"I was Confused … and Still am" Barriers Impacting the Help-Seeking Pathway for an Autism Diagnosis in Urban North India: A Mixed Methods Study

Digital tools for direct assessment of autism risk during early childhood: A systematic review

LAY ABSTRACT

The challenge of finding autistic children, and finding them early enough to make a difference for them and their families, becomes all the greater in parts of the world where human and material resources are in short supply. Poverty of resources delays interventions, translating into a poverty of outcomes. Digital tools carry potential to lessen this delay because they can be administered by non-specialists in children's homes, schools or other everyday environments, they can measure a wide range of autistic behaviours objectively and they can automate analysis without requiring an expert in computers or statistics. This literature review aimed to identify and describe digital tools for screening children who may be at risk for autism. These tools are predominantly at the 'proof-of-concept' stage. Both portable (laptops, mobile phones, smart toys) and fixed (desktop computers, virtual-reality platforms) technologies are used to present computerised games, or to record children's behaviours or speech. Computerised analysis of children's interactions with these technologies differentiates children with and without autism, with promising results. Tasks assessing social responses and hand and body movements are the most reliable in distinguishing autistic from typically developing children. Such digital tools hold immense potential for early identification of autism spectrum disorder risk at a large scale. Next steps should be to further validate these tools and to evaluate their applicability in a variety of settings. Crucially, stakeholders from underserved communities globally must be involved in this research, lest it fail to capture the issues that these stakeholders are facing.

Caregiver Perceptions of Autism and Neurodevelopmental Disabilities in New Delhi, India

Evidence suggests that parenting an autistic child or a child with neurodevelopmental disabilities can be more challenging than parenting a child meeting their developmental milestones, especially when there is a dearth of support services, such as in low- and middle-income countries (LMICs). Despite the majority of the world's children residing in LMICs, there are limited studies examining the understanding of developmental disorders and autism in these regions. We therefore aim to investigate perceptions of autism and developmental disabilities in caregivers of children in an urban setting in New Delhi, India. Thirteen semi-structured interviews with parents/caregivers of children were conducted in three groups: (1) caregivers with a child with a diagnosis of autism spectrum disorder (ASD); (2) caregivers with a child with a diagnosis of intellectual disability (ID); (3) and caregivers with children meeting their developmental milestones. Transcripts were analysed using framework analysis. Three themes on the impact of cultural and contextual factors on the recognition, interpretation, and reporting of autistic symptoms are discussed, and additional themes focus on the impact of diagnosis and family support. Our findings highlighted a vital need for greater community awareness and recognition of autism in India, for example through community and healthcare training, which may help to reduce stigma and facilitate wider family support.

Diagnosing autism in low-income countries: Clinical record-based analysis in Sri Lanka

Use of autism diagnosing standards in low-income countries (LICs) are restricted due to the high price and unavailability of trained health professionals. Furthermore, these standards are heavily skewed towards developed countries and LICs are underrepresented. Due to such constraints, many LICs use their own ways of assessing autism. This is the first retrospective study to analyze such local practices in Sri Lanka. The study was conducted at Ward 19B of Lady Ridgeway Hospital (LRH) using the clinical forms filled for diagnosing ASD. In this study, 356 records were analyzed, from which 79.5% were boys and the median age was 33 months. For each child, the clinical form together with the Childhood Autism Rating Scale (CARS) value were recorded. In this study, a Clinically Derived Autism Score (CDAS) is obtained from the clinical forms. Scatter plot and Pearson product moment correlation coefficient were used to benchmark CDAS with CARS, and it was found CDAS to be positively and moderately correlated with CARS. In identifying the significant variables, a logistic regression model was built based on clinically observed data and it evidenced that "Eye Contact," "Interaction with Others," "Pointing," "Flapping of Hands," "Request for Needs," "Rotate Wheels," and "Line up Things" variables as the most significant variables in diagnosing autism. Based on these significant predictors, the classification tree was built. The pruned tree depicts a set of rules, which could be used in similar clinical environments to screen for autism. LAY SUMMARY: Screening and diagnosing autism in low-income countries such as Sri Lanka has always been a challenge due to limited resources and not being able to afford global standards. Due to these challenges, locally developed clinical forms have been used. This study is the first to analyze a clinical record set for autism in Sri Lanka to benchmark the local clinic form with a global standard. Furthermore, this study identifies the most significant diagnostic symptoms for children and based on these significant features, a simple set of IF-THEN rules are derived which could be used for screening autism in a similar clinical environment by health officials in the absence of consultants.