Diagnosis Of Autism In Children Research Articles

Diagnosis of Autism in Children Based on their Gait Pattern and Movement Signs Using the Kinect Sensor

Abstract Background: Autism spectrum disorders are a type of developmental disorder that primarily disrupt social interactions and communications. Autism has no treatment, but early diagnosis of it is crucial to reduce these effects. The incidence of autism is represented in repetitive patterns of children’s motion. When walking, these children tighten their muscles and cannot control and maintain their body position. Autism is not only a mental health disorder but also a movement disorder. Method: This study aims to identify autistic children based on data recorded from their gait patterns using a Kinect sensor. The database used in this study comprises walking information, such as joint positions and angles between joints, of 50 autistic and 50 healthy children. Two groups of features were extracted from the Kinect data in this study. The first one was statistical features of joints’ position and angles between joints. The second group was the features based on medical knowledge about autistic children’s behaviors. Then, extracted features were evaluated through statistical tests, and optimal features were selected. Finally, these selected features were classified by naïve Bayes, support vector machine, k-nearest neighbors, and ensemble classifier. Results: The highest classification accuracy for medical knowledge-based features was 87% with 86% sensitivity and 88% specificity using an ensemble classifier; for statistical features, 84% of accuracy was obtained with 86% sensitivity and 82% specificity using naïve Bayes. Conclusion: The dimension of the resulted feature vector based on autistic children’s medical knowledge was 16, with an accuracy of 87%, showing the superiority of these features compared to 42 statistical features.

The development, feasibility and acceptability of Empower-Autism: A new psychoeducational and psychotherapeutic programme for caregivers of children recently diagnosed with autism.

What is already known about the topic?Parents and carers face many challenges following their child's autism diagnosis. They often look for information, and social and emotional support. There has been relatively little research into how best to provide this support and this means that there is no evidence to guide the delivery of services. Studies have suggested that an approach called Acceptance and Commitment Therapy can help parents and carers with their adjustment and emotional wellbeing.What does this article add?This article describes the development of a new group-based programme to address the diverse needs of caregivers after their child's autism diagnosis. The new programme was developed with caregivers, autistic people and professionals. It was called Empower-Autism and contained lots of information about autism and strategies to support autistic children, alongside therapeutic aspects based on Acceptance and Commitment Therapy. The programme was delivered to 29 parents/carers in three groups. Attendance at the groups was satisfactory. Both parents/carers and facilitators liked and valued the programme and found it accessible. They made suggestions for improvements. After the programme, parents and carers described improved wellbeing. They felt more positive and more connected to other people. They also described parenting their child in a more informed and sensitive way.Implications for practice, research or policyThe new programme is being tested within a large clinical trial. If there are positive results, the programme could be recommended for delivery and this would address an important gap in evidence-based practice.

Does hope mediate the relationship between parent's resolution of their child's autism diagnosis and parental stress.

Resolution of a child's diagnosis, the process of accepting and adjusting to the reality of a child's significant diagnosis, has been often associated with decreased parental stress. Hope, a potential buffer against psychological distress, has been suggested as a potential explanation for this relationship. However, the mediating role of hope in the relationship between resolution of diagnosis and parental stress has not been explored. This study aimed to examine whether four types of hope (child, parental, societal, denial of diagnosis) mediated the relationship between resolution to an autism diagnosis and reduced parental stress. Participants included 73 parents (Mage = 43.22, SD = 7.69, female 97.3%) of autistic children (Mage = 11.15, SD = 4.56, male = 67.1%). Resolution to diagnosis was negatively and significantly correlated with resolution to diagnosis, as well as child, parental and societal hope. These three hopes were also significantly and negatively correlated with parental stress. Importantly, when controlling for level of support and autism awareness, parental hope mediated the relationship between resolution to diagnosis and parental stress. Denial of diagnosis was not correlated with resolution or parental stress but did have significant but weak associate with the other hopes. These findings suggest that hope based on parent's abilities to support their child and be supported themselves play an important role in parental stress once parents are more resolved to their child's diagnosis. Supporting parents to manage factors associated with supporting their child's needs, may benefit parents of autistic children.

Studi Pustaka: Deskripsi Penerimaan Keluarga terhadap Pengungkapan Anak Autisme

According to Loftus (2024), in the United States, 1 out of 36 children were diagnosed with autism in 2023, which is an increase compared to 2020 when it was 1 out of 44 children. Disclosure by healthcare professionals elicits various emotions within families such as disbelief, blaming God or oneself, ultimately leading to denial and neglect of children with autism. However, the family's role is crucial in the development of children, especially those with special needs like autism. The author here writes about the various emotional reactions of family members and the roles they undertake after the disclosure of a child's autism diagnosis, aiming to uncover the extent of family emotions and their role in the growth of children with autism. This research is conducted using a descriptive literature review method by describing and critiquing previously published journals. The results of this study indicate that the emotional reactions of family members are mostly negative, but positive emotional regulation can lead to better acceptance of the child. Stigmatization is one factor that contributes to negative emotions, but after receiving social support, families seek information about autism, followed by subsequent roles that help children with autism become independent and adaptive..

Utility of the 3Di short version in the identification and diagnosis of autism in children at the Kenyan coast.

The precise epidemiological burden of autism is unknown because of the limited capacity to identify and diagnose the disorder in resource-constrained settings, related in part to a lack of appropriate standardised assessment tools and health care experts. We assessed the reliability, validity, and diagnostic accuracy of the Developmental Diagnostic Dimensional Interview (3Di) in a rural setting on the Kenyan coast. Using a large community survey of neurodevelopmental disorders (NDDs), we administered the 3Di to 2,110 children aged between 6 years and 9 years who screened positive or negative for any NDD and selected 242 who had specific symptoms suggestive of autism based on parental report and the screening tools for review by a child and adolescent psychiatrist. On the basis of recorded video, a multi-disciplinary team applied the Autism Diagnostic Observation Schedule to establish an autism diagnosis. Internal consistency was used to examine the reliability of the Swahili version of the 3Di, tetrachoric correlations to determine criterion validity, structural equation modelling to evaluate factorial structure and receiver operating characteristic analysis to calculate diagnostic accuracy against Diagnostic Statistical Manual of Mental Disorders (DSM) diagnosis. The reliability coefficients for 3Di were excellent for the entire scale {McDonald's omega (ω) = 0.83 [95% confidence interval (CI) 0.79-0.91]}. A higher-order three-factor DSM-IV-TR model showed an adequate fit with the model, improving greatly after retaining high-loading items and correlated items. A higher-order two-factor DSM-5 model also showed an adequate fit. There were weak to satisfactory criterion validity scores [tetrachoric rho = 0.38 (p = 0.049) and 0.59 (p = 0.014)] and good diagnostic accuracy metrics [area under the curve = 0.75 (95% CI: 0.54-0.96) and 0.61 (95% CI: 0.49-0.73] for 3Di against the DSM criteria. The 3Di had a moderate sensitivity [66.7% (95% CI: 0.22-0.96)] and a good specificity [82.5% (95% CI: 0.74-0.89)], when compared with the DSM-5. However, we observed poor sensitivity [38.9% (95% CI: 0.17-0.64)] and good specificity [83.5% (95% CI: 0.74-0.91)] against DSM-IV-TR. The Swahili version of the 3Di provides information on autism traits, which may be helpful for descriptive research of endophenotypes, for instance. However, for accuracy in newly diagnosed autism, it should be complemented by other tools, e.g., observational clinical judgment using the DSM criteria or assessments such as the Autism Diagnostic Observation Schedule. The construct validity of the Swahili 3Di for some domains, e.g., communication, should be explored in future studies.

Regional-asymmetric Adaptive Graph Convolutional Neural Network for Diagnosis of Autism in Children with Resting-state EEG.

Currently, resting-state electroencephalography (rs-EEG) has become an effective and low-cost evaluation way to identify autism spectrum disorders (ASD) in children. However, it is of great challenge to extract useful features from raw rs-EEG data to improve diagnosis performance. Traditional methods mainly rely on the design of manual feature extractors and classifiers, which are separately performed and cannot be optimized simultaneously. To this end, this paper proposes a new end-to-end diagnostic method based on a recently emerged graph convolutional neural network for the diagnosis of ASD in children. Inspired by related neuroscience findings on the abnormal brain functional connectivity and hemispheric asymmetry characteristics observed in autism patients, we design a new Regional-asymmetric Adaptive Graph Convolutional Neural Network (RAGNN). It utilizes a hierarchical feature extraction and fusion process to learn separable spatiotemporal EEG features from different brain regions, two hemispheres, and a global brain. In the temporal feature extraction section, we utilize a convolutional layer that spans from the brain area to the hemisphere. This allows for effectively capturing temporal features both within and between brain areas. To better capture spatial characteristics of multi-channel EEG signals, we employ adaptive graph convolutional learning to capture non-Euclidean features within the brain's hemispheres. Additionally, an attention layer is introduced to highlight different contributions of the left and right hemispheres, and the fused features are used for classification. We conducted a subject-independent cross-validation experiment on rs-EEG data from 45 children with ASD and 45 typically developing (TD) children. Experimental results have shown that our proposed RAGNN model outperformed several existing deep learning-based methods (ShaollowNet, EEGNet, TSception, ST-GCN, and CGRU-MDGN).

Maternal autoimmune diseases and mental disorders in children and adolescents

IntroductionThe influence of maternal autoimmunity mediators on child development and brain function has been the subject of several studies. Clinically, most have focused on the association between maternal autoimmunity and the diagnosis of autism in children. On the other hand, data are rarer concerning the rest of the mental disorders and mainly, they are obtained from small cohorts.ObjectivesThe aim of this study is to discuss the association between the presence of autoimmune pathology in the mother and the development of mental disorders in the childMethodswe conducted our study through a descriptive study of six clinical cases.Results80 % the patients treated were male57% had a characterized depressive disorder34% had ADHD9 % had ASDConclusionsMaternal autoimmune diseases were associated with increased mental disorders in children. These results suggest a possible shared genetic vulnerability between the two conditions or a potential role of maternal immune activation in the expression of neurodevelopmental disorders in children.Disclosure of InterestNone Declared

Potential dynamic regional brain biomarkers for early discrimination of autism and language development delay in toddlers.

The early diagnosis of autism in children is particularly important. However, there is no obvious objective indices for the diagnosis of autism spectrum disorder (ASD), especially in toddlers aged 1-3 years with language development delay (LDD). The early differential diagnosis of ASD is challenging. To examine differences in the dynamic characteristics of regional neural activity in toddlers with ASD and LDD, and whether the differences can be used as an imaging biomarker for the early differential diagnosis of ASD and LDD. Dynamic regional homogeneity (dReHo) and dynamic amplitude of low-frequency fluctuations (dALFF) in 55 children with ASD and 31 with LDD, aged 1-3 years, were compared. The correlations between ASD symptoms and the values of dReHo/dALFF within regions showing significant between-group differences were analyzed in ASD group. We further assessed the accuracy of dynamic regional neural activity alterations to distinguish ASD from LDD using receiver operating characteristic (ROC) analysis. Compared with the LDD group, the ASD group showed increased dReHo in the left cerebellum_8/Crust2 and right cerebellum_Crust2, and decreased dReHo in the right middle frontal gyrus (MFG) and post-central gyrus. Patients with ASD also exhibited decreased dALFF in the right middle temporal gyrus (MFG) and right precuneus. Moreover, the Childhood Autism Rating Scale score was negatively correlated with the dReHo of the left cerebellum_8/crust2 and right cerebellum_crust2. The dReHo value of the right MFG was negatively correlated with social self-help of the Autism Behavior Checklist score. The pattern of resting-state regional neural activity variability was different between toddlers with ASD and those with LDD. Dynamic regional indices might be novel neuroimaging biomarkers that allow differentiation of ASD from LDD in toddlers.

Using the syndrome approach to the diagnosis of autism in children

Autism spectrum disorders in children is a very urgent problem. Today, there is an increase in the number of children suffering from autism spectrum disorders around the world. The relevance of early diagnosis of autism spectrum disorders for timely treatment and correction is high. However, the diagnostic criteria for ASD require an assessment of certain psychomotor skills in a child, which mature much later than necessary for a timely diagnosis, so the diagnosis is made by 5-7 years. New clinical guidelines suggest that primary screening should be performed by a pediatrician. However, practice shows that in reality this does not happen. The reason for this is not only a contradiction in the diagnostic criteria, but also the current ICD-10 classification, which does not reflect the pathogenetic processes in the child's body. Despite this, new clinical guidelines recognize the role of genetic disorders and epigenetic factors in the development of autism spectrum disorders. In this regard, it is proposed to consider autism spectrum disorders as a syndrome that accompanies various genetic disorders, both chromosomal and monogenic anomalies. This approach enables early diagnosis of autism spectrum disorders, as well as the development of treatment and correction methods based on pathogenetic disorders. Currently, more than 100 genes associated with autism are known. In the above studies, it was noted that the polygenic nature of disorders in autism does not allow focusing on phenotypic features. Probably, this is the reason for the difficulties in diagnosing autism by external signs and the low efficiency of the currently known screening methods for diagnosing autism spectrum disorders. Therefore, autism spectrum disorders must be considered from the point of view of pathogenetic changes in the child's body, usually of a hereditary nature, which will allow us to offer effective methods of diagnosis, treatment and correction.

Application of Quantitative Magnetic Resonance Imaging in the Diagnosis of Autism in Children.

ObjectiveTo explore the application of quantitative magnetic resonance imaging in the diagnosis of autism in children.MethodsSixty autistic children aged 2–3 years and 60 age- and sex-matched healthy children participated in the study. All the children were scanned using head MRI conventional sequences, 3D-T1, diffusion kurtosis imaging (DKI), enhanced T2*- weighted magnetic resonance angiography (ESWAN) and 3D-pseudo continuous Arterial Spin-Labeled (3D-pcASL) sequences. The quantitative susceptibility mapping (QSM), cerebral blood flow (CBF), and brain microstructure of each brain area were compared between the groups, and correlations were analyzed.ResultsThe iron content and cerebral blood flow in the frontal lobe, temporal lobe, hippocampus, caudate nucleus, substantia nigra, and red nucleus of the study group were lower than those in the corresponding brain areas of the control group (P < 0.05). The mean kurtosis (MK), radial kurtosis (RK), and axial kurtosis (AK) values of the frontal lobe, temporal lobe, putamen, hippocampus, caudate nucleus, substantia nigra, and red nucleus in the study group were lower than those of the corresponding brain areas in the control group (P < 0.05). The mean diffusivity (MD) and fractional anisotropy of kurtosis (FAK) values of the frontal lobe, temporal lobe and hippocampus in the control group were lower than those in the corresponding brain areas in the study group (P < 0.05). The values of CBF, QSM, and DKI in frontal lobe, temporal lobe and hippocampus could distinguish ASD children (AUC > 0.5, P < 0.05), among which multimodal technology (QSM, CBF, DKI) had the highest AUC (0.917) and DKI had the lowest AUC (0.642).ConclusionQuantitative magnetic resonance imaging (including QSM, 3D-pcASL, and DKI) can detect abnormalities in the iron content, cerebral blood flow and brain microstructure in young autistic children, multimodal technology (QSM, CBF, DKI) could be considered as the first choice of imaging diagnostic technology.Clinical Trial Registration[http://www.chictr.org.cn/searchprojen.aspx], identifier [ChiCTR2000029699].

Challenges Surrounding the Diagnosis of Autism in Children.

This comprehensive thematic review aims to highlight and familiarize readers with the challenges and pitfalls encountered in differential diagnosis of autism spectrum disorders (ASD) in children to facilitate the process of accurate identification by stakeholders. Accordingly, articles that best answer our questions and highlight our concerns were chosen from well-established publishers with prime peer reviewed journals. Included are studies showing alternate views of the issues so as to point readers to other possibilities. ASD, a complex dynamic biological-neurodevelopmental disorder, is underscored by its heterogeneous symptomology, severity, and phenotypes – all characterized by social communication deficits and presence of restricted interests and repetitive behaviours (RRBs), the core symptoms in ASD. Language and intellectual capacities do not form ASD core symptoms although vary considerably. Accurate identification is challenging as ASD is often enmeshed with other neurodevelopmental disorders, and medical comorbidities, a situation now recognized as the rule rather than the exception in child psychiatry and developmental medicine. ASD is a disorder with varying performance and severity of symptoms over time, including unexpected loss of early skills, and lost diagnosis in some children following treatment. The review reiterates the urgency in accurate diagnosis in face of the rapid rise in ASD prevalence globally, and risk-increase in delayed or denied treatment with undesirable life-long consequences for most of the affected children. In addition, a call for change is advised to circumvent the ethical dilemma posed by the present “deficit model” in ASD diagnosis. Here, ASD prevalence is presented first, followed by emphasis on importance of accurate early diagnosis, and challenges in its accomplishment due to flaws in diagnostic instruments and other contributing factors. Next follow the required criteria for accurate identification, and its difficulties attributed to comorbid conditions, gender differences, and socio-economic and cultural influences. The conclusion includes future directions and a take away message.

Brief Report: The Characterization of Medical Comorbidity Prior to Autism Diagnosis in Children Before Age Two.

In autism spectrum disorder (ASD), medical conditions in infancy could be predictive markers for later ASD diagnosis. In this study, electronic medical records of 579 autistic individuals and 1897 matched controls prior to age 2 were analyzed for potential predictive conditions. Using a novel tool, the relative association of each condition in the autistic group was compared to the control group using logistic regressions across medical records. Generalized convulsive epilepsy, nystagmus, lack of normal physiological development, delayed milestones, and strabismus were more likely in those later diagnosed with ASD while perinatal jaundice was less likely to be associated. Lesser-known conditions, such as strabismus and nystagmus, may point to novel predictive co-occurring condition profiles which could improve screening practices for ASD.

Implementasi Metode Forward chaining dan Certainty factor dalam Mendiagnosa Autisme Anak Berbasis Web

Lack of parental or community knowledge of the symptoms of autism in their children results in neglected early detection. This of course can be too late in the treatment of autism in the future. Therefore, this study aims to design a web-based expert system for diagnosing children's autism. The development model used to design an autism expert system in children is a waterfall and implements the forward chaining method and the certainty factor method. While the data collection methods consisted of interview methods and literature study methods. From the results of the calculation test, it is concluded that the results of manual calculations and the web-based application of an expert system for autism diagnosis in children are the same as the results of the 98% confidence level. With this web-based autism expert system in children, it is hoped that it can help parents or the community to detect autism in their children early on.Keywords:Autism, Expert System, Web Based, Forward chaining Method, Certainty factor Method.

A influência do diagnóstico de autismo na trajetória profissional das mães da Grande Florianópolis

As Mulheres que se tornam mães e se deparam com o diagnóstico de autismo dos filhos, tem que adequar a vida à uma nova realidade. Dentro dessa mudança, inclui-se o assunto carreira profissional, no qual podem ou não interrompê-la ou até mesmo mudá-la em função da situação. Diante do exposto, o objetivo deste trabalho foi o de compreender a influência do diagnóstico de autismo do filho sobre a trajetória profissional das mães pertencentes à região da Grande Florianópolis. No que tange à metodologia, informa-se que foi um estudo aplicado, exploratório e quantitativo. Como estratégia de coleta de dados, utilizou-se de um questionário com 76 questões, sendo o mesmo enviado para 379 mães de autistas. O contingente de respondentes foi compatível com a amostra mínima projetada. Os resultados mostraram os perfis e as mudanças ocorridas após o recebimento do diagnóstico dos filhos o que, ao final, permitiu-se a identificação de similaridades e disparidades das trajetórias profissionais destas mulheres, o que permitiu o entendimento de suas escolhas.

Couples' Experiences of Parenting a Child After an Autism Diagnosis: A Qualitative Study.

After a child is diagnosed with autism, parents' relationships are impacted as they reorganize their daily lives to support their child's specific needs. A better understanding of parenting couples' adaptation is needed to accompany them during this period. This qualitative study explored couples' experiences after their child's autism diagnosis. An inductive thematic analysis among ten couple interviews (N = 20) revealed three key themes: emotional experiences, external support, and adaptation. Overall, the quality of couples' relationships before having a child influenced their relationship after the diagnosis. In general, parents presented complementary coparenting roles, while different opinions about how to raise the child strained their relationship. Helping parents adapt to a diagnosis together could prove to be important for future interventions and research.

4420 Characterizing medical comorbidity prior to autism diagnosis in children before age two.

OBJECTIVES/GOALS: Autism spectrum disorder (ASD) is a developmental disorder with a high financial and personal burden. Individuals with ASD experience significant comorbid medical conditions. We identified conditions that appear prior to ASD diagnosis in order to potentially improve early screening practices. METHODS/STUDY POPULATION: We used electronic health record data from an anonymized database at Vanderbilt University Medical Center for individuals with ASD and matched controls to analyze comorbid conditions prior to an ASD diagnosis. Data were censored to include only individuals who first appeared in the databank prior to two years of age (ntotal = 1551, ncontrols = 976, nASD = 575). Comorbidities (~1800 conditions) were compared between the ASD and matched control group using a novel tool (pyPheWAS) to examine presence, count, and duration of comorbidities that occurred between 0-2 years old and before ASD diagnosis. RESULTS/ANTICIPATED RESULTS: Convulsions (p = 0.000404, ß = 0.807), constipation (p = 0.000789, ß = 0.894), and strabismus (p = 0.00243, ß = 1.155) were the most significant comorbid conditions prior to age 2 in individuals who would later be diagnosed with ASD. The group with ASD also had more visits associated with convulsions (p = 0.00511, ß = 0.195), diseases of the esophagus (p = 0.0117, ß = 1.675), and allergic reactions to food (p = 0.0119, ß = 0.540) prior to their diagnosis. The ASD group was also seen for a longer duration regarding convulsions (p = 0.000273, ß = 0.695), constipation (p = 0.00157, ß = 0.712), and malaise and fatigue (p = 0.00188, ß = 0.903) before ASD diagnosis. DISCUSSION/SIGNIFICANCE OF IMPACT: Precise comorbid condition profiles in early childhood may help uncover biomarkers leading to better prediction of a future ASD diagnosis. Medical conditions that precede the onset of measurable behavioral symptoms may enhance early screening, treatment, and intervention in ASD.

