Developmental Surveillance and Referral in a Traditionally Medically Underserved Border Community.

This was a project in primary care for young children (1-2 years old). We tested a parent questionnaire on a tablet. This tablet questionnaire asked questions to see whether the child may have autism. We compared the paper and pencil version of the questionnaire to the tablet questionnaire. We read the medical charts for the children until they were 4 years old to see whether they ended up having autism. We found that doctors were more likely to recommend an autism evaluation when a parent used the tablet questionnaire. We think that the tablet's automatic scoring feature helped the doctors. We also think that the doctors benefited from the advice the tablet gave them.

We examined the characteristics of children at 4 to 5 years of age who were correctly and incorrectly classified as "at risk" for an autism spectrum diagnosis using the Checklist for Autism in Toddlers (CHAT) at age 2 to 3 years. Information is provided on the stability of risk/disorder status over a 2-year period of early development. Participants were 19 children with autism and 11 children with other developmental disabilities who had all been administered the CHAT between 2 and 3 years of age (Time 1) and received diagnostic and developmental re-evaluations between 4 and 6 years of age (Time 2). The risk status of children was discussed based on the original CHAT authors' criteria for risk of autism and the Denver modification for risk. High levels of stability in risk/diagnostic status from Time 1 assessments to Time 2 assessments were noted. Specifically, the original CHAT criteria for medium to high risk of autism applied at Time 1 predicted Time 2 diagnostic classification for 83% of the sample, and the Denver modification of the CHAT risk criteria predicted Time 2 diagnostic classification for 93% of the sample. Implications of the findings are discussed as they relate to early screening and identification of autism spectrum disorders.

This study examined a widely used autism screening tool, the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up to identify differences in screening for autism between toddler males and females. Examining sex differences in screening for autism in toddlerhood is important as it determines who will be referred for evaluations and receive diagnoses, which is critical for access to autism-specific early intervention. This study found that females were less likely to screen positive and be invited for evaluations compared with males. Females at high likelihood for autism were less likely to be diagnosed with autism, which decreases confidence in the screener's results. Importantly, the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up accurately identified both males and females with autism. Future research should examine ways to improve accuracy in screening results for females.

With the continuous increase in the prevalence of autistic spectrum disorder (ASD), effective early screening is crucial for initiating timely interventions and improving outcomes. To develop predictive models for ASD using routinely collected developmental surveillance data and to assess their performance in predicting ASD at different ages and in different clinical scenarios. This retrospective cohort study used nationwide data of developmental assessments conducted between January 1, 2014, and January 17, 2023, with minimal follow-up of 4 years and outcome collection in March 2023. Data were from a national program of approximately 1000 maternal child health clinics that perform routine developmental surveillance of children from birth to 6 years of age, serving 70% of children in Israel. The study included all children who were assessed at the maternal child health clinics (N = 1 187 397). Children were excluded if they were born at a gestational age of 33 weeks or earlier, had no record of gestational age, or were followed up for less than 4 years without an ASD outcome. The data set was partitioned at random into a development set (80% of the children) and a holdout evaluation set (20% of the children), both with the same prevalence of ASD outcome. For each child, demographic and birth-related covariates were extracted, as were per-visit growth measurements, quantified developmental milestone assessments, and referral summary covariates. Only information that was available before the prediction age was used for training and evaluating the models. The main outcome was eligibility for a governmental disabled child allowance due to ASD, according to administrative data of the National Insurance Institute of Israel. The performance of the models that predict the outcome was evaluated and compared with previous work on the Modified Checklist for Autism in Toddlers (M-CHAT). The study included 1 187 397 children (610 588 [51.4%] male). The performance of the ASD prediction models improved with prediction age, with fair accuracy already at 12 months of age. A model that combined longitudinal measures of developmental milestone assessments with a minimal set of demographic variables, which was applied at 18 to 24 months of age, achieved an area under the receiver operating characteristic curve of 0.83, with a sensitivity of 45.1% at a specificity of 95.0%. A model using single-visit assessments achieved an area under the receiver operating characteristic curve of 0.81 and a sensitivity of 41.2% at a specificity of 95.0%. The best performing prediction models surpassed the pooled performance of M-CHAT (sensitivity, 40%; specificity, 95%) reported in studies with a similar design. This cohort study found that ASD can be predicted from routine developmental surveillance data at an accuracy surpassing M-CHAT screening. This tool may be seamlessly integrated in the clinical workflow to improve early identification of children who may benefit from timely interventions.

