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SCI-Expanded JCR Q1 Özgün Makale Scopus
Physiotherapy students' acceptance of AI-based chatbots (including ChatGPT) in education: a multi-institutional study from Turkey
BMC MEDICAL EDUCATION 2026 Cilt 26 Sayı 1
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Background: AI-based chatbots are increasingly used in health professions education to support learning tasks (e.g., studying, drafting assignments, and summarizing content). Evidence on the acceptance of AI-based chatbots, including ChatGPT, in physiotherapy education is limited. This study examined physiotherapy students’ acceptance in Turkey, focusing on perceived usefulness (PU) and perceived ease of use (PEOU) within the Technology Acceptance Model (TAM). Methods: A cross-sectional online survey (Google Forms) using convenience sampling was conducted with undergraduate physiotherapy students from nine universities across different regions of Turkey (May–June 2025). Digital informed consent was obtained, and responses were anonymous. PU and PEOU were assessed using Turkish TAM items contextualized for AI-based chatbot use. Psychometric properties were re-evaluated in the present sample (Cronbach’s alpha; PCA with KMO/Bartlett, with an EFA sensitivity analysis using PAF with Promax rotation), and group differences, correlations, and predictors of PU and PEOU were analyzed. Results: A total of 478 students (79.3% female) were included. Mean PU and PEOU scores were 52.91 ± 7.47 and 51.73 ± 6.49, respectively (scale range 14–70). PU and PEOU were moderately correlated (r = 0.450, p < 0.001). Technology interest was the strongest predictor of PU (β = 0.283, p < 0.001) and PEOU (β = 0.371, p < 0.001), while year of study had a smaller effect on PU (β = 0.112, p = 0.011); gender was not significant in regression models. Exploratory factor-analytic results suggested PU was unidimensional, whereas PEOU showed two exploratory facets (learnability/clarity and control/flexibility). Conclusions: Physiotherapy students expressed cautious optimism toward AI-based chatbots such as ChatGPT. Acceptance was higher among students with greater technology interest and, to a lesser extent, in advanced study years. These findings support stage-sensitive integration and targeted AI literacy, emphasizing ethical awareness and source verification for safe and effective learning.
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Kaynak: BMC MEDICAL EDUCATION
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Bu makaleye, sistemimizdeki Scopus veritabanında bulunan 0 makale atıf yapmıştır. Scopus genel atıf sayısı: 5.

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Makale Bilgileri

Dergi BMC MEDICAL EDUCATION
ISSN 1472-6920
Yıl 2026 / 1. ay
Cilt / Sayı 26 / 1
Sayfalar 1 – 11
Makale Türü Özgün Makale
Hakemlik Hakemli
Endeks SCI-Expanded
JCR Quartile Q1
Teşvik Puanı 3,60 · YÖKSİS Akademik Teşvik
Yayın Dili İngilizce
Kapsam Uluslararası
Toplam Yazar 5 kişi
Erişim Türü Elektronik
Alan Sağlık Bilimleri Temel Alanı Fizyoterapi ve Rehabilitasyon

YÖKSİS Yