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In response to the COVID-19 pandemic, expectant parents experienced changes in the availability and uptake of both National Health Service (NHS) community and hospital-based healthcare. To examine how COVID-19 and its societal related restrictions have impacted the provision of healthcare support for pregnant women during the COVID-19 pandemic. A thematic analysis using an inductive approach was undertaken using data from open-ended responses to the national COVID in Context of Pregnancy, Infancy and Parenting (CoCoPIP) Study online survey (n = 507 families). The overarching theme identified was the way in which the changes to healthcare provision increased parents' anxiety levels, and feelings of not being supported. Five sub-themes, associated with the first wave of the pandemic, were identified: (1) rushed and/or fewer antenatal appointments, (2) lack of sympathy from healthcare workers, (3) lack of face-to-face appointments, (4) requirement to attend appointments without a partner, and (5) requirement to use PPE. A sentiment analysis, that used quantitative techniques, revealed participant responses to be predominantly negative (50.1%), with a smaller proportion of positive (21.8%) and neutral (28.1%) responses found. This study provides evidence indicating that the changes to healthcare services for pregnant women during the pandemic increased feelings of anxiety and have left women feeling inadequately supported. Our findings highlight the need for compensatory social and emotional support for new and expectant parents while COVID-19 related restrictions continue to impact on family life and society. [ABSTRACT FROM AUTHOR]

A diagnosis of autism typically depends on clinical assessments by highly trained professionals. This high resource demand poses a challenge in low-resource settings. Digital assessment of neurodevelopmental symptoms by non-specialists provides a potential avenue to address this challenge. This cross-sectional case-control field study establishes proof of principle for such a digital assessment. We developed and tested an app, START, that can be administered by non-specialists to assess autism phenotypic domains (social, sensory, motor) through child performance and parent reports. N = 131 children (2–7 years old; 48 autistic, 43 intellectually disabled and 40 non-autistic typically developing) from low-resource settings in Delhi-NCR, India were assessed using START in home settings by non-specialist health workers. The two groups of children with neurodevelopmental disorders manifested lower social preference, greater sensory interest and lower fine-motor accuracy compared to their typically developing counterparts. Parent report further distinguished autistic from non-autistic children. Machine-learning analysis combining all START-derived measures demonstrated 78% classification accuracy for the three groups. Qualitative analysis of the interviews with health workers and families of the participants demonstrated high acceptability and feasibility of the app. These results provide feasibility, acceptability and proof of principle for START, and demonstrate the potential of a scalable, mobile tool for assessing neurodevelopmental conditions in low-resource settings. Autism is diagnosed by highly trained professionals– but most autistic people live in parts of the world that harbour few or no such autism specialists and little autism awareness. So many autistic people go undiagnosed, misdiagnosed, and misunderstood. We designed an app (START) to identify autism and related conditions in such places, in an attempt to address this global gap in access to specialists. START uses computerised games and activities for children and a questionnaire for parents to measure social, sensory, and motor skills. To check whether START can flag undiagnosed children likely to have neurodevelopmental conditions, we tested START with children whose diagnoses already were known: Non-specialist health workers with just a high-school education took START to family homes in poor neighbourhoods of Delhi, India to work with 131 two-to-seven-year-olds. Differences between typically and atypically developing children were highlighted in all three types of skills that START assesses: children with neurodevelopmental conditions preferred looking at geometric patterns rather than social scenes, were fascinated by predictable, repetitive sensory stimuli, and had more trouble with precise hand movements. Parents' responses to surveys further distinguished autistic from non-autistic children. An artificial-intelligence technique combining all these measures demonstrated that START can fairly accurately flag atypically developing children. Health workers and families endorsed START as attractive to most children, understandable to health workers, and adaptable within sometimes chaotic home and family environments. This study provides a proof of principle for START in digital screening of autism and related conditions in community settings. [ABSTRACT FROM AUTHOR]