The study examined the clinical utility and psychometric properties of the Korean Modified Checklist of Autism in Toddlers (K-M-CHAT)-2. A sample of 2300 parents of 16- to 36-month-old children was recruited across South Korea. A phone interview was utilized to follow up with participants who initially screened positive for autism spectrum disorder (ASD). Item response theory was applied to assess the psychometric properties of the K-M-CHAT-2. Parents' responses were substantially changed after the follow-up, and the final screen-positive rate was 2.3 %. Results indicated that the psychometric properties of items 1, 3, 11, 18 and 22 were not as strong as the other items. The K-M-CHAT-2 is a useful ASD screening test when implemented with a follow-up.

This study investigated the psychometric properties of the modified checklist for autism in toddlers (M-CHAT) in a diverse rural American low-socioeconomic status (SES) sample. Four hundred and forty-seven English (n=335) and Spanish (n=112) speaking caregivers completed the M-CHAT during their toddler's 18- or 24-month well visit in a Southwest Virginia pediatric clinic. The M-CHAT did not show acceptable internal consistency in groups with low maternal education or minority status. Caregivers reporting low maternal education and minority status were more likely to endorse items suggestive of autism. These results indicate that the M-CHAT may require modifications to be more internally consistent and accurate across ethnic and educational groups in rural areas with low levels of SES. Recommendations to increase the utility of the M-CHAT are discussed.

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

Early detection and treatment have been shown to be effective in reducing disability severity caused by Autistic Spectrum Disorders (ASDs). As Spanish pediatricians have no detection tool, the Modified Checklist for Autism in Toddlers (M-CHAT) was first translated into and culturally adapted to Spanish. Validity and reliability studies were carried out in two different geographical areas of Spain, where M-CHAT was administered to two different samples, namely: 2,480 high- and low-risk children; and 2,055 low-risk children. The results obtained were similar to those yielded by the original M-CHAT studies. Differences were found in positive predictive value, due to the low ASD frequency observed in this study. M-CHAT is still being studied in a large population-based screening program in Spain.

The Modified Checklist for Autism in Toddlers (M-CHAT) is a screening questionnaire for Autism Spectrum Disorder (ASD). Previous findings have confirmed the M-CHAT's sensitivity and specificity across several cultures, yet few studies have considered M-CHAT scores as a distributed trait in a sample of typical infants. The current study examined how the M-CHAT predictsconcurrent word learning (experiment 1) as well as socio-emotional understanding (experiment 2) in 18-month-old infants. Results demonstrated that the number of items endorsed on the M-CHAT negatively correlated with the proportion of trials on which infants looked at a toy named by the experimenter as well as performance on the word learning task. In experiment 2, high scores on the M-CHAT correlated with less instrumental helping, less imitation, and a smaller productive vocabulary size.

