Feasibility of a Randomized Controlled Trial of Large AI-Based Linguistic Models for Clinical Reasoning Training of Physical Therapy Students: Pilot Randomized Parallel-Group Study
Abstract BackgroundClinical reasoning is a critical skill for physical therapists, involving the collection and interpretation of patient information to form accurate diagnoses. Traditional training often lacks the diversity of clinical cases necessary for students to develop...
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JMIR Publications
2025-07-01
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| Series: | JMIR Formative Research |
| Online Access: | https://formative.jmir.org/2025/1/e66126 |
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| author | Raúl Ferrer-Peña Silvia Di-Bonaventura Alberto Pérez-González Alfredo Lerín-Calvo |
| author_facet | Raúl Ferrer-Peña Silvia Di-Bonaventura Alberto Pérez-González Alfredo Lerín-Calvo |
| author_sort | Raúl Ferrer-Peña |
| collection | DOAJ |
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Abstract
BackgroundClinical reasoning is a critical skill for physical therapists, involving the collection and interpretation of patient information to form accurate diagnoses. Traditional training often lacks the diversity of clinical cases necessary for students to develop these skills comprehensively. Large language models (LLMs) like GPT-4 have the potential to simulate a wide range of clinical scenarios, offering a novel approach to enhance clinical reasoning in physical therapy education.
ObjectiveThe aim of the study is to explore the main barriers and facilitators that could be encountered in conducting a randomized clinical trial to study the effectiveness of the implementation of LLM models as tools to work on the clinical reasoning of physical therapy students.
MethodsThis pilot randomized parallel-group study involved 46 third-year physical therapy students at La Salle Centre for Higher University Studies. Participants were randomly assigned to either the experimental group, which received LLM training, or the control group, which followed the usual curriculum. The intervention lasted for 4 weeks, during which the experimental group used LLM to solve weekly clinical cases. Digital competencies, satisfaction, and costs were evaluated to explore the feasibility of this intervention.
ResultsThe recruitment and participation rates were high, but active engagement with the LLM was low, with only 5.75% (5/23) of the experimental group actively using the model. No significant difference in overall satisfaction was found between the groups, and the cost analysis reflected an initial cost of US $1738 for completing the study.
ConclusionsWhile LLMs have the potential to enhance specific digital competencies in physical therapy students, their practical integration into the curriculum faces challenges. Future studies should focus on improving student engagement with LLMs and extending the training period to determine the feasibility of integrating this tool into physical therapy education and maximize benefits. |
| format | Article |
| id | doaj-art-44b744b0d31f451cba9e081429c2d71e |
| institution | DOAJ |
| issn | 2561-326X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Formative Research |
| spelling | doaj-art-44b744b0d31f451cba9e081429c2d71e2025-08-20T02:47:25ZengJMIR PublicationsJMIR Formative Research2561-326X2025-07-019e66126e6612610.2196/66126Feasibility of a Randomized Controlled Trial of Large AI-Based Linguistic Models for Clinical Reasoning Training of Physical Therapy Students: Pilot Randomized Parallel-Group StudyRaúl Ferrer-Peñahttp://orcid.org/0000-0001-5495-8458Silvia Di-Bonaventurahttp://orcid.org/0000-0003-0564-9557Alberto Pérez-Gonzálezhttp://orcid.org/0009-0003-9892-768XAlfredo Lerín-Calvohttp://orcid.org/0000-0002-7337-8747 Abstract BackgroundClinical reasoning is a critical skill for physical therapists, involving the collection and interpretation of patient information to form accurate diagnoses. Traditional training often lacks the diversity of clinical cases necessary for students to develop these skills comprehensively. Large language models (LLMs) like GPT-4 have the potential to simulate a wide range of clinical scenarios, offering a novel approach to enhance clinical reasoning in physical therapy education. ObjectiveThe aim of the study is to explore the main barriers and facilitators that could be encountered in conducting a randomized clinical trial to study the effectiveness of the implementation of LLM models as tools to work on the clinical reasoning of physical therapy students. MethodsThis pilot randomized parallel-group study involved 46 third-year physical therapy students at La Salle Centre for Higher University Studies. Participants were randomly assigned to either the experimental group, which received LLM training, or the control group, which followed the usual curriculum. The intervention lasted for 4 weeks, during which the experimental group used LLM to solve weekly clinical cases. Digital competencies, satisfaction, and costs were evaluated to explore the feasibility of this intervention. ResultsThe recruitment and participation rates were high, but active engagement with the LLM was low, with only 5.75% (5/23) of the experimental group actively using the model. No significant difference in overall satisfaction was found between the groups, and the cost analysis reflected an initial cost of US $1738 for completing the study. ConclusionsWhile LLMs have the potential to enhance specific digital competencies in physical therapy students, their practical integration into the curriculum faces challenges. Future studies should focus on improving student engagement with LLMs and extending the training period to determine the feasibility of integrating this tool into physical therapy education and maximize benefits.https://formative.jmir.org/2025/1/e66126 |
| spellingShingle | Raúl Ferrer-Peña Silvia Di-Bonaventura Alberto Pérez-González Alfredo Lerín-Calvo Feasibility of a Randomized Controlled Trial of Large AI-Based Linguistic Models for Clinical Reasoning Training of Physical Therapy Students: Pilot Randomized Parallel-Group Study JMIR Formative Research |
| title | Feasibility of a Randomized Controlled Trial of Large AI-Based Linguistic Models for Clinical Reasoning Training of Physical Therapy Students: Pilot Randomized Parallel-Group Study |
| title_full | Feasibility of a Randomized Controlled Trial of Large AI-Based Linguistic Models for Clinical Reasoning Training of Physical Therapy Students: Pilot Randomized Parallel-Group Study |
| title_fullStr | Feasibility of a Randomized Controlled Trial of Large AI-Based Linguistic Models for Clinical Reasoning Training of Physical Therapy Students: Pilot Randomized Parallel-Group Study |
| title_full_unstemmed | Feasibility of a Randomized Controlled Trial of Large AI-Based Linguistic Models for Clinical Reasoning Training of Physical Therapy Students: Pilot Randomized Parallel-Group Study |
| title_short | Feasibility of a Randomized Controlled Trial of Large AI-Based Linguistic Models for Clinical Reasoning Training of Physical Therapy Students: Pilot Randomized Parallel-Group Study |
| title_sort | feasibility of a randomized controlled trial of large ai based linguistic models for clinical reasoning training of physical therapy students pilot randomized parallel group study |
| url | https://formative.jmir.org/2025/1/e66126 |
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