Artificial Intelligence (AI)NCT06941402
Physiotherapists and Artificial Intelligence
An observational study of Artificial Intelligence (AI) and Physiotherapist Students, run by Uşak University at 4 sites in Turkey (Türkiye).
Trial summary
This study is a cross-sectional study designed within the scope of the descriptive and relational screening model of quantitative research methods. The research aims to evaluate the digital competence levels, attitudes towards artificial intelligence and artificial intelligence acceptance levels of undergraduate… Read more about this study
- Who is it for?
- Ages 18 to 45 yearsHealthy volunteers can take part
- Conditions the study is for
- Artificial Intelligence (AI), Physiotherapist Students, Digital Competences
- Type of treatment
- Pill or oral medicine
- How many people
- 552 participants
- Where
- 4 sitesTurkey (Türkiye)
- Study dates
- 11 Apr 2025to 1 Jun 2025
- Phase
- Observational
- 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 18 to 45 years
- All sexes
- Healthy volunteers accepted
- Adult
Study population: The universe of the study is undergraduate students studying in the Department of Physiotherapy and Rehabilitation at Okan University, Faculty of Health Sciences, Alanya, İnönü, Pamukkale.
Who may be able to join
- Consisting of students studying in a physiotherapy and rehabilitation undergraduate program in Türkiye,
- Agreeing to participate in the research voluntarily and approving the online informed consent form,
- Being 18 years of age or older,
- Completely filling out the survey form,
- Actively using at least one digital device (smartphone, computer, tablet, etc.)
Who cannot join
- Studying in any department other than the physiotherapy department,
- Filling out the survey without approving the informed consent form,
- Filling out the survey form incompletely or incorrectly,
- Being under the age of 18
Trial locations and contacts
4 sites in 1 country.
Turkey (Türkiye)4 sites
Alanya Alaaddin Keykubat University
Antalya, Antalya
Pamukkale University
Denizli, Denizli
Okan University
Istanbul, Istanbul
İnönü University
Malatya, Malatya
About this study
Official title: Adaptation of Future Physiotherapists to the Artificial Intelligence Era: Artificial Intelligence Attitude, Acceptance and Digital Competence
This study is a cross-sectional study designed within the scope of the descriptive and relational screening model of quantitative research methods. The research aims to evaluate the digital competence levels, attitudes towards artificial intelligence and artificial intelligence acceptance levels of undergraduate students of the physiotherapy department and to reveal the relationships between these variables.
Research Questions
Read more
- What are the digital competence levels of physiotherapy students?
- What are the attitude levels of physiotherapy students towards artificial intelligence?
- What are the acceptance levels of physiotherapy students towards artificial intelligence technologies?
- Is there a significant relationship between the level of digital competence and the attitude towards artificial intelligence?
- Is there a significant relationship between the level of digital competence and the acceptance of artificial intelligence technologies?
- Is there a significant relationship between the attitude towards artificial intelligence and the acceptance level of artificial intelligence technologies?
- Is there a significant difference between the participants' digital competence, attitudes towards artificial intelligence and acceptance levels according to variables such as gender, grade level and duration of digital tool use? The universe of the research will consist of undergraduate students studying in the Department of Physiotherapy and Rehabilitation at the Faculty of Health Sciences of Alanya, İnönü, Pamukkale, Okan University. The sample of the research is planned to be approximately 600 students who are randomly selected from four different universities to represent different geographical regions and are determined on a voluntary basis.
The research is planned to consist of students studying in the undergraduate program of physiotherapy and rehabilitation in Türkiye. While collecting the data, the Introductory Information Form, Digital Competencies Scale for University Students, Scale of Attitude of University Students Towards Artificial Intelligence, and Productive Artificial Intelligence Acceptance Scale will be used.
The collected data will be analyzed using the SPSS (Statistical Package for Social Sciences) program. The Kolmogorov-Smirnov and Shapiro-Wilk tests will be used to evaluate whether the data are normally distributed. In variables that are normally distributed: Mean, standard deviation, independent sample t-test, ANOVA and Pearson correlation test will be used. In non-normal distribution: Median, minimum-maximum, Mann-Whitney U test, Kruskal Wallis test, Spearman correlation tests will be applied. In addition, regression analysis will be performed to evaluate the relationships between students' sociodemographic information, digital competence, artificial intelligence attitude and artificial intelligence acceptance levels. P < 0.05 will be accepted as the significance level.
