ArticleInquiry : a journal of medical care organization, provision and financing
Artificial Intelligence in Speech and Language Therapy: A Qualitative Comparative Analysis of Clinical Applications and Outcomes.
Article in Inquiry : a journal of medical care organization, provision and financing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large language models (LLMs) such as ChatGPT are entering clinical practice, yet how their clinical reasoning compares with speech-language therapists (SLTs) is not well understood. This comparative multi-case qualitative study used 3 hypothetical vignettes. Ten experienced SLTs (≥10 years) participated in semi-structured interviews, providing assessment, diagnosis and therapy plans for each vignette. ChatGPT-4o was presented with identical, standardized Turkish prompts over five consecutive days to evaluate the model's temporal consistency in clinical reasoning. All outputs were analyzed with content analysis, and day-to-day consistency of ChatGPT themes was examined. ChatGPT-4o and SLTs showed substantial overlap in core practices such as case history, spontaneous speech analysis, key diagnostic labels, and emphasis on generalization and caregiver involvement. However, SLTs utilized broader, locally normed assessment tools and offered more flexible, individualized and context-sensitive therapy approaches. ChatGPT-4o's responses were more standardized and showed stable thematic patterns across days, yet they did not reflect the clinical nuance or contextual adaptation observed in SLTs' reasoning. ChatGPT-4o can approximate expert-like reasoning in structured scenarios and may serve as a clinical decision support aid. Nonetheless, it does not replace experienced SLTs, particularly for culturally grounded, person-specific assessment and intervention planning.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.