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The aim of this study is to analyze, using a mixed-methods approach, the attitudes, perceptions, levels of technology acceptance, and competencies in the use of generative artificial intelligence among healthcare professionals working in the field of orthotics and prosthetics.
The study will reveal how the technological transformation in orthotics and prosthetics is perceived by healthcare professionals, and will also identify the professional requirements, barriers, and opportunities for integrating artificial intelligence technologies into practice.
In this way, it aims to provide a scientific reference for decision-makers to support the updating of professional education programs in orthotics and prosthetics, the development of institutional policies, and the wider adoption of AI-supported clinical applications.
Healthcare professionals working in the field of orthotics and prosthetics who voluntarily agree to participate will be included in the study. Based on the G*Power analysis, a minimum of 159 participants is required to achieve 95% statistical power at a 5% significance level (|ρ| = 0.277). Considering a possible sample loss of 10%, it was determined that the study should be conducted with at least 175 healthcare professionals.
For the quantitative part of the study, the Technology Acceptance Model Scale will be used to determine technology acceptance levels; the General Attitude Toward Artificial Intelligence Scale will be used to measure general attitudes toward AI; the Generative Artificial Intelligence Use and Competency Scale will be used to assess AI usage skills and AI-supported learning motivation; and the Artificial Intelligence Perception and Attitude Scale will be used to examine AI perceptions and usage tendencies.
For the qualitative part of the study, face-to-face interviews will be conducted with participants who actively use artificial intelligence in their field, using 8 semi-structured questions designed to evaluate AI awareness, its impact on clinical workflow, economic feasibility, and ethical and safety concerns. After the individual interviews, an online focus group interview will be conducted with 5 participants who use AI most intensively. The focus group will consist of 7 questions prepared to explore healthcare professionals' shared perceptions, usage experiences, professional concerns, and future suggestions regarding artificial intelligence through group interaction.
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| Measure | Description | Time Frame |
|---|---|---|
| Technology Acceptance Model Scale | The scale was developed by Tubaishat to determine the level of technology acceptance. It consists of 28 items and two sub-dimensions: "Perceived Usefulness" and "Perceived Ease of Use." It is scored using a five-point Likert scale. A high score indicates a high level of technology acceptance, while a low score indicates a low level of technology acceptance. | 5 minutes |
| Demographic Information Form | Participants' name, surname, gender, age, department of last graduation, highest level of education, total professional experience in the orthotics and prosthetics field, the institution they work at, and their position in the institution will be recorded. | 5 minutes |
| General Attitude Toward Artificial Intelligence Scale | This scale was developed by Schepman and Rodway in 2020 to measure individuals' general attitudes toward artificial intelligence. It consists of 20 items, including 12 items measuring positive attitudes toward AI and 8 items measuring negative attitudes toward AI. It is scored using a five-point Likert scale. A high score on the positive attitude subscale indicates strong positive attitudes toward AI, while a high score on the negative attitude subscale indicates strong negative attitudes toward AI. | 5 minutes |
| Generative Artificial Intelligence Use and Competency Scale | This scale was developed by Arslankara et al. in 2024 to measure individuals' ability to use generative artificial intelligence tools and their competency in using these tools effectively. It consists of two sections: "AI Use Competency" and "AI-Supported Learning Motivation." The first section includes 10 items, and the second section includes 9 items. It is scored using a five-point Likert scale. A high score on this scale indicates a high level of competency in effectively using generative AI tools and strong motivation for AI-supported learning, while a low score indicates low competency and motivation. |
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Inclusion Criteria:
Exclusion Criteria:
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HEALTHCARE PROFESSIONALS WORKING IN THE ORTHOTICS AND PROSTHETICS FIELD
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Istanbul Medipol Üniversitesi | Istanbul | Kavacık | 34040 | Turkey (Türkiye) |
Individual participant data will not be shared. This study does not include patient data; the data consist of survey responses and qualitative interview data obtained from health professionals working in orthotics-prosthetics practice. Because the qualitative data include detailed participant narratives, there may be a risk of indirect identification even after anonymization. Therefore, individual-level data will not be shared with other researchers. Only aggregated findings will be reported in publications.
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| ID | Term |
|---|---|
| D001519 | Behavior |
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| 5 minutes |
| Artificial Intelligence Perception and Attitude Scale | This scale was developed by Dinler in 2025 to comprehensively evaluate individuals' perceptions and attitudes toward artificial intelligence technologies. It includes four sub-dimensions: positive perception, negative perception, generative media use, and chatbot interaction. The scale consists of 24 items and is rated on a seven-point Likert scale. A high score on this scale indicates high levels of positive perception, usage, and interaction with AI technologies, while a low score indicates weak perceptions and attitudes toward AI. | 5 minutes |
| Semi-Structured Interview Form | The interview form includes 8 questions categorized under the following themes: AI awareness and professional perception, impact on clinical workflow and performance, ethical issues, safety and risk of errors, economic and institutional feasibility, and future expectations and changes in professional roles. | 40-60 minute |
| Focus Group Interview Form | The form includes 7 questions categorized under the following themes: AI awareness and perception, impact on clinical workflow and performance, economic feasibility, ethics, safety and professional responsibility, education, usability, and future expectations. | 60- 90 minute |