Read the detailed description
Rapid developments in digitalization and artificial intelligence technologies have caused significant changes in the way healthcare services are provided. Today, artificial intelligence-supported applications are actively used in many areas in the healthcare field, from early diagnosis of diseases to treatment, from patient follow-up to personalized care planning. In disciplines where clinical decision-making processes are important, such as physiotherapy and rehabilitation, digital tools and artificial intelligence systems are integrated into the field with motion analysis, exercise tracking, rehabilitation robots, virtual reality-based treatments and artificial intelligence-supported mobile applications. This technological transformation affects not only professional practice but also vocational education. The digital competence levels of university students receiving health education, their capacity to adopt technology and their attitudes towards artificial intelligence are of critical importance in terms of both their individual professional development and post-graduation service quality. Understanding how ready physiotherapy students in particular are for the digital transformation process will guide both the restructuring of educational programs and the harmonization of the profession with technological developments. Studies have shown that health sciences students generally have access to digital tools, but they experience various inadequacies in using these tools effectively and consciously. In addition, it is reported that individuals who develop a positive attitude towards artificial intelligence adapt to these technologies faster and achieve more efficient results in education and clinical practices. However, the number of holistic studies in the literature, especially those specific to physiotherapy students, where artificial intelligence attitudes, technology acceptance and digital competence levels are evaluated together, is quite limited.
Therefore, the rationale of this research is to evaluate the digital competence levels of physiotherapy students, their attitudes towards artificial intelligence and their tendency to accept artificial intelligence technologies, to evaluate their adaptation processes to digitalization in the health field and to produce scientific data that will contribute to educational policies, course content and clinical practice strategies in this context.
The main purpose of this research is to evaluate the digital competence levels of physiotherapy undergraduate students, their attitudes towards artificial intelligence and their tendency to accept artificial intelligence technologies. In addition, by examining the possible relationships between these three variables, it is aimed to reveal to what extent students have developed their professional competencies in the age of digital transformation and artificial intelligence. In this context, the data to be obtained will contribute to the determination of educational needs for digital literacy and artificial intelligence-based applications in the field of health; and will pave the way for understanding the level of adaptation of future physiotherapists to technological developments.
- Conditions
- Artificial Intelligence (AI), Physiotherapist Students, Digital Competences, Acceptance of Artificial Intelligence, Artificial Intelligence Attitude
- Keywords
- physiotherapist, artificial intelligence, digital age
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| physiotherapy students | The acceptance attitude of physiotherapy students towards artificial intelligence and their digital competencies will be conducted in the form of a survey.The characteristics of the study group are that they consist of students studying in a physiotherapy and rehabilitation undergraduate program in Türkiye, that they agree to participate in the study voluntarily and approve the online informed consent form, that they are 18 years of age or older, that they fill out the survey form completely, and that they actively use at least one digital device (smartphone, computer, tablet, etc.). |
What is being measured
The primary outcome is the main question the study is designed to answer.
Digital Competencies Scale for University Students
It is a valid and reliable scale that measures the digital competences of university students, developed based on the European Digital Competence Framework (DigComp). The original version of the Basic Digital Competences of University Students 2.0 - COBADI scale, developed by López-Meneses et al. (2013), has 4 factors and 31 items. The 4 factors in the COBADI scale are determined as "Competences related to the use of ICT in social communication and collaborative learning", "Competences related to the use of ICT in research", "Interpersonal competences in the use of ICT in the university context" and "University virtual tools and social communication". There are 12 items in the first factor, 11 items in the second factor, and 4 items each in the third and fourth factors. A 4-point Likert type was used in the rating of the scale. Within the scope of the ratings, 1 indicates the least level of competence, while 4 indicates the highest level of competence. The 4-point Likert-type scale co
Measured: 1 week
Secondary outcomes (2)
University Students' Attitude Scale Towards Artificial Intelligence
University Students' Attitude Scale Towards Artificial Intelligence : It is a 5-point Likert-type scale that aims to measure students' feelings, thoughts and attitudes towards artificial intelligence. The scale consists of cognitive, affective and behavioral dimensions. The sub-dimensions of the scale are; Interest in artificial intelligence, Concerns about artificial intelligence, Ethical aspects and social effects of artificial intelligence, Opportunities and threats related to the use of artificial intelligence in education. Its validity and reliability in Turkish were made by Turgut and Kunuroğlu (2025). It is a 5-point Likert-type scale (1: Strongly Disagree - 5: Strongly Agree) consisting of 26 questions. Cronbach Alpha of the scale: 0.89 (total scale), varies between 0.78-0.87 in the sub-dimensions
Measured: 1 week
Generative Artificial Intelligence Acceptance Scale
A tool to determine the extent to which individuals accept artificial intelligence technologies and how willing they are to use these technologies. To determine the level to which generative artificial intelligence tools (ChatGPT, DALL E, Bard, etc.) are accepted by users and whether they are adopted or not. It was prepared to measure the attitudes, usage intentions and perceptions of individuals in the field of education, especially teacher candidates, students and academics, towards generative artificial intelligence. The scale was developed based on Davis's Technology Acceptance Model (TAM). According to this model, acceptance of technology is related to how useful and easy to use the individual perceives the technology. It is a 5-point Likert-type scale with 20 questions. It is as follows: 1: Strongly Disagree - 5: Strongly Agree. Confirmatory Factor Analysis (CFA) was performed for construct validity and it was determined that
Measured: 1 week
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Apr 2025
- Study start11 Apr 2025
- Primary completion1 Jun 2025
- Study completion1 Jun 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Artificial Intelligence (AI)Studies 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
- Observational
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 552 participants (actual)
Sponsor and investigators
- Lead sponsor
- Uşak University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Kevser Gürsan, Uşak University
- Investigators
- Kevser G Gursan, Dr., Principal investigator, Uşak University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06941402
- Sponsor's protocol ID
- 607-607-05
- Status last verified
- Jun 2025
- First submitted
- 15 Apr 2025
- Last updated
- 6 Jun 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: In order to protect participant confidentiality and comply with the confidentiality commitment approved by the ethics committee, no sharing of individual-level data is planned. In addition, the ethics committee decision that approved the study covers data use with limited access only. Therefore, it may not be possible to share IPD data publicly.
