Tools for early screening of autism spectrum disorders in primary health care - a scoping review

Mobile Application for Tracking Children with Autistic Spectrum Disorder: Content Validation and Usability

BACKGROUND

This study aims to validate the content and evaluate the usability of the Autism App for screening children with autism spectrum disorder.

METHODS

This methodological study was conducted between August 2023 and March 2024. The study included 15 experts for content validation and nine for usability evaluation, all of whom had experience in the health/technology field. Content validation data were analyzed using the Content Validity Ratio (CVR), and usability was assessed through heuristics using the MATcH-MED instrument.

RESULTS

The content validation showed satisfactory CVR values, ensuring the validity of the developed application, with suggestions for revisions regarding aims and structure. The usability evaluation yielded an overall average score of 50.9 points, classified as a high level of usability.

CONCLUSION

The results demonstrated that the App-Autismo has adequate evidence of content validity and usability. By incorporating the experts' suggestions, this tool can be tested in future research for its effectiveness and efficiency.

Validation of the autism behavior checklist in Egyptian children with autism spectrum disorder

This study was designed to validate the Arabic version of the Autism Behavior Checklist (ABC) for the Egyptian population. A total of 500 mothers of children aged 4-14 years, of whom 150 had a diagnosis of ASD, 100 with intellectual disability, and 250 typically developing children completed the ABC. The factor analysis showed that 48 of 57 ABC items yielded a five-dimensional factor structure. The ABC-Arabic version indicated acceptable internal consistency (α = 0.85) and test - retest reliability (0.82). Also, the ABC exhibited good concurrent validity and discriminative validity. A cutoff score of 58 obtained a sensitivity of 94.7% and a specificity of 92.14% for detecting children with ASD. Our findings support the use of the ABC as a valid screening measure for ASD cases, and it may promote the use of the ABC for clinical and research purposes among Arabic-speaking communities.

Machine Learning Prediction of Autism Spectrum Disorder From a Minimal Set of Medical and Background Information

Importance

Early identification of the likelihood of autism spectrum disorder (ASD) using minimal information is crucial for early diagnosis and intervention, which can affect developmental outcomes.

Objective

To develop and validate a machine learning (ML) model for predicting ASD using a minimal set of features from background and medical information and to evaluate the predictors and the utility of the ML model.

Design, Setting, and Participants

For this diagnostic study, a retrospective analysis of the Simons Foundation Powering Autism Research for Knowledge (SPARK) database, version 8 (released June 6, 2022), was conducted, including data from 30 660 participants after adjustments for missing values and class imbalances (15 330 with ASD and 15 330 without ASD). The SPARK database contains participants recruited from 31 university-affiliated research clinicals and online in 26 states in the US. All individuals with a professional ASD diagnosis and their families were eligible to participate. The model performance was validated on independent datasets from SPARK, version 10 (released July 21, 2023), and the Simons Simplex Collection (SSC), consisting of 14 790 participants, followed by phenotypic associations.

Exposures

Twenty-eight basic medical screening and background history items present before 24 months of age.

Main Outcomes and Measures

Generalizable ML prediction models were developed for detecting ASD using 4 algorithms (logistic regression, decision tree, random forest, and eXtreme Gradient Boosting [XGBoost]). Performance metrics included accuracy, area under the receiver operating characteristics curve (AUROC), sensitivity, specificity, positive predictive value (PPV), and F1 score, offering a comprehensive assessment of the predictive accuracy of the model. Explainable AI methods were applied to determine the effect of individual features in predicting ASD as secondary outcomes, enhancing the interpretability of the best-performing model. The secondary outcome analyses were further complemented by examining differences in various phenotypic measures using nonparametric statistical methods, providing insights into the ability of the model to differentiate between different presentations of ASD.

Results

The study included 19 477 (63.5%) male and 11 183 (36.5%) female participants (mean [SD] age, 106 [62] months). The mean (SD) age was 113 (68) months for the ASD group and 100 (55) months for the non-ASD group. The XGBoost (termed AutMedAI) model demonstrated strong performance with an AUROC score of 0.895, sensitivity of 0.805, specificity of 0.829, and PPV of 0.897. Developmental milestones and eating behavior were the most important predictors. Validation on independent cohorts showed an AUROC of 0.790, indicating good generalizability.

Conclusions and Relevance

In this diagnostic study of ML prediction of ASD, robust model performance was observed to identify autistic individuals with more symptoms and lower cognitive levels. The robustness and ML model generalizability results are promising for further validation and use in clinical and population settings.

Autism Spectrum Disorders: Etiology, Epidemiology, and Challenges for Public Health

Autism spectrum disorder (ASD) is a growing public health problem. American psychiatrist Leo Kanner is considered the "father of autism." ASD encompasses a range of neurodevelopmental disorders that last throughout life. Symptoms of ASD include impairments in social skills, including specific repetitive behaviors, as well as abnormal sensory responses. The clinical symptoms of ASD vary among patients. Their severity also differs, both in the area of social communication and cognitive functioning. The etiology of ASD is still unclear, although a role is attributed to both genetic and environmental factors. According to the World Health Organization, 1/100 children have ASD, but these estimates vary depending on the methodology used. Nevertheless, early detection of ASD and initiation of appropriate therapy may be essential in the continued functioning of patients and their families. The purpose of this article is to provide an overview of current knowledge about autism spectrum disorders. We discuss factors associated with autism and the prevalence of ASD in various parts of the world, and identify the most common diseases comorbid with ASD, pointing to limitations in the quality of life of patients with ASD and their families.

