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Area of Science:

  • Speech-language pathology
  • Pediatric audiology

Background:

  • Stuttering onset frequently occurs before age three.
  • Current interventions demand significant cognitive engagement, limiting their use in very young children.
  • Limited clinical trial evidence exists for treating stuttering in children under three.

Purpose of the Study:

  • To highlight the need for immediate intervention following stuttering onset.
  • To identify suitable interventions for preschool children who stutter.
  • To propose a novel treatment protocol for early stuttering intervention.

Main Methods:

  • Developed a clinical protocol based on parent speech rate reduction and increased interturn speaker latency.
  • Demonstrated the clinical viability of the protocol with three young children who stuttered.
  • Proposed AI-driven avatar clinicians for automated, globally accessible treatment.

Main Results:

  • The developed clinical protocol proved viable in initial trials with three children.
  • Parent-led strategies requiring minimal child cognitive engagement are suitable for immediate intervention.
  • AI automation can enhance the global reach and scalability of stuttering treatment.

Conclusions:

  • Parent-implemented strategies are effective for immediate stuttering intervention in very young children.
  • AI-powered interventions offer a scalable solution for early stuttering treatment.
  • The proposed protocol is a candidate for future clinical trials (Phases I-IV).