Alterations in the development of attention control and learning have been associated with autism and can be measured using the 'antisaccade task', which assesses a child's ability to make an oculomotor response away from a distracting stimulus, and learn to instead anticipate a later reward. We aimed to assess these cognitive processes using portable eye-tracking in an understudied population of pre-school children with and without a diagnosis of autism spectrum disorder in community settings in New Delhi, India. The eye-tracking antisaccade task was presented to children in three groups (n = 104) (children with a clinical diagnosis of autism spectrum disorder or intellectual disability and children meeting developmental milestones). In accordance with findings from high-income, laboratory-based environments, children learnt to anticipate looks towards a reward, as well as inhibit eye-movements towards a distractor stimulus. We also provide novel evidence that while differences in inhibition responses might be applicable to multiple developmental conditions, a reduced learning to anticipate looks towards a target in this age group may be specific to autism. This eye-tracking task may, therefore, have the potential to identify and assess autism specific traits across development, and be used in longitudinal research studies such as investigating response to intervention in low-resource settings. The development of cognitive processes, such as attention control and learning, has been suggested to be altered in children with a diagnosis of autism spectrum disorder. However, nearly all of our understanding of the development of these cognitive processes comes from studies with school-aged or older children in high-income countries, and from research conducted in a controlled laboratory environment, thereby restricting the potential generalisability of results and away from the majority of the world's population. We need to expand our research to investigate abilities beyond these limited settings. We address shortcomings in the literature by (1) studying attention control and learning in an understudied population of children in a low- and middle-income country setting in India, (2) focusing research on a critical younger age group of children and (3) using portable eye-tracking technology that can be taken into communities and healthcare settings to increase the accessibility of research in hard-to-reach populations. Our results provide novel evidence on differences in attention control and learning responses in groups of children with and without a diagnosis of autism spectrum disorder. We show that learning responses in children that we assessed through a portable eye-tracking task, called the 'antisaccade task', may be specific to autism. This suggests that the methods we use may have the potential to identify and assess autism-specific traits across development, and be used in research in low-resource settings. [ABSTRACT FROM AUTHOR]

Background: Most research on early outcomes in infants with a family history (FH) of autism has focussed on categorically defined autism, although some have language and developmental delays. Less is known about outcomes in infants with a FH of attention deficit hyperactivity disorder (ADHD). Methods: Infants with and without a FH of autism and/or ADHD, due to a first‐degree relative with either or both conditions, were recruited at 5 or 10 months. Three year outcomes were characterised using latent profile analysis (LPA) across measures of cognitive ability, adaptive functioning and autism, ADHD and anxiety traits (n = 131). We additionally ran an LPA using only autism and ADHD measures, and the broader LPA in an independent cohort (n = 139) and in both cohorts combined (n = 270). Results: A Low Developmental Level + High Behavioural Concerns class had elevated autism, ADHD and anxiety scores, low cognitive and adaptive function, and included all but one child with autism. A Low Developmental Level + Typical Behaviour class had average cognitive ability and typical behaviour but low adaptive function. A Typical Developmental Level + Some Behavioural Concerns class had average cognitive and adaptive function but slightly elevated behaviour scores. A High Developmental Level + Typical Behaviour class had above average cognitive ability and typical behaviour. All four LPAs identified classes characterised by combinations of either, or both, Low Development Level and elevated behaviour scores, as well as a typically developing class. No classes had elevated autism or ADHD traits in isolation. Conclusions: Some infants with a FH of autism or ADHD have atypical developmental and behavioural outcomes, but do not show strong autism or ADHD traits in isolation. The field needs to recalibrate aims and methods to embrace the broader transdiagnostic pattern of outcomes seen in these infants. [ABSTRACT FROM AUTHOR]

