Purpose: This study investigates the potential of the ChatGPT-4.0 artificial intelligence bot to assist speech-language pathologists (SLPs) by assessing its accuracy, comprehensiveness, and relevance in various tasks related to speech, language, and swallowing disorders.
Method: In this cross-sectional descriptive study, 15 practicing SLPs evaluated ChatGPT-4.0's responses to task-specific queries across six core areas: report writing, assessment material generation, clinical decision support, therapy stimulus generation, therapy planning, and client/family training material generation. English prompts were created in seven areas: speech sound disorders, motor speech disorders, aphasia, stuttering, childhood language disorders, voice disorders, and swallowing disorders. These prompts were entered into ChatGPT-4.0, and its responses were evaluated. Using a three-point Likert-type scale, participants rated each response for accuracy, relevance, and comprehensiveness based on clinical expectations and their professional judgment.
Results: The study revealed that ChatGPT-4.0 performed with predominantly high accuracy, comprehensiveness, and relevance in tasks related to speech and language disorders. High accuracy, comprehensiveness, and relevance levels were observed in report writing, clinical decision support, and creating education material. However, tasks such as creating therapy stimuli and therapy planning showed more variation with medium and high accuracy levels.
Conclusions: ChatGPT-4.0 shows promise in assisting SLPs with various professional tasks, particularly report writing, clinical decision support, and education material creation. However, further research is needed to address its limitations in therapy stimulus generation and therapy planning to improve its usability in clinical practice. Integrating AI technologies such as ChatGPT could improve the efficiency and effectiveness of therapeutic processes in speech-language pathology.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s00405-025-09295-y | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Psychometric Properties of Questionnaires to Assess the Family Food Environment in the Pediatric Population: A Systematic Review.
Nutr Rev
March 2025
Department of Epidemiology of the School of Public Health in Austin, The University of Texas Health Science Center at Houston (UTHealth Houston), Austin, TX 78701, United States.
Context: Given the diverse aspects of the family food environment, it is essential to clarify the availability of tools, the assessed dimensions, and the extent to which they offer a comprehensive and valid evaluation of the domestic food setting.
Objective: This systematic review aims to assess the validity and reliability of instruments gauging the food environment within the pediatric population.
Data Sources: A systematic literature search was conducted in the EMBASE, Medline (PubMed), SCOPUS, Web of Science, and PsychINFO databases until December 2023, resulting in the identification of 2850 potentially eligible articles.
Rapid quality evaluation of wheat flour containing moderate level of gluten using near-infrared spectroscopy and chemometrics.
J Sci Food Agric
March 2025
Key Laboratory of Detection and Risk Prevention of Key Hazardous Materials in Food, China General Chamber of Commerce, Ningbo Key Laboratory of Detection, Control, and Early Warning of Key Hazardous Materials in Food, College of Food Science and Engineering, Ningbo University, Ningbo, China.
Background: Currently, flour quality evaluation methods are varied, but there are some issues, such as single evaluation indicators and insufficient comprehensiveness. The present study aimed to develop a more comprehensive and rapid evaluation method for flour quality.
Results: We first measured nine key quality indicators of dough samples, raw noodle products and cooked noodle products made from wheat flour.
Data augmented lung cancer prediction framework using the nested case control NLST cohort.
Front Oncol
February 2025
Centre de Recherche du CHU de Québec, Université Laval, Québec, QC, Canada.
Purpose: In the context of lung cancer screening, the scarcity of well-labeled medical images poses a significant challenge to implement supervised learning-based deep learning methods. While data augmentation is an effective technique for countering the difficulties caused by insufficient data, it has not been fully explored in the context of lung cancer screening. In this research study, we analyzed the state-of-the-art (SOTA) data augmentation techniques for lung cancer binary prediction.
View Article and Find Full Text PDFComparison of Lateral Semicircular Canal Dysfunction in Chronic Otitis Media Patients using Air Caloric Test and Video Head Impulse Test.
Indian J Otolaryngol Head Neck Surg
February 2025
Department of ENT, SRM Medical College Hospital and Research Centre, Kanchipuram, Tamil Nadu India.
In developing nations like India, chronic otitis media (COM) is a common middle ear ailment that has serious ramifications for both hearing and quality of life. Long-term inflammation of middle ear cavity and tympanic membrane are the hallmarks of COM, which can result in consequences like facial paralysis, labyrinthitis, hearing loss, and potentially fatal cerebral abscesses. The effect of COM on vestibular function is still unknown.
View Article and Find Full Text PDFApproach to Detecting Beneficial and Detrimental Drug-Drug Interactions in Complex Pharmacotherapy.
Cureus
February 2025
Pharmacy, Mie University Hospital, Tsu, JPN.
Background The increasing prevalence of polypharmacy has raised concerns about drug-drug interactions (DDIs) and their impact on patient safety. Database-based DDI detection often suffers from insufficient patient background information and missing data, limiting the accuracy and applicability of DDI assessments. A novel model is needed to overcome these limitations and provide a more comprehensive evaluation of DDIs to enhance patient safety in the context of multiple medication use.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!