Scoping review on the role of the family doctor in the prevention and care of patients with foetal alcohol spectrum disorder

BACKGROUND

Foetal alcohol spectrum disorder (FASD) is the leading preventable cause of nongenetic mental disability. Given the patient care pathway, the General Practitioner (GP) is in the front line of prevention and identification of FASD. Acknowledging the importance of the prevalence of FASD, general practitioners are in the front line both for the detection and diagnosis of FASD and for the message of prevention to women of childbearing age as well as for the follow-up.

OBJECTIVES

The main objective of the scoping review was to propose a reference for interventions that can be implemented by a GP with women of childbearing age, their partners and patients with FASD. The final aim of this review is to contribute to the improvement of knowledge and quality of care of patients with FASD.

METHODS

A scoping review was performed using databases of peer-reviewed articles following PRISMA guidelines. The search strategy was based on the selection and consultation of articles on five digital resources. The advanced search of these publications was established using the keywords for different variations of FASD: "fetal alcohol syndrome," "fetal alcohol spectrum disorder," "general medicine," "primary care," "primary care"; searched in French and English.

RESULTS

Twenty-three articles meeting the search criteria were selected. The interventions of GPs in the management of patients with FASD are multiple: prevention, identification, diagnosis, follow-up, education, and the role of coordinator for patients, their families, and pregnant women and their partners. FASD seems still underdiagnosed.

CONCLUSION

The interventions of GPs in the management of patients with FASD are comprehensive: prevention, identification, diagnosis, follow-up, education, and the role of coordinator for patients, their families, and pregnant women and their partners. Prevention interventions would decrease the incidence of FASD, thereby reducing the incidence of mental retardation, developmental delays, and social, educational and legal issues. A further study with a cluster randomized trial with a group of primary care practitioners trained in screening for alcohol use during pregnancy would be useful to measure the impact of training on the alcohol use of women of childbearing age and on the clinical status of their children.

Autism Spectrum Disorder: Brain Areas Involved, Neurobiological Mechanisms, Diagnoses and Therapies

Autism spectrum disorder (ASD), affecting over 2% of the pre-school children population, includes an important fraction of the conditions accounting for the heterogeneity of autism. The disease was discovered 75 years ago, and the present review, based on critical evaluations of the recognized ASD studies from the beginning of 1990, has been further developed by the comparative analyses of the research and clinical reports, which have grown progressively in recent years up to late 2023. The tools necessary for the identification of the ASD disease and its related clinical pathologies are genetic and epigenetic mutations affected by the specific interaction with transcription factors and chromatin remodeling processes occurring within specific complexes of brain neurons. Most often, the ensuing effects induce the inhibition/excitation of synaptic structures sustained primarily, at dendritic fibers, by alterations of flat and spine response sites. These effects are relevant because synapses, established by specific interactions of neurons with glial cells, operate as early and key targets of ASD. The pathology of children is often suspected by parents and communities and then confirmed by ensuing experiences. The final diagnoses of children and mature patients are then completed by the combination of neuropsychological (cognitive) tests and electro-/magneto-encephalography studies developed in specialized centers. ASD comorbidities, induced by processes such as anxieties, depressions, hyperactivities, and sleep defects, interact with and reinforce other brain diseases, especially schizophrenia. Advanced therapies, prescribed to children and adult patients for the control of ASD symptoms and disease, are based on the combination of well-known brain drugs with classical tools of neurologic and psychiatric practice. Overall, this review reports and discusses the advanced knowledge about the biological and medical properties of ASD.

Insights on dental care management and prevention in children with autism spectrum disorder (ASD). What is new?

Autistic subjects represent a severe concern to dentistry due to the considerable difficulty in managing their oral health, maintaining routine toothbrushing, and preventing dental and periodontal problems. The social and economic burden of managing dental care in autism spectrum disorder (ASD) children is particularly cumbersome for families and public and private health expenditure, especially when children reach the dentist following a late diagnosis with evident oral health problems. An early diagnosis of ASD helps dentists better address these children's oral health. Unfortunately, insufficient attention is paid to the training and education of general pediatricians, dentists, and dental hygienists, allowing them to get to approach the different clinical aspects of ASD. Usually, children diagnosed with ASD are scheduled for dental appointments like their neurotypical peers, whereas their needs are typically complex and personalized. Scant attention is also devoted to these patients by commercial manufacturers of dental products and devices for oral hygiene and prevention of caries and periodontal diseases, leaving parents without the support and often failing when they address the oral health of autistic children. The difficulties of oral care do not derive simply from the behavior of ASD patients, as is commonly assumed, and therefore cannot be overcome solely by the patience and attention of parents and dentists. Genetics, dietary habits, sensory impairments, and cognition disorders are other causes contributing in various degrees to the impact on the mood and psychological reactions of autistic children towards dentists. How can we prevent teeth caries, periodontal disorders, and other oral health impairments by properly managing ASD children? This manuscript gives an up-to-date overview of these problems and helps to provide good remarks.