Slower acquisition of language and motor milestones are common in infants with later autism and studies have indicated that motor skills predict the rate of language development, suggesting these domains of development may be interlinked. However, the inter‐relationships between the two domains over development and emerging autistic traits are not fully established. We studied language and motor development using standardized observational and parent‐report measures in infants with (n = 271) and without (n = 137) a family history of autism across four waves of data collection from 10 to 36 months. We used Random Intercept Cross‐Lagged Panel Models to examine contemporaneous and longitudinal associations between language and motor developments in both elevated and typical likelihood groups. We estimated paths between language and motor abilities at 10, 14, 24, and 36 months and autism trait scores at 36 months, to test whether the domains were interrelated and how they related to emerging autism traits. Results revealed consistent bidirectional Expressive Language (EL) and Fine Motor (FM) cross‐lagged effects from 10 to 24 and a unidirectional EL to FM effect from 24 to 36 months as well as significantly correlated random intercepts between Gross motor (GM) and Receptive language (RL), indicating stable concurrent associations over time. However, only the associations between GM and RL were associated with later autism traits. Early motor and language are linked, but only gross motor and receptive language are jointly associated with autistic traits in infants with an autism family history. Lay Summary: Children with autism sometimes show delays in language and motor skills from infancy. However, few researchers have focused on how language and motor skills develop together. We studied infants with a family history of autism over time, and found that early expressive language skills predicted later fine motor skills and vice versa. Gross motor (e.g., walking) and early language understanding predicted later autistic traits at age 3. Together, our results suggest that early motor and language are linked, but only gross motor and receptive language are jointly associated with autistic traits among children with autism family history. [ABSTRACT FROM AUTHOR]

Background: Autism spectrum disorders (ASD) and attention deficit hyperactivity disorder (ADHD) are two of the most common neurodevelopmental disorders, with a high degree of co-occurrence. Methods: Prospective longitudinal studies of infants who later meet criteria for ASD or ADHD offer the opportunity to determine whether the two disorders share developmental pathways. Results: Prospective studies of younger siblings of children with autism have revealed a range of infant behavioral and neural markers associated with later diagnosis of ASD. Research on infants with later ADHD is less developed, but emerging evidence reveals a number of relations between infant measures and later symptoms of inattention and hyperactivity. Conclusions: We review this literature, highlighting points of convergence and divergence in the early pathways to ASD and ADHD.

A number of recent studies on early categorization suggest that young infants form category representations for stimuli at both global and basic levels of exclusiveness (i.e., mammal, cat). A set of computational models designed to analyze the factors responsible for the emergence of these representations are presented. The models (1) simulated the formation of global-level and basic-level representations, (2) yielded a global-to-basic order of category emergence and (3) revealed the formation of two distinct global-level representations - an initial "self-organizing' perceptual global level and a subsequently "trained" arbitrary (i.e., non-perceptual) global level. Information from the models is used to make a number of testable predictions concerning category development in infants.

Background: Many studies have reported that autism spectrum disorder (ASD) is associated with atypical structural and functional connectivity. However, we know relatively little about the development of these differences in infancy. Methods: We used a high-density electroencephalogram (EEG) dataset pooled from two independent infant sibling cohorts, to characterize such neurodevelopmental deviations during the first years of life. EEG was recorded at 6 and 12 months of age in infants at typical (N = 92) or elevated likelihood for ASD (N = 90), determined by the presence of an older sibling with ASD. We computed the functional connectivity between cortical sources of EEG during video watching using the corrected imaginary part of phase-locking values. Results: Our main analysis found no significant association between functional connectivity and ASD, showing only significant effects for age, sex, age-sex interaction, and site. Given these null results, we performed an exploratory analysis and observed, at 12 months, a negative correlation between functional connectivity and ADOS calibrated severity scores for restrictive and repetitive behaviors (RRB). Limitations: The small sample of ASD participants inherent to sibling studies limits diagnostic group comparisons. Also, results from our secondary exploratory analysis should be considered only as potential relationships to further explore, given their increased vulnerability to false positives. Conclusions: These results are inconclusive concerning an association between EEG functional connectivity and ASD in infancy. Exploratory analyses provided preliminary support for a relationship between RRB and functional connectivity specifically, but these preliminary observations need corroboration on larger samples. [ABSTRACT FROM AUTHOR]

