Whose Gestures are More Predictive of Expressive Language Abilities among Chinese-Speaking Children with Autism? A Comparison of Caregivers' and Children's Gestures.

So et al. (2023) watched Chinese-speaking preschoolers with autism and their caregivers. They coded every gesture both partners used during play. Then they ran a cluster analysis to see if the kids fell into clear verbal-ability groups.

The goal was to find out whose gestures—child or caregiver—best predict later talking skills.

The children sorted into four distinct verbal-ability profiles. Some kids had many gestures and some had few. Some caregivers gestured a lot and some did not.

The clusters give clinicians a quick picture of where each child stands today.

Mason et al. (2025) show that kids who already mand, babble, and imitate are far more likely to echo. You can fold those signs into the four clusters to pick who is ready for echoic training.

Bak et al. (2019) followed minimally verbal school-age kids for a whole school year and saw zero growth in vocalizations. That sounds like bad news, but their sample was older and stuck at the bottom of the range. Wing-Chee’s clusters include both verbal and minimally verbal preschoolers, so they capture the full spread of ability.

Yu-Wen et al. (2023) tracked toddlers for a decade and found that early pointing and showing predicted the best teen outcomes. Wing-Chee’s gesture clusters line up with those same toddler markers, giving you an earlier way to spot the kids on the strong track.

Use the four clusters as a starting map. Place each new preschooler into the profile that matches their gesture count and caregiver support. Then pick goals that fit: more child gestures, more caregiver gestures, or jump straight to echoics if Mason’s green lights are already there. Re-check the cluster every six months to see movement.