Study at a glance
From the registry record, last updated by the sponsor on 6 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Adaptation of Future Physiotherapists to the Artificial Intelligence Era: Artificial Intelligence Attitude, Acceptance and Digital Competence
- ClinicalTrials.gov ID
- NCT06941402
- Acronym / sponsor ID
- 607-607-05
- Conditions
- Artificial Intelligence (AI), Physiotherapist Students, Digital Competences, Acceptance of Artificial Intelligence, Artificial Intelligence Attitude
- Keywords
- physiotherapist, artificial intelligence, digital age
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 552 participants (actual)
- Lead sponsor
- Uşak UniversityUniversity, hospital or other
- Study start
- 11 Apr 2025 (actual)
- Primary completion
- 1 Jun 2025 (actual)
- Study completion
- 1 Jun 2025 (actual)
- First posted
- 23 Apr 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 is a cross-sectional study designed within the scope of the descriptive and relational screening model of quantitative research methods. The research aims to evaluate the digital competence levels, attitudes towards artificial intelligence and artificial intelligence acceptance levels of undergraduate students of the physiotherapy department and to reveal the relationships between these variables.
Research Questions
- What are the digital competence levels of physiotherapy students?
- What are the attitude levels of physiotherapy students towards artificial intelligence?
- What are the acceptance levels of physiotherapy students towards artificial intelligence technologies?
- Is there a significant relationship between the level of digital competence and the attitude towards artificial intelligence?
- Is there a significant relationship between the level of digital competence and the acceptance of artificial intelligence technologies?
- Is there a significant relationship between the attitude towards artificial intelligence and the acceptance level of artificial intelligence technologies?
- Is there a significant difference between the participants' digital competence, attitudes towards artificial intelligence and acceptance levels according to variables such as gender, grade level and duration of digital tool use? The universe of the research will consist of undergraduate students studying in the Department of Physiotherapy and Rehabilitation at the Faculty of Health Sciences of Alanya, İnönü, Pamukkale, Okan University. The sample of the research is planned to be approximately 600 students who are randomly selected from four different universities to represent different geographical regions and are determined on a voluntary basis.
The research is planned to consist of students studying in the undergraduate program of physiotherapy and rehabilitation in Türkiye. While collecting the data, the Introductory Information Form, Digital Competencies Scale for University Students, Scale of Attitude of University Students Towards Artificial Intelligence, and Productive Artificial Intelligence Acceptance Scale will be used.
The collected data will be analyzed using the SPSS (Statistical Package for Social Sciences) program. The Kolmogorov-Smirnov and Shapiro-Wilk tests will be used to evaluate whether the data are normally distributed. In variables that are normally distributed: Mean, standard deviation, independent sample t-test, ANOVA and Pearson correlation test will be used. In non-normal distribution: Median, minimum-maximum, Mann-Whitney U test, Kruskal Wallis test, Spearman correlation tests will be applied. In addition, regression analysis will be performed to evaluate the relationships between students' sociodemographic information, digital competence, artificial intelligence attitude and artificial intelligence acceptance levels. P < 0.05 will be accepted as the significance level.
