Parkinson DiseaseAI-PD-OT25NCT07045077
Effect of AI Chatbot-Assisted Versus Traditional Case-Based Learning on Clinical Reasoning in Occupational Therapy Students: A Study on Parkinson's Disease
A study testing AI Chatbot-Assisted Case-Based Learning and Traditional Case-Based Learning with Standard Materials in people with Parkinson Disease and Occupational Therapy Students, run by Ceyhun Türkmen at 1 site in Turkey (Türkiye).
Trial summary
This study aims to examine whether using an artificial intelligence (AI) chatbot can enhance occupational therapy students' learning during a case-based activity focused on Parkinson's disease. Read more about this study
- Who is it for?
- Ages 20 to 23 yearsHealthy volunteers can take part
- Conditions the study is for
- Parkinson Disease, Occupational Therapy Students, Clinical Reasoning
- What is being tested?
- AI Chatbot-Assisted Case-Based Learning and Traditional Case-Based Learning with Standard Materials
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 25 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 1 Jul 2025to 3 Jul 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 to 23 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- Currently enrolled as an undergraduate student in an occupational therapy program
- Registered in the "Neurological Rehabilitation" course during the study semester
- Aged between 20 and 23 years
- Provided written informed consent to participate in the study
Who cannot join
- Previously completed the "Neurological Rehabilitation" course in a prior semester
- Refused or failed to provide informed consent
- Participated in a similar case-based learning study within the past 6 months
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Effect of AI Chatbot-Assisted Case-Based Learning on Clinical Reasoning in Occupational Therapy Students: A Post-Test Only Controlled Trial in Parkinson's Disease Education
This study aims to examine whether using an artificial intelligence (AI) chatbot can enhance occupational therapy students' learning during a case-based activity focused on Parkinson's disease. The research compares two groups of students: one using traditional learning materials, and another using both traditional resources and a conversational AI chatbot. Students in both groups work in teams to analyze the same clinical case and propose assessment and treatment strategies for a hypothetical patient. The main purpose of the study is to evaluate whether the AI chatbot helps improve students' performance in three learning domains: cognitive (knowledge and understanding), affective (empathy and attitudes), and psychomotor (planning and action skills). Students' performance is assessed through a structured written examination. The hypothesis is that students who use the AI chatbot will achieve higher scores, especially in the cognitive and psychomotor domains, compared to those who rely on traditional methods only. The study also examines how students interact with the chatbot and whether they use it to support deeper clinical reasoning. By exploring the role of AI in occupational therapy education, this research seeks to inform future teaching strategies and support the thoughtful integration of digital tools in health professions training.
Read the detailed description
This study investigates the impact of an artificial intelligence (AI) chatbot on occupational therapy (OT) students' clinical reasoning skills within the context of neurological rehabilitation, specifically focusing on Parkinson's disease. The study uses a post-test only control group design and adopts a mixed-methods approach to assess educational outcomes across three learning domains: cognitive, affective, and psychomotor.
A total of 25 OT undergraduate students enrolled in a Neurological Rehabilitation course are randomly assigned to one of two groups: (1) Chatbot Group and (2) Classic Group. Both groups receive the same didactic instruction and engage in a small-group, case-based learning session featuring a hypothetical Parkinson's disease case. The Classic Group uses traditional learning resources such as lecture notes and textbooks, while the Chatbot Group additionally interacts with an AI language model simulating a patient. The chatbot allows students to ask open-ended questions to gather occupational history, explore symptoms, and plan interventions.
After the learning task, all students complete a six-item written exam assessing their performance in the cognitive, affective, and psychomotor domains. Two independent raters, blinded to group assignment, evaluate student responses using a predefined rubric. Inter-rater reliability is calculated. To account for possible differences in baseline academic performance, Grade Point Average (GPA) is used as a covariate in the statistical analysis.
The study also includes a qualitative component in which students in the Chatbot Group submit the queries they posed during the interaction. These queries are analyzed inductively using a content analysis approach to explore how students engage with AI support-whether for conceptual clarification, procedural guidance, or ethical reasoning.
This research addresses a growing interest in how AI-based tools may enhance, supplement, or potentially limit professional training in occupational therapy. Although AI chatbots may offer convenient access to information and support student creativity, concerns remain about their effectiveness in fostering reflective and ethical clinical reasoning. By analyzing both performance data and interaction patterns, this study aims to offer evidence-based insights into the role of digital tools in OT education.
- Conditions
- Parkinson Disease, Occupational Therapy Students, Clinical Reasoning, Neurologic Rehabilitation
- Being tested
- AI Chatbot-Assisted Case-Based Learning, Traditional Case-Based Learning with Standard Materials
- Keywords
- Parkinson Disease, Occupational Therapy Education, Artificial Intelligence, Clinical Reasoning, Case-Based Learning, Chatbot
- Medical subject headings
- Parkinson Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI Chatbot-Assisted Case-Based LearningBehavioural
Participants in this intervention used a conversational AI chatbot integrated into a case-based learning activity focused on Parkinson's disease. The chatbot simulated a virtual client and responded to student questions in natural language. Students used the chatbot to gather occupational history, clarify symptoms, and explore intervention planning options during a structured 90-minute session.
Traditional Case-Based Learning with Standard MaterialsBehavioural
Participants in this intervention completed the same Parkinson's disease case analysis using only traditional educational materials, such as lecture notes, textbooks, and class handouts. No digital or AI-based tool was used. The session was instructor-guided and lasted 90 minutes, during which students worked collaboratively to assess the case and develop intervention plans.
| Study group | Role | What they receive |
|---|---|---|
| AI Chatbot-Assisted Case-Based Learning | Experimental | Participants in this arm completed a Parkinson's disease case analysis using an AI chatbot designed to simulate interaction with a virtual client. The chatbot provided real-time, natural language responses to student queries. Students worked in small groups to develop problem lists, goals, and intervention plans based on the simulated interaction. Receives: Behavioral: AI Chatbot-Assisted Case-Based Learning |
| Traditional Case-Based Learning | Active comparator | Participants in this arm completed the same Parkinson's disease case analysis using traditional learning resources, such as lecture notes and textbooks. They worked in small groups to develop problem lists, goals, and intervention plans without access to the AI chatbot or any digital simulation tool. Receives: Behavioral: Traditional Case-Based Learning with Standard Materials |
What is being measured
The primary outcome is the main question the study is designed to answer.
Total Post-Test Score (0-24 points)
The total score on a six-item written examination measuring clinical reasoning performance in occupational therapy students. The test includes items covering cognitive, affective, and psychomotor domains. Each item is scored by two independent, blinded raters. The total possible score is 24 points. Higher scores indicate better clinical reasoning performance.
Measured: Immediately after the intervention (within the same session)
Secondary outcomes (3)
Cognitive Domain Score (0-8 points)
Subscore from the written examination assessing knowledge and understanding of clinical reasoning in occupational therapy. Scored by two blinded raters. Higher scores indicate better performance in the cognitive domain.
Measured: Immediately after the intervention
Affective Domain Score (0-8 points)
Subscore from the written examination evaluating empathy, professional attitude, and reflective thinking in clinical reasoning. Scored by two blinded raters. Higher scores reflect stronger affective learning outcomes.
Measured: Immediately after the intervention
Psychomotor Domain Score (0-8 points)
Subscore from the written examination assessing planning and implementation of occupational therapy interventions. Scored by two blinded raters. Higher scores indicate better applied reasoning and intervention planning.
Measured: Immediately after the intervention
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted1 Jul 2025
- Study start1 Jul 2025
- Primary completion2 Jul 2025
- Study completion3 Jul 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Parkinson DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Participants were randomly assigned to one of two parallel groups. The intervention group used an AI chatbot to support clinical reasoning during a Parkinson's disease case analysis, while the control group used traditional learning resources. Both groups completed the same task and post-intervention assessment.
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 25 participants (actual)
Sponsor and investigators
- Lead sponsor
- Ceyhun Türkmen
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Ceyhun Türkmen, Çankırı Karatekin University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07045077
- Sponsor's protocol ID
- F109843008AF4827
- Acronym
- AI-PD-OT25
- Status last verified
- Jul 2025
- First submitted
- 22 Jun 2025
- Last updated
- 8 Jul 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data will not be shared due to the educational context of the study, the small sample size, and institutional privacy policies. The data were collected solely for internal academic evaluation and are not intended for secondary use.