Reliability and validity of the Japanese version of the Modified Checklist for autism in toddlers (M-CHAT)

We assessed the prevalence of autism spectrum disorders (ASD) and screening test characteristics in children with Down syndrome. Eligible children born in a defined geographic area between January 1, 1996, and December 31, 2003, were recruited through a population-based birth defects registry and community outreach, then screened with the modified checklist for autism in toddlers or social communication questionnaire, as appropriate. Screen-positive children and a random sample of screen-negative children underwent developmental evaluation. We screened 123 children (27.8% of the birth cohort). Mean age was 73.4 months (range, 31-142). Compared to screen-negative children, screen-positive children had similar sociodemographic characteristics but a lower mean developmental quotient (mean difference: 11.0; 95% confidence interval: 4.8-17.3). Weighted prevalences of autistic disorder and total ASD were 6.4% (95% confidence interval [CI]: 2.6%-11.6%) and 18.2% (95% CI: 9.7%-26.8%), respectively. The estimated minimum ASD prevalence, accounting for unscreened children, is 5.1% (95% CI: 3.3%-7.4%). ASD prevalence increased with greater cognitive impairment. Screening test sensitivity was 87.5% (95% CI: 66.6%-97.7%); specificity was 49.9% (95% CI: 37.0%-61.4%). The prevalence of ASD among children with Down syndrome aged 2 to 11 years is substantially higher than in the general population. The modified checklist for autism in toddlers and social communication questionnaire were highly sensitive in children with Down syndrome but could result in many false positive tests if universal screening were implemented using current algorithms. Research needs include development of specific ASD screening algorithms and improved diagnostic discrimination in children with Down syndrome. Timely identification of these co-occurring diagnoses is essential so appropriate interventions can be provided.

In the past two decades, several screening instruments were developed to detect toddlers who may be autistic both in clinical and unselected samples. Among others, the Quantitative CHecklist for Autism in Toddlers (Q-CHAT) is a quantitative and normally distributed measure of autistic traits that demonstrates good psychometric properties in different settings and cultures. Recently, machine learning (ML) has been applied to behavioral science to improve the classification performance of autism screening and diagnostic tools, but mainly in children, adolescents, and adults. In this study, we used ML to investigate the accuracy and reliability of the Q-CHAT in discriminating young autistic children from those without. Five different ML algorithms (random forest (RF), naïve Bayes (NB), support vector machine (SVM), logistic regression (LR), and K-nearest neighbors (KNN)) were applied to investigate the complete set of Q-CHAT items. Our results showed that ML achieved an overall accuracy of 90%, and the SVM was the most effective, being able to classify autism with 95% accuracy. Furthermore, using the SVM–recursive feature elimination (RFE) approach, we selected a subset of 14 items ensuring 91% accuracy, while 83% accuracy was obtained from the 3 best discriminating items in common to ours and the previously reported Q-CHAT-10. This evidence confirms the high performance and cross-cultural validity of the Q-CHAT, and supports the application of ML to create shorter and faster versions of the instrument, maintaining high classification accuracy, to be used as a quick, easy, and high-performance tool in primary-care settings.

To understand Black mothers' perspectives on the autism screening process with the Modified Checklist for Autism in Toddlers (M-CHAT) and preferences in provider communications and interactions around autism screening. This qualitative study thematically analyzed semi-structured interviews of Black mothers (N = 11) whose child screened positive on an autism screener administered as part of a routine well-child visit in primary care. All interviews were audio-recorded, transcribed, and entered into NVivo software for data management and analysis. Coders achieved an average of over 95% agreement in double-coded transcripts across all thematic codes. Results from a qualitative thematic analysis of Black mothers' experiences with and preferences for early autism screening in primary care produced 5 primary themes: (1) preference for the pediatrician to report positive screening results, (2) desire to discuss developmental concerns with family members, (3) online resources as key information resources on autism and child development juxtaposed to, (4) valuing face-to-face time with early childhood providers, and (5) barriers to completing the M-CHAT. Black mothers described their preferences for completing autism screening for their children and emphasized the role of the pediatrician, family members, and online resources in providing information about child development and autism concerns. Trust in the pediatrician emerged as a salient theme, which runs counter to prior narratives that describe earned mistrust between Black caregivers and medical providers. Results can inform the improvement of early autism screening processes and health care communication for underrepresented families in primary care settings.

