Autism

Do social and non-social attention combine to predict autism?

Bedford R, Pickles A, Gliga T, et al. · Developmental science · 2014

Open access · cc by · source: Europe PMC

Infants who show both reduced social attention and slower attention disengagement are at the highest risk for developing autism, with these factors combining additively rather than interactively.

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Do social and non-social attention combine to predict autism?

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13 months

At 13 months, 45 low-risk controls, 22 high-risk (HR)-typical and 17 HR-ASD infants took part in the gap-overlap task (see Table).

36 months

Toddlers from the high-risk group were considered typically developing (HR-typical) at 36 months if they (1) did not meet ICD-10 criteria for an ASD; (2) did not score above the cut-off on the ADOS-G or ADI-R; (3) scored within 1.5 SD of the population mean on the MSEL Early Learning Composite (ELC) () standard score (> 77.5) and RL and EL subscale T-scores (> 35).

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Key findings

Both reduced social looking time and slower visual disengagement at 13 months independently predicted an autism diagnosis at 36 months. An additive model of risk fit the data significantly better than a multiplicative model, with log-likelihoods of −14.18 and −19.77 respectively. This indicates that social and non-social attention deficits represent distinct, cumulative pathways to autism rather than a single interacting cascade.

Methodology

The researchers measured both social attention (using an eye-tracking gaze-following task) and non-social attention (using a gap-overlap task) in low-risk and high-risk infants at 13 months. At 36 months, these children were assessed clinically for an autism diagnosis. The authors then used statistical modeling to determine whether these two attentional measures predicted later autism outcomes independently or through interaction.

Limitations

The study is limited by a relatively small clinical sample, with only 17 infants in the high-risk group receiving an autism diagnosis, which restricts generalizability. Since the data are observational and correlational, the design cannot prove that these attentional differences directly cause autism. Additionally, the study did not examine whether these early attention measures map onto specific subtypes of later autism symptoms, such as restricted or repetitive behaviors.

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