An observational study in Stuttering, sponsored by Istanbul Gelisim University. Completed at 1 site in Turkey (Türkiye). Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-09-22.
Sponsored by Istanbul Gelisim University · Observational
This observational study aims to compare the quality of responses generated by four large language models (ChatGPT, Claude, Google Gemini, and Grok-4.20) to questions about stuttering. The study focuses on three main areas: general information about stuttering, clinical assessment, and therapy. A total of nine questions were developed based on evidence-based clinical practice guidance, including the American Speech-Language-Hearing Association (ASHA) Practice Portal. Each question is presented to each language model in separate sessions, and the generated responses are recorded for evaluation.
Five speech-language therapists with clinical experience in stuttering independently evaluate the model-generated responses. Each response is rated for relevance, accuracy, clarity, completeness, and consistency using a 5-point Likert scale. The responses are also compared with guideline-based reference information. The study does not involve any clinical intervention or treatment of patients. The aim is to determine how closely large language model responses align with current clinical practice guidance and to identify their potential strengths and limitations when used as informational or clinical support tools in the field of stuttering.
74 studies on the registry are indexed under Stuttering; 23 are open to participants now.
This study's enrollment of 5 is below the median of 60 across 15 observational studies indexed under Stuttering.
Browse Stuttering studies →Istanbul Gelisim University is the lead sponsor of 64 studies on the registry; 8 are open to participants now.
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The study population consisted of adult speech-language therapists in Türkiye who were actively working in the field of stuttering and fluency disorders. Five speech-language therapists with clinical experience in stuttering were purposively selected to independently evaluate responses generated by four large language models to standardized questions concerning stuttering information, assessment, and therapy.
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Exclusion Criteria:
Five speech-language therapists with clinical experience in stuttering independently evaluated responses generated by four large language models (ChatGPT, Claude, Google Gemini, and Grok-4.20). The responses addressed nine questions covering general information about stuttering, clinical assessment, and therapy. Each response was rated for relevance, accuracy, clarity, completeness, and consistency using a 5-point Likert scale.
Other: ChatGPT-Generated Responses · Other: Claude-Generated Responses · Other: Google Gemini-Generated Responses · Other: Grok-4.20-Generated Responses
ChatGPT responses to nine standardized questions on stuttering information, assessment, and therapy were generated in separate sessions and recorded for independent expert evaluation. Questions were repeated under comparable conditions to allow assessment of response consistency.
Claude responses to nine standardized questions on stuttering information, assessment, and therapy were generated in separate sessions and recorded for independent expert evaluation. Questions were repeated under comparable conditions to allow assessment of response consistency.
Google Gemini responses to nine standardized questions on stuttering information, assessment, and therapy were generated in separate sessions and recorded for independent expert evaluation. Questions were repeated under comparable conditions to allow assessment of response consistency.
Grok-4.20 responses to nine standardized questions on stuttering information, assessment, and therapy were generated in separate sessions and recorded for independent expert evaluation. Questions were repeated under comparable conditions to allow assessment of response consistency.
Expert-Rated Quality of Large Language Model Responses
Responses generated by four large language models (ChatGPT, Claude, Google Gemini, and Grok-4.20) to nine standardized questions about stuttering were independently evaluated by five speech-language therapists with clinical experience in stuttering. Each response was rated using a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree) across five criteria: relevance, accuracy, clarity, completeness, and consistency. Responses were evaluated against guideline-based reference information derived from evidence-based clinical practice guidance. Higher scores indicate better response quality and closer alignment with clinical practice guidance. Mean scores were calculated for each large language model and each evaluation criterion.
Time frame: During the single cross-sectional expert evaluation conducted over approximately 1 month
This study is completed, as verified in Sep 2026. You cannot join it, but the record below documents what was studied.
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Istanbul Gelisim University