Background: Children with neurodevelopmental disorders including autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) often experience sleep disturbances, but little is known about when these sleep differences emerge and how they relate to later development. Methods: We used a prospective longitudinal design in infants with a family history of ASD and/or ADHD to examine infant sleep and its relation to trajectories of attention and later neurodevelopmental disorders. We formed factors of Day and Night Sleep from parent‐reported measures (including day/night sleep duration, number of naps in the day, frequency of night awakenings and sleep onset problems). We examined sleep in 164 infants at 5‐, 10‐ and 14‐months with/without a first‐degree relative with ASD and/or ADHD who underwent a consensus clinical assessment for ASD at age 3. Results: By 14‐months, infants with a first‐degree relative with ASD (but not ADHD) showed lower Night Sleep scores than infants with no family history of ASD; lower Night Sleep scores in infancy were also associated with a later ASD diagnosis, decreased cognitive ability, increased ASD symptomatology at 3‐years, and developing social attention (e.g., looking to faces). We found no such effects with Day Sleep. Conclusions: Sleep disturbances may be apparent at night from 14‐months in infants with a family history of ASD and also those with later ASD, but were not associated with a family history of ADHD. Infant sleep disturbances were also linked to later dimensional variation in cognitive and social skills across the cohort. Night Sleep and Social Attention were interrelated over the first 2 years of life, suggesting that this may be one mechanism through which sleep quality influences neurodevelopment. Interventions targeted towards supporting families with their infant's sleep problems may be useful in this population. [ABSTRACT FROM AUTHOR]

Emerging findings from studies with infants at familial high risk for autism spectrum disorder (ASD), owing to an older sibling with a diagnosis, suggest that those who go on to develop ASD show early impairments in the processing of stimuli with both social and non-social content. Although ASD is defined by social-communication impairments and restricted and repetitive behaviours, the majority of cognitive theories of ASD posit a single underlying factor, which over development has secondary effects across domains. This is the first high-risk study to statistically differentiate theoretical models of the development of ASD in high-risk siblings using multiple risk factors. We examined the prediction of ASD outcome by attention to social and non-social stimuli: gaze following and attentional disengagement assessed at 13 months in low-risk controls and high-risk ASD infants (who were subsequently diagnosed with ASD at 3 years). When included in the same regression model, these 13-month measures independently predicted ASD outcome at 3 years of age. The data were best described by an additive model, suggesting that non-social attention, disengagement, and social attention as evidenced by gaze following, have a cumulative impact on ASD risk. These data argue against cognitive theories of ASD which propose that a single underlying factor has cascading effects across early development leading to an ASD outcome, and support multiple impairment models of ASD that are more consistent with recent genetic and neurobiological evidence. [Members of the BASIS Team who also contributed to the writing of this article are as follows: Simon Baron-Cohen, Patrick Bolton, Susie Chandler, Janice Fernandes, Holly Garwood, Kristelle Hudry, Greg Pasco, Leslie Tucker, and Agnes Volein.]

The recent development in the measurements of spontaneous mental state understanding, employing eye-movements instead of verbal responses, has opened new opportunities for understanding the developmental origin of "mind-reading" impairments frequently described in autism spectrum disorders (ASDs). Our main aim was to characterize the relationship between mental state understanding and the broader autism phenotype, early in childhood. An eye-tracker was used to capture anticipatory looking as a measure of false beliefs attribution in 3-year-old children with a family history of autism (at-risk participants, n 47) and controls (control participants, n 39). Unlike controls, the at-risk group, independent of their clinical outcome (ASD, broader autism phenotype or typically developing), performed at chance. Performance was not related to children's verbal or general IQ, nor was it explained by children "missing out" on crucial information, as shown by an analysis of visual scanning during the task. We conclude that difficulties with using mental state understanding for action prediction may be an endophenotype of autism spectrum disorders.