existing decision support software system. Statistical analyses were conducted from February 6, 2017, to June 1, 2018.

INTERVENTIONS

Four clinics were matched in pairs based on patient volume and race/ethnicity, then randomized within pairs. Decision support with the Child Health Improvement Through Computer Automation system (CHICA) was integrated with workflow and with the electronic health record in intervention clinics.

MAIN OUTCOMES AND MEASURES

The main outcome was screening rates among children aged 18 to 24 months. Because the intervention was discontinued among children aged 18 months at the request of the participating clinics, only results for those aged 24 months were collected and analyzed. Rates of positive screening results, clinicians' response rates to screening results in the computer system, and new cases of ASD identified were also measured. Main results were controlled for race/ethnicity and intracluster correlation.

RESULTS

Two clinics were randomized to receive the intervention, and 2 served as controls. Records from 274 children (101 girls, 162 boys, and 11 missing information on sex; age range, 23-30 months) were reviewed (138 in the intervention clinics and 136 in the control clinics). Of 263 children, 242 (92.0%) were enrolled in Medicaid, 138 (52.5%) were African American, and 96 (36.5%) were Hispanic. Screening rates in the intervention clinics increased from 0% (95% CI, 0%-5.5%) at baseline to 68.4% (13 of 19) (95% CI, 43.4%-87.4%) in 6 months and to 100% (18 of 18) (95% CI, 81.5%-100%) in 24 months. Control clinics had no significant increase in screening rates (baseline, 7 of 64 children [10.9%]; 6-24 months after the intervention, 11 of 72 children [15.3%]; P = .46). Screening results were positive for 265 of 980 children (27.0%) screened by CHICA during the study period. Among the 265 patients with positive screening results, physicians indicated any response in CHICA in 151 (57.0%). Two children in the intervention group received a new diagnosis of ASD within the time frame of the study.

CONCLUSIONS AND RELEVANCE

The findings suggest that computer automation, when integrated with clinical workflow and the electronic health record, increases screening of children for ASD, but follow-up by physicians is still flawed. Automation of the subsequent workup is still needed.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01612897.

Implementation of M-CHAT Screening for Autism in Primary Care in Saudi Arabia

Background. Integration of autism screening into primary care practice in Saudi Arabia is not well established. Objectives. To evaluate the feasibility and effectiveness of implementing the Arabic Modified Checklist for Autism in Toddlers (M-CHAT) in a primary care practice at John Hopkins Aramco Healthcare Center in Saudi Arabia. Method. The Arabic version of M-CHAT was distributed to caregivers of 1207 toddlers (16-32 months) from January to December 2014. Feasibility was assessed by measuring the proportion of visits with M-CHAT completed, and reports of workflow challenges and provider satisfaction. The effectiveness of screening was evaluated based on the number of referrals for autism evaluation and autism identification rates. Results. Total M-CHAT completion rate was 89% (1078 out of 1207 child-specific visits). Those identified as low risk (n = 951; 88%) were reassured and followed routinely. Those screening positive (n = 127; 12%) were referred for diagnostic assessment. Twelve (1% of toddlers screened) were diagnosed with autism at a mean age of 24 months. In addition, positive M-CHAT detected speech delay and social anxiety. Providers acknowledged their satisfaction with the M-CHAT implementation process; the main challenge was communicating to families the importance of screening. Referrals for diagnostic evaluations increased from 23 to 43 cases in the first year, and 35 in the second year. Conclusion. Implementation of the autism screening using the Arabic M-CHAT is feasible and effective in a primary care setting in Saudi Arabia. Sustaining the implementation of developmental screening in practice requires staff engagement and systematic monitoring of the impact of change.

Reliability and Validity of the Chinese Version of Modified Checklist for Autism in Toddlers, Revised, with Follow-Up (M-CHAT-R/F)

Although early detection of autism facilitates intervention, early detection strategies are not yet widespread in China. To improve the situation, the Chinese version of the Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT-R/F) was validated. The sample included 7928 toddlers, aged 16 to 30 months, screened during their routine care in six provinces of China. When the cut-off value was 3, the sensitivity and specificity of M-CHAT-R were 0.963 and 0.865. The inter-rater reliability and the test-retest reliability were also adequate (intraclass correlation coefficients were 0.853 and 0.759, both ps < .01). The Chinese version of M-CHAT-R/F is an effective tool for early detection of ASD and is applicable to early screening in China.