Publications
Veltkamp DMJ, Nijhoff MF, van den Broek DAJ, Buntinx M, Kers J, Engelse MA, Huurman VAL, Roelen DL, Heidt S, Alwayn IPJ, de Koning EJP, de Vries APJ. Chronic Pancreas Allograft Rejection Followed by Successful HLA-Incompatible Islet Alloautotransplantation: A Novel Strategy? Transpl Int. 2023 Aug 24;36:11505. doi: 10.3389/ti.2023.11505. eCollection 2023.
PubMed 37692453
Study at a glance
From the registry record, last updated by the sponsor on 8 Jul 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Effect of AI Chatbot-Assisted Case-Based Learning on Clinical Reasoning in Occupational Therapy Students: A Post-Test Only Controlled Trial in Parkinson's Disease Education
- ClinicalTrials.gov ID
- NCT07045077
- Acronym / sponsor ID
- AI-PD-OT25 / F109843008AF4827
- Conditions
- Parkinson Disease, Occupational Therapy Students, Clinical Reasoning, Neurologic Rehabilitation
- Keywords
- Parkinson Disease, Occupational Therapy Education, Artificial Intelligence, Clinical Reasoning, Case-Based Learning, Chatbot
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 25 participants (actual)
- Lead sponsor
- Ceyhun TürkmenUniversity, hospital or other
- Study start
- 1 Jul 2025 (actual)
- Primary completion
- 2 Jul 2025 (actual)
- Study completion
- 3 Jul 2025 (actual)
- First posted
- 1 Jul 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study aims to examine whether using an artificial intelligence (AI) chatbot can enhance occupational therapy students' learning during a case-based activity focused on Parkinson's disease. The research compares two groups of students: one using traditional learning materials, and another using both traditional resources and a conversational AI chatbot. Students in both groups work in teams to analyze the same clinical case and propose assessment and treatment strategies for a hypothetical patient. The main purpose of the study is to evaluate whether the AI chatbot helps improve students' performance in three learning domains: cognitive (knowledge and understanding), affective (empathy and attitudes), and psychomotor (planning and action skills). Students' performance is assessed through a structured written examination. The hypothesis is that students who use the AI chatbot will achieve higher scores, especially in the cognitive and psychomotor domains, compared to those who rely on traditional methods only. The study also examines how students interact with the chatbot and whether they use it to support deeper clinical reasoning. By exploring the role of AI in occupational therapy education, this research seeks to inform future teaching strategies and support the thoughtful integration of digital tools in health professions training.
Detailed description
This study investigates the impact of an artificial intelligence (AI) chatbot on occupational therapy (OT) students' clinical reasoning skills within the context of neurological rehabilitation, specifically focusing on Parkinson's disease. The study uses a post-test only control group design and adopts a mixed-methods approach to assess educational outcomes across three learning domains: cognitive, affective, and psychomotor.
A total of 25 OT undergraduate students enrolled in a Neurological Rehabilitation course are randomly assigned to one of two groups: (1) Chatbot Group and (2) Classic Group. Both groups receive the same didactic instruction and engage in a small-group, case-based learning session featuring a hypothetical Parkinson's disease case. The Classic Group uses traditional learning resources such as lecture notes and textbooks, while the Chatbot Group additionally interacts with an AI language model simulating a patient. The chatbot allows students to ask open-ended questions to gather occupational history, explore symptoms, and plan interventions.
After the learning task, all students complete a six-item written exam assessing their performance in the cognitive, affective, and psychomotor domains. Two independent raters, blinded to group assignment, evaluate student responses using a predefined rubric. Inter-rater reliability is calculated. To account for possible differences in baseline academic performance, Grade Point Average (GPA) is used as a covariate in the statistical analysis.
The study also includes a qualitative component in which students in the Chatbot Group submit the queries they posed during the interaction. These queries are analyzed inductively using a content analysis approach to explore how students engage with AI support-whether for conceptual clarification, procedural guidance, or ethical reasoning.
