Frederick Shic

Children born low-birth-weight (LBW) or with autistic siblings may show differences in their developmental trajectories, including higher rates of autism and lower levels of adaptive behavior skills. Parsing out developmental differences in these groups could help hone screening tools and lead to more precise interventions. The present study aimed to evaluate trajectories of adaptive behavior in children at elevated likelihood for autism and investigate whether trajectories differ for autistic and nonautistic children based on their likelihood group at birth. Two hundred fifty-seven children participated in a longitudinal study at approximately 7, 14, 28, and 39 months of age. Participants were categorized as low likelihood (LL) or elevated likelihood (EL) due to LBW or having an older autistic sibling. We analyzed diagnostic outcomes and social, communication, daily living, and motor skills as measured by the Vineland Adaptive Behavior Scales–Third Edition. Both EL groups presented with adaptive behavior delays, but children with an autistic sibling exhibited greater delays than their LBW or LL counterparts, particularly if they themselves were diagnosed as autistic, with some age- and domain-related nuances. Results reveal the unique developmental vulnerabilities among both EL groups and underscore the importance of targeted intervention during this critical early period. Lay Some children are more likely to develop autism than others or are more likely to have delays in their development. Babies who are born with a low birth weight and those who have an older sibling with autism are two examples. These children may also have more difficulty with everyday life skills like communicating, socializing, and taking care of themselves. This study followed children from about 7 to 39 months of age to see how their everyday communication, social, daily living, and motor skills developed over time. We found that children who had an older autistic sibling had the most difficulty with everyday skills compared with other groups and were more likely to develop autism themselves. These findings help us better understand how development differs among children who may go on to develop autism and can help us provide better interventions for these children early in life.

Purpose: The aim of this study was to evaluate how eye-trackers are currently used in clinical settings and to explore whether guidelines are perceived to be needed to support their use in a clinical context. Methods: A survey was developed and distributed to clinical eye-tracker users, manufacturers, professional bodies and other key stakeholders. The survey explored current practices, perceived barriers to clinical eye-tracking, guideline availability, and the perceived need for guidelines to support clinical practice. Results: Eighty responses to at least one of the survey questions were received. Of these, three were excluded from some analyses due to having no clinical involvement in eye-tracking (their involvement was in research only). Eye-tracking was performed by ophthalmologists, orthoptists, neurologists, optometrists, allied scientists and audiologists. Whilst most respondents were assessing eye movements daily, eye-tracking was mostly performed either rarely (less than 10%) or moderately often (10-60%) in their practice. Most clinical respondents (76%) reported they both performed eye-tracking and interpreted the results. The most commonly identified barriers to clinical eye-tracking were eye-trackers being considered primarily research tools, considered unsuitable for performing the assessments, and lack of access to an eye-tracker. Most respondents (71%) were unaware of any existing guidelines for clinical eye-tracking. Where guidelines were reported to exist, they were described as somewhat sufficient to completely insufficient. Most respondents (93%) supported the development of guidelines for clinical eye-tracking. A small number of respondents (7%) reported concerns about introducing clinical eye-tracking guidelines. Conclusion: A broad range of clinicians, professionals and other stakeholders involved in clinical eye-tracking responded to this survey. Their responses suggest a general consensus of a need for clinical eye-tracking guidelines. Whilst guidelines may address some of the reported barriers to eye-tracking clinically, and support benchmarking and standardisation across a broad range of clinical disciplines, concerns around a perceived threat to autonomous clinical practice should also be considered.

Reduced social attention (SA) is a hallmark feature of autism that is foundational to social communication and interaction. However, emerging evidence suggests that reduced SA may not be uniformly expressed across the autism spectrum. Sex and cognitive ability (IQ) have been identified as relevant stratification variables, potentially moderating SA in autistic children. We examined differential patterns of SA stratified by sex and cognitive ability in a large, longitudinal sample of autistic and neurotypical (NT) children (ages 6–11 years) from the Autism Biomarkers Consortium for Clinical Trials (ABC‐CT), examining SA across four measurement timepoints (Baseline, 6 weeks, 6 months, and 4 years). SA was measured using the oculomotor index of gaze to human faces (OMI) derived from standardized eye‐tracking (ET) assays, with children stratified by sex (male, female) and IQ (IQ ≥ 85, IQ < 85). Linear mixed‐effects models were used to evaluate the effects of sex, IQ, and timepoint on SA, with additional analyses assessing the stability and clinical associations of OMI. Autistic females did not exhibit lower OMI scores compared to autistic males; however, relative to sex‐matched NT children, autistic females showed approximately twice the reduction in OMI observed in autistic males. Likewise, the reduction in OMI associated with autism (i.e., ASD < NT) was larger in autistic children with below‐average IQ than in those with average or above‐average IQ. These differences were relatively stable across measurement timepoints, and OMI was more strongly associated with clinical features like face memory and adaptive behavior in autistic males and the average or above‐average IQ autism subgroup. While reduced SA is a general feature of autism, its expression is stratified by sex and cognitive ability. These findings highlight the importance of subgroup stratification to better understand heterogeneity in autism and improve the utility of SA as a therapeutic biomarker.