Autism spectrum disorder (ASD) is a neurodevelopmental condition made up of enduring challenges in social communication and interaction and the presence of repetitive and restricted behavior patterns. Early diagnosis of autism is crucial for timely intervention and improved long-term outcomes. This review aims to explore some of its signs and symptoms, look into some diagnostic tools, and analyze the benefits and risks associated with an early diagnosis of autism.The symptoms of ASD vary from child to child, some of which are: avoidance of eye contact, lack of response to names, excessive fear, and lack of interactive and pretend play. Early identification of these symptoms by caregivers and healthcare providers facilitates the need for diagnosis and appropriate interventions. Some screening and diagnostic tools that have been found to help make the diagnosis are the Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT-R/F), the Social Communication Questionnaire (SCQ), the Parents' Evaluation of Developmental Status (PEDS), and the Childhood Autism Rating Scale (CARS), amongst others.The benefits of early diagnosis include the opportunity for early intervention, which has been shown to enhance developmental outcomes and improve adaptive skills. Early identification allows for the implementation of specialized interventions tailored to the specific needs of individuals with autism, targeting social communication, language development, and behavioral challenges. Furthermore, early diagnosis enables families to access appropriate support services, educational resources, and community programs, facilitating better coping mechanisms, reducing parental stress, and increasing adult independence.However, early diagnosis of autism also entails certain risks. One significant concern is the potential for labeling and stigmatization, which can impact the child's self-esteem and social interactions. There is a risk of overdiagnosis or misdiagnosis, leading to unnecessary interventions and treatments. Additionally, the diagnostic process can be lengthy, complex, and emotionally challenging for families, requiring comprehensive assessments by multidisciplinary teams.This review highlights the importance of a balanced approach when considering the benefits and risks of early diagnosis. Early identification allows for timely interventions that significantly improve developmental outcomes and quality of life for individuals with autism. To mitigate the risks, it is crucial to ensure accurate and reliable diagnostic procedures, support families throughout the process, and promote societal awareness and acceptance. We also highlighted some future directions in the management of autism, including the use of biomarkers and the use of artificial intelligence and learning for diagnosing ASD.

When a child develops a psychological disorder, even a mild one, early diagnosis is essential to provide a timely and appropriate intervention that can improve the child’s symptoms and development. Early identification can prevent consequences of differing levels, in the short and long term, in the individual, in their family and in society as a whole. Hence the importance of the paediatrician’s point of view and clinical knowhow in identifying potential disorders early, but also of the parents’ views. It is therefore important to actively involve parents in initial diagnosis. In this regard, within the NASCITA Project, a study branch aimed to build a shared, active approach between parents, paediatricians and neuropsychiatrists/psychologists was activated for the 2-year health assessments (well-child visits) phase. Three tests were used: the M-CHAT-R (Modified Checklist for Autism in Toddlers, Revised) to evaluate language, social skills, behaviour, sensory areas; the PSI-SF (Parenting Stress Index - Short Form) to verify the degree of discrepancy perceived by the parent between the child’s requests and their ability to deal with them properly; the DERS (Difficulties in Emotion Regulation Scale) to highlight the difficulties of each parent in recognising, interpreting, and managing their emotions. The tests were given to 380 parents (142 couples, 215 mothers and 23 fathers) by 45 family paediatricians during the well-child visit held at two years of age. In all, 33 children (9%) resulted at risk, with a score of ≥ 3, 1 of whom was found to be at high risk. For 64 children (16.8%) at least one of the parents tested positive for PSI-SF and for 19 (5%) children at least one parent tested positive with the DERS. After combining the results obtained from the three tests and the clinical evaluation and by assessing the child’s condition with respect to those results, the paediatrician can provide the parents with a concise description of what emerged and the specialist with a summarised report. Such an effort leads to timely, shared communication within the parent-paediatrician-neuropsychiatrist triad that includes specificity of intervention and that can contribute to the effectiveness of the response.