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Play for the win: Study finds parent-child play helps with friendships 

Early parent-child play can be a key predictor in how successfully children interact with peers, according to a new study from the University of Georgia.  

Most of the time, parents take the lead role, but play can flip the script, allowing a parent to respond to a child’s lead, according to the study, summarized in Neuroscience News. A parent who balanced assertiveness (being proactive or taking charge) and responsiveness during play encouraged the same in the child, laying a promising foundation for social interactions, particularly with new peers, the study found. 

Again: It’s give-and-take in play that teaches these powerful lessons. 

For this study, the data analyzed came from observations of more than 120 mother-toddler pairs interacting in a lab playroom, then observations of the children as they interacted with friends at preschool. Researchers later paired the children with peers they had never met and observed their interactions, and they also observed the children playing with close friends. 

We at Pariva are firm believers in the power of play to help children learn and to prepare them for life. Play lets children try out different approaches in a safe environment, without the risks of real-world consequences. 

In addition to training children to navigate social relationships, play teaches basic life skills, creates meaningful connections, encourages emotional regulation, helps children make sense of the world, and so much more. Clinicians in our Family Support Program use many research-backed, play-based therapies to help neurodivergent children make developmental strides in various aspects of everyday life.  

Pariva Health has helped more than 25,000 families of neurodivergent children and 
counting — find out more about the ways in which we empower families, offering hope 
and help, with lots of play and no wait list. 

Prithvi Singh

Seasoned Technical Product Manager, focusing on product strategy, roadmap development, and data-driven decision-making. Hands-on experience in implementing and optimizing machine learning algorithms in various projects