Asst. Prof. Jiabin Shen Says Research Could Help Prevent Injuries
By Marlon Pitter
Asst. Prof. of Psychology Jiabin Shen has won a $119,907 federal grant from the Health Resources and Services Administration to research the effects of injuries on children with autism spectrum disorder (ASD).
The yearlong study will focus on the disparities between the risk of injuries to children with and without ASD, how their families seek health care for their injuries, and the financial costs they endure as a result. Shen says the research could ultimately help reduce injuries among children with ASD.
A study published in the Journal of Autism and Developmental Disorders in 2017 found that children with ASD are more likely to sustain injuries than children who do not have the disorder.
“If we find that children with ASD are more likely to receive hospitalization services than children without ASD, maybe it suggests that children with ASD are more likely to suffer more severe type of injuries than their counterparts,” says Shen.
While researchers continue to explore ASD, Shen says he looks to fill in “critical gaps” in the methodology of prior studies with this grant.
Shen will collaborate on the study with Center for Autism Research and Education Co-Director and Psychology Prof. Ashleigh Hillier, Assoc. Prof. of Psychology Yan Wang and Health Statistics and Geography Lab Director and Public Health Chair Wenjun Li, as well as with graduate students and an external expert on national healthcare survey databases.
According to Shen, previous research on childhood injuries has been conducted with hospital data, which limits the quantity of information that researchers can collect. Instead, he is using a population-based approach, sampling data from the Medical Expenditure Panel Survey database, the most comprehensive source of information on the cost and use of health care and health insurance coverage in the U.S. The database includes information on injuries to children with and without ASD from 2000 through 2021, totaling 193,031 individuals from across the U.S.
“Population-based research is a way to do systematic random sampling across the entire population, so the findings will be more representative,” he says.
Shen says prior ASD studies have been conducted with a top-down approach, in which researchers use existing information to predict potential outcomes and determine whether the data supports their hypothesis.
Shen looks to take a bottom-up approach by analyzing the full data set and finding any correlations or trends that may exist. He will use a machine learning algorithm to analyze the data and identify injury risk factors and disparities in health care use in children with ASD.
Long range, Shen expects an important benefit for children with ASD will emerge from the research: fewer injuries.
“When we start to disseminate our findings, hopefully … this research can help develop effective and tailored injury prevention programs that are specifically designed for children with autism spectrum disorder,” he says.