A growing body of work on robot‐mediated therapy suggests that robots can elicit engagement and novel social behaviors among users with autism. In this narrative review, we trace the full historical arc of this field to date, from its inception in 2001 to 2024, covering 304 studies that present a robot for autism support. Early work largely consisted of short, highly structured sessions conducted in controlled laboratory or clinical environments. More recent research has shifted toward longer‐term, real‐world deployments in which robots operate with greater autonomy and engage users over multiple days or weeks. However, evidence for lasting and generalized benefits is still limited. The literature also remains focused primarily on children, with comparatively little research involving adults or individuals across a wider range of support needs. Despite rapid growth over these past two decades, the research remains fragmented across disciplinary boundaries, with robotics and clinical communities advancing similar goals without a cohesive, shared research framework. To address this, we offer a translational roadmap that details what interventions work, for whom, under which conditions, and why. We highlight current methodological gaps, outline key design considerations, and propose priorities for future research.

Eye tracking has emerged as a powerful tool for advancing autism research, including diagnostics and interventions. However, studies on joint attention (JA) in autistic children have predominantly concentrated on the responding to joint attention (RJA) construct, with limited focus on the initiating joint attention (IJA) construct. Moreover, despite the interactive nature of JA, researchers have often relied on passive paradigms to study JA in this population. To address these gaps, we developed a gaze-contingent eye-tracking battery targeting three developmentally appropriate JA skills for young children: RJA, IJA to request, and IJA to comment or reference. The development process was multifaceted and iterative, involving a series of collaborative steps and the allocation of various resources. These steps included determining the motion format and stimulus type, designing and prototyping the stimuli, recruiting an actor to serve as a communication partner in the stimuli, recording and editing videos for the stimuli, and building and test-running the battery. We developed the Interactive Eye Tracking for Joint Attention (IET-JA) battery, which consists of 32 JA stimuli: 16 RJA, 8 IJA-Request, and 8 IJA-Comment/Reference. The stimuli are dynamic (i.e., videos) and feature a preprogrammed interactive human communication partner who is responsive to the participant’s gaze. The IET-JA takes approximately 8 minutes to complete, and its duration is expected to vary based on the participant’s level of engagement. Implications for advancing methodologies, fostering team science, and enhancing iterative processes are discussed.

This review provides an overview of eye-tracking tasks used to investigate joint attention (JA) in autistic children by examining key methodological dimensions, including the structure of the JA probe, design of the JA task, and gaze metrics derived to quantify JA. A systematic search was conducted following the PRISMA guidelines. A total of 26 studies were included in this review. The findings highlight a heavy focus on responding to joint attention (RJA), with limited emphasis on initiating joint attention (IJA). There was a clear preference for dynamic yet non-interactive social stimuli without environmental context, accompanied by variability in deictic cues for RJA and prompts for IJA tasks. Nine gaze metrics were identified, showing variability in their computation and prerequisites. These findings have implications for the conceptualization, design, and refinement of JA eye-tracking tasks and their applications for autistic children.

Slower looking to faces is a common behavioral feature of autism central to sociocognitve development. However, the underlying mechanism explaining this phenomenon remains unclear. We investigated whether deprioritization of social information or prolonged prioritization of nonsocial information better accounted for slower latency to look at faces in a large sample of autistic (n = 269) and neurotypical (NT; n = 118) children. Participants completed an eye tracking (ET) assay in which they viewed arrays of social and nonsocial stimuli. To determine why autistic children were slower to look at faces, we computed two ET metrics that reflected either deprioritization of social information or prolonged prioritization of nonsocial information. Deprioritization of social information was operationalized by face look number (FLN), which was defined as the numerical look sequence position of the first face look. Prolonged prioritization of nonsocial information was operationalized by time per object prior, which was defined as the average looking time per nonsocial object prior to the first face look. We found that autistic children were slower to look at faces compared to NT children and had higher FLN but not time per object prior compared to NT children. FLN was associated with measures of the autism phenotype. In summary, this work suggests deprioritization of social information better explains slower latency to look at faces in autistic children than prolonged prioritization of nonsocial information, with the reduced prioritization of faces contributing to difficulties in dynamic social interaction commonly observed in autism. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

There is a growing body of evidence suggesting a concurrent association between attentional indices measured via eye tracking and autism symptoms. This meta‐analysis examined the utility of eye tracking within longitudinal frameworks for autism interventions, including treatment monitoring and prediction of treatment response. We conducted a multivariate random‐effects meta‐analysis with a multilevel structure on 25 studies (828 autistic participants; M _age = 3–28 years) to estimate: (a) changes in eye‐tracking outcomes from pre‐ to post‐treatment ( k = 179); and (b) the correlation between baseline eye‐tracking profiles and changes in developmental outcomes following treatment ( k = 39). Our analysis revealed a moderate and significant summary effect size for changes in eye‐tracking outcomes from pre‐ to post‐treatment (Hedge's g = 0.32, p = 0.010). Additionally, a moderate but non‐significant summary effect size was revealed for the correlation between baseline eye‐tracking outcomes and changes in developmental outcomes following treatment (Fisher's z = 0.20, p = 0.115), with moderation effects observed based on developmental domain and sex. These findings highlight the potential of eye tracking as a tool for monitoring treatment‐induced changes in autistic individuals, while its predictive utility remains less supported. Limitations and implications are discussed.