This research addresses a growing interest in how AI-based tools may enhance, supplement, or potentially limit professional training in occupational therapy. Although AI chatbots may offer convenient access to information and support student creativity, concerns remain about their effectiveness in fostering reflective and ethical clinical reasoning. By analyzing both performance data and interaction patterns, this study aims to offer evidence-based insights into the role of digital tools in OT education.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- Model description
- Participants were randomly assigned to one of two parallel groups. The intervention group used an AI chatbot to support clinical reasoning during a Parkinson's disease case analysis, while the control group used traditional learning resources. Both groups completed the same task and post-intervention assessment.
| Arm | Type | Receives |
|---|---|---|
| AI Chatbot-Assisted Case-Based Learning | Experimental | Behavioral: AI Chatbot-Assisted Case-Based LearningParticipants in this arm completed a Parkinson's disease case analysis using an AI chatbot designed to simulate interaction with a virtual client. The chatbot provided real-time, natural language responses to student queries. Students worked in small groups to develop problem lists, goals, and intervention plans based on the simulated interaction. |
| Traditional Case-Based Learning | Active comparator | Behavioral: Traditional Case-Based Learning with Standard MaterialsParticipants in this arm completed the same Parkinson's disease case analysis using traditional learning resources, such as lecture notes and textbooks. They worked in small groups to develop problem lists, goals, and intervention plans without access to the AI chatbot or any digital simulation tool. |
Who may qualify
- Ages
- 20 to 23 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (4 listed)
- Currently enrolled as an undergraduate student in an occupational therapy program
- Registered in the "Neurological Rehabilitation" course during the study semester
- Aged between 20 and 23 years
- Provided written informed consent to participate in the study
Key exclusion criteria (3 listed)
- Previously completed the "Neurological Rehabilitation" course in a prior semester
- Refused or failed to provide informed consent
- Participated in a similar case-based learning study within the past 6 months
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI Chatbot-Assisted Case-Based LearningParticipants in this intervention used a conversational AI chatbot integrated into a case-based learning activity focused on Parkinson's disease. The chatbot simulated a virtual client and responded to student questions in natural language. Students used the chatbot to gather occupational history, clarify symptoms, and explore intervention planning options during a structured 90-minute session. | Behavioural | AI Chatbot-Assisted Case-Based Learning |
| Traditional Case-Based Learning with Standard MaterialsParticipants in this intervention completed the same Parkinson's disease case analysis using only traditional educational materials, such as lecture notes, textbooks, and class handouts. No digital or AI-based tool was used. The session was instructor-guided and lasted 90 minutes, during which students worked collaboratively to assess the case and develop intervention plans. | Behavioural | Traditional Case-Based Learning |
Primary outcome
Total Post-Test Score (0-24 points)
Time frame: Immediately after the intervention (within the same session)
The total score on a six-item written examination measuring clinical reasoning performance in occupational therapy students. The test includes items covering cognitive, affective, and psychomotor domains. Each item is scored by two independent, blinded raters. The total possible score is 24 points. Higher scores indicate better clinical reasoning performance.
3 secondary outcomes
Cognitive Domain Score (0-8 points)
Time frame: Immediately after the intervention
Affective Domain Score (0-8 points)
Time frame: Immediately after the intervention
Psychomotor Domain Score (0-8 points)
Time frame: Immediately after the intervention
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Jul 2025.
- Results publication: PubMed 37692453Veltkamp DMJ, Nijhoff MF, van den Broek DAJ, Buntinx M, Kers J, Engelse MA, Huurman VAL, Roelen DL, Heidt S, Alwayn IPJ, de Koning EJP, de Vries APJ. Chronic Pancreas Allograft Rejection Followed by Successful HLA-Incompatible Islet Alloautotransplantation: A Novel Strategy? Transpl Int. 2023 Aug 24;36:11505. doi: 10.3389/ti.2023.11505. eCollection 2023.
- Individual participant dataSharing planned: No. Individual participant data will not be shared due to the educational context of the study, the small sample size, and institutional privacy policies. The data were collected solely for internal academic evaluation and are not intended for secondary use.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI Chatbot-Assisted Case-Based Learning and Traditional Case-Based Learning with Standard Materials in people with Parkinson Disease and Occupational Therapy Students, run by Ceyhun Türkmen at 1 site in Turkey (Türkiye).
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 8 Jul 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Turkey (Türkiye). Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Total Post-Test Score (0-24 points) (time frame: Immediately after the intervention (within the same session)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07045077, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 Jul 2025.