Linking the Medical and Educational Home to Support Children With Autism Spectrum Disorder: Practice Recommendations

Children with autism spectrum disorder (ASD) present with complex medical problems that are often exacerbated by a range of other intellectual and psychiatric comorbidities. These children receive care for their physical and mental health from a range of providers within numerous child-serving systems, including their primary care clinic, school, and the home and community. Given the longitudinal nature in which care is provided for this chronic disorder, it is particularly necessary for services and providers to coordinate their care to ensure optimal efficiency and effectiveness. There are 2 primary venues that serve as a "home" for coordination of service provision for children with ASD and their families-the "medical home" and the "educational home." Unfortunately, these venues often function independently from the other. Furthermore, there are limited guidelines demonstrating methods through which pediatricians and other primary care providers (PCPs) can coordinate care with schools and school-based providers. The purpose of this article is 2-fold: (1) we highlight the provision of evidence-based care within the medical home and educational home and (2) we offer practice recommendations for PCPs in integrating these systems to optimally address the complex medical, intellectual, and psychiatric symptomology affected by autism.

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

Accuracy of autism screening using M-CHAT plus the follow-up interview (M-CHAT/F) for children screened positive at 18-months was compared to screening at 24-months. Formal ASD testing was criterion for a community sample of M-CHAT positive children (n = 98), positive predictive value (PPV) was 0.40 for the M-CHAT and 0.58 for the M-CHAT/F. MCHAT/F PPV was 0.69 among children 20+ months compared to 0.36 for <20 months. Multivariate analyses incorporating data from the Ages and Stages Questionnaire, MacArthur-Bates Communicative Development Inventory, M-CHAT and M-CHAT/F results, and M-CHAT items suggest language variables carry greatest relative importance in contributing to an age-based algorithm with potential to improve PPV for toddlers <20 months to the same level as observed in older toddlers.

Risk Assessment for Parents Who Suspect Their Child Has Autism Spectrum Disorder: Machine Learning Approach

Background

Parents are likely to seek Web-based communities to verify their suspicions of autism spectrum disorder markers in their child. Automated tools support human decisions in many domains and could therefore potentially support concerned parents.

Objective

The objective of this study was to test the feasibility of assessing autism spectrum disorder risk in parental concerns from Web-based sources, using automated text analysis tools and minimal standard questioning.

Methods

Participants were 115 parents with concerns regarding their child’s social-communication development. Children were 16- to 30-months old, and 57.4% (66/115) had a family history of autism spectrum disorder. Parents reported their concerns online, and completed an autism spectrum disorder-specific screener, the Modified Checklist for Autism in Toddlers-Revised, with Follow-up (M-CHAT-R/F), and a broad developmental screener, the Ages and Stages Questionnaire (ASQ). An algorithm predicted autism spectrum disorder risk using a combination of the parent's text and a single screening question, selected by the algorithm to enhance prediction accuracy.

Results

Screening measures identified 58% (67/115) to 88% (101/115) of children at risk for autism spectrum disorder. Children with a family history of autism spectrum disorder were 3 times more likely to show autism spectrum disorder risk on screening measures. The prediction of a child’s risk on the ASQ or M-CHAT-R was significantly more accurate when predicted from text combined with an M-CHAT-R question selected (automatically) than from the text alone. The frequently automatically selected M-CHAT-R questions that predicted risk were: following a point, make-believe play, and concern about deafness.

Conclusions

The internet can be harnessed to prescreen for autism spectrum disorder using parental concerns by administering a few standardized screening questions to augment this process.

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

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.

Comparison of Autism Screening in Younger and Older Toddlers

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 et al. (Research in Autism Spectrum Disorders 4(4):605-611, 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.