Comparing trajectories of sport participation for autistic- and non-autistic youth: A group-based multi-trajectory modelling approach

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First published online 11 June 2025.

Why this study was done

Autistic children are generally less likely to take part in sport than non-autistic children. However, we don’t fully understand how their participation changes over time, especially between team sports and individual sports. This study aimed to track these patterns across childhood and adolescence.

What the study did

Researchers used data from a large group of Australian children and followed their sport participation from ages 8 to 15. They used a statistical method to group children based on how their participation in team and individual sports changed over time.

What the study found

The study found that:

  • Children fell into five different participation patterns over time
  • Autistic children were more likely to be in a “low participation” (sport avoider) group
  • They were less likely to be involved in team sports over time
  • There was no major difference between autistic and non-autistic children in individual sport participation
  • Patterns of participation were influenced by similar factors for both groups

What this means

This research suggests that:

  • Autistic children may face ongoing barriers to team sports, such as social or environmental challenges
  • Individual sports may be more inclusive or accessible for autistic children
  • Improving inclusion in team sport environments could help increase participation

Overall, the study highlights the importance of creating more supportive and inclusive sport settings, particularly for team-based activities.

This study was conducted by: Dr. Martin O’Flaherty, Dr. Jessica Hill, Dr. Matthew Bourke, Associate Professor Sjaan Gomersall, Associate Professor Sean Tweedy, and Professor John Cairney.

To read the full article, visit the journal.

For other accessible formats, please see the column to the right.

Disclaimer: The QDRN has utilised generative AI to refine the wording of this plain language summary. All content has been checked for accuracy, appropriate tone, and clarity, and approved by the author.

First published online 11 June 2025.

Why this study was done

Autistic children are generally less likely to take part in sport than non-autistic children. However, we don’t fully understand how their participation changes over time, especially between team sports and individual sports. This study aimed to track these patterns across childhood and adolescence.

What the study did

Researchers used data from a large group of Australian children and followed their sport participation from ages 8 to 15. They used a statistical method to group children based on how their participation in team and individual sports changed over time.

What the study found

The study found that:

  • Children fell into five different participation patterns over time
  • Autistic children were more likely to be in a “low participation” (sport avoider) group
  • They were less likely to be involved in team sports over time
  • There was no major difference between autistic and non-autistic children in individual sport participation
  • Patterns of participation were influenced by similar factors for both groups

What this means

This research suggests that:

  • Autistic children may face ongoing barriers to team sports, such as social or environmental challenges
  • Individual sports may be more inclusive or accessible for autistic children
  • Improving inclusion in team sport environments could help increase participation

Overall, the study highlights the importance of creating more supportive and inclusive sport settings, particularly for team-based activities.

This study was conducted by: Dr. Martin O’Flaherty, Dr. Jessica Hill, Dr. Matthew Bourke, Associate Professor Sjaan Gomersall, Associate Professor Sean Tweedy, and Professor John Cairney.

To read the full article, visit the journal.

For other accessible formats, please see the column to the right.

Disclaimer: The QDRN has utilised generative AI to refine the wording of this plain language summary. All content has been checked for accuracy, appropriate tone, and clarity, and approved by the author.