Biographical disruption or cohesion?: How parents deal with their child's autism diagnosis

Currently, we are witnessing a precipitous rise in autism diagnoses among children, and several bodies of sociological research are attempting to explain this development. However, the experiences within parental contexts have been inadequately examined; that is, how parents feel about and act upon the awareness of their child's autism diagnosis. Drawing upon a qualitative study among Danish parents of 20 children recently diagnosed with autism, this paper contributes with situated insights into parents' experiences. We identify a spectrum of feelings towards the autism diagnosis, including both relief and grief. In the absence of theoretical notions drawing attention to how a child's diagnosis influences parents' self-conceptions and understandings of their child, we develop the concept of ‘parent-biographical disruption’: the parents' rethinking of themselves and their child that might be caused by a chronic condition such as autism. Based on the variety of findings, we discuss what we call ‘parent-biographical cohesion’ as a counterpart to ‘disruption’. By ‘cohesion’ we refer to the diagnostic awareness potentially creating clarification for parents about the past, present and future parenting of their child instead of disrupting their self-understandings as parents. In this way, through the notion of a parental-biographical spectrum of disruption and cohesion, we emphasize the diversity in how parents deal with a child's autism diagnosis and the variety of needs for rethinking parental biographies in the wake of a diagnosis.

Using Multilayer Fuzzy Cognitive Maps to diagnose Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is comprised of a group of heterogeneous neurodevelopmental conditions, typically characterized by a triad of symptoms consisting of (1) impaired communication, (2) restricted interests, and (3) repetitive and stereotypical behavior pattern. An accurate and early diagnosis of autism can provide the basis for an appropriate educational and treatment program. In this work, we propose a computational model using a Multilayer Fuzzy Cognitive Map (hereafter referred to as MFCM) based on standardized behavioral assessments diagnosing the ASD (MFCM-ASD). The two standards used in the model are: the Autism Diagnostic Observation Schedule, Second Edition (ADOS2), and the Autism Diagnostic Interview Revised (ADIR). The MFCM’s are a soft computing technique characterized by robust properties that make it an effective technique for medical decision support systems. For the evaluation of the MFCM-ASD model, we have used real datasets of diagnosed cases, so as to compare against other method/approaches. Initial experiments demonstrated that the proposed model outperforms conventional Fuzzy Cognitive Maps (FCMs) for ASD diagnosis. Our MFCM-ASD model serves as a diagnostic tool required to support the medical decisions when determining the correct diagnosis of Autism in children with different cognitive characteristics.

The association between socioeconomic status and autism diagnosis in the United Kingdom for children aged 5-8 years of age: Findings from the Born in Bradford cohort.

There has been recent interest in the relationship between socioeconomic status and the diagnosis of autism in children. Studies in the United States have found lower rates of autism diagnosis associated with lower socioeconomic status, while studies in other countries report no association, or the opposite. This article aims to contribute to the understanding of this relationship in the United Kingdom. Using data from the Born in Bradford cohort, comprising 13,857 children born between 2007 and 2011, it was found that children of mothers educated to A-level or above had twice the rate of autism diagnosis, 1.5% of children (95% confidence interval: 1.1%, 1.9%) compared to children of mothers with lower levels of education status 0.7% (95% confidence interval: 0.5%, 0.9%). No statistically significant relationship between income status or neighbourhood material deprivation was found after controlling for mothers education status. The results suggest a substantial level of underdiagnosis for children of lower education status mothers, though further research is required to determine the extent to which this is replicated across the United Kingdom. Tackling inequalities in autism diagnosis will require action, which could include increased education, awareness, further exploration of the usefulness of screening programmes and the provision of more accessible support services.

Cost of assessing a child for possible autism spectrum disorder? An observational study of current practice in child development centres in the UK

ObjectiveUK guidelines recommend that diagnosis of autism in children requires assessment by a multidisciplinary team. With growing numbers of referrals for assessment, diagnostic services have been under increasing pressure to...