Detailed description
Rapid developments in digitalization and artificial intelligence technologies have caused significant changes in the way healthcare services are provided. Today, artificial intelligence-supported applications are actively used in many areas in the healthcare field, from early diagnosis of diseases to treatment, from patient follow-up to personalized care planning. In disciplines where clinical decision-making processes are important, such as physiotherapy and rehabilitation, digital tools and artificial intelligence systems are integrated into the field with motion analysis, exercise tracking, rehabilitation robots, virtual reality-based treatments and artificial intelligence-supported mobile applications. This technological transformation affects not only professional practice but also vocational education. The digital competence levels of university students receiving health education, their capacity to adopt technology and their attitudes towards artificial intelligence are of critical importance in terms of both their individual professional development and post-graduation service quality. Understanding how ready physiotherapy students in particular are for the digital transformation process will guide both the restructuring of educational programs and the harmonization of the profession with technological developments. Studies have shown that health sciences students generally have access to digital tools, but they experience various inadequacies in using these tools effectively and consciously. In addition, it is reported that individuals who develop a positive attitude towards artificial intelligence adapt to these technologies faster and achieve more efficient results in education and clinical practices. However, the number of holistic studies in the literature, especially those specific to physiotherapy students, where artificial intelligence attitudes, technology acceptance and digital competence levels are evaluated together, is quite limited.
Therefore, the rationale of this research is to evaluate the digital competence levels of physiotherapy students, their attitudes towards artificial intelligence and their tendency to accept artificial intelligence technologies, to evaluate their adaptation processes to digitalization in the health field and to produce scientific data that will contribute to educational policies, course content and clinical practice strategies in this context.
The main purpose of this research is to evaluate the digital competence levels of physiotherapy undergraduate students, their attitudes towards artificial intelligence and their tendency to accept artificial intelligence technologies. In addition, by examining the possible relationships between these three variables, it is aimed to reveal to what extent students have developed their professional competencies in the age of digital transformation and artificial intelligence. In this context, the data to be obtained will contribute to the determination of educational needs for digital literacy and artificial intelligence-based applications in the field of health; and will pave the way for understanding the level of adaptation of future physiotherapists to technological developments.
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| physiotherapy students | – | –The acceptance attitude of physiotherapy students towards artificial intelligence and their digital competencies will be conducted in the form of a survey.The characteristics of the study group are that they consist of students studying in a physiotherapy and rehabilitation undergraduate program in Türkiye, that they agree to participate in the study voluntarily and approve the online informed consent form, that they are 18 years of age or older, that they fill out the survey form completely, and that they actively use at least one digital device (smartphone, computer, tablet, etc.). |
Who may qualify
- Ages
- 18 to 45 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
- Study population
- The universe of the study is undergraduate students studying in the Department of Physiotherapy and Rehabilitation at Okan University, Faculty of Health Sciences, Alanya, İnönü, Pamukkale.
Key inclusion criteria (5 listed)
- Consisting of students studying in a physiotherapy and rehabilitation undergraduate program in Türkiye,
- Agreeing to participate in the research voluntarily and approving the online informed consent form,
- Being 18 years of age or older,
- Completely filling out the survey form,
- Actively using at least one digital device (smartphone, computer, tablet, etc.)
Key exclusion criteria (4 listed)
- Studying in any department other than the physiotherapy department,
- Filling out the survey without approving the informed consent form,
- Filling out the survey form incompletely or incorrectly,
- Being under the age of 18
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Digital Competencies Scale for University Students
Time frame: 1 week
It is a valid and reliable scale that measures the digital competences of university students, developed based on the European Digital Competence Framework (DigComp). The original version of the Basic Digital Competences of University Students 2.0 - COBADI scale, developed by López-Meneses et al. (2013), has 4 factors and 31 items. The 4 factors in the COBADI scale are determined as "Competences related to the use of ICT in social communication and collaborative learning", "Competences related to the use of ICT in research", "Interpersonal competences in the use of ICT in the university context" and "University virtual tools and social communication". There are 12 items in the first factor, 11 items in the second factor, and 4 items each in the third and fourth factors. A 4-point Likert type was used in the rating of the scale. Within the scope of the ratings, 1 indicates the least level of competence, while 4 indicates the highest level of competence. The 4-point Likert-type scale co
2 secondary outcomes
University Students' Attitude Scale Towards Artificial Intelligence
Time frame: 1 week
Generative Artificial Intelligence Acceptance Scale
Time frame: 1 week
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 6 Jun 2025.
- Individual participant dataSharing planned: No. In order to protect participant confidentiality and comply with the confidentiality commitment approved by the ethics committee, no sharing of individual-level data is planned. In addition, the ethics committee decision that approved the study covers data use with limited access only. Therefore, it may not be possible to share IPD data publicly.
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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.
Kevser G Gursan, Dr. principal investigator
Uşak University
4 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Artificial Intelligence (AI) and Physiotherapist Students, run by Uşak University at 4 sites 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 5 inclusion and 4 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 6 Jun 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 4 sites 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?
Digital Competencies Scale for University Students (time frame: 1 week). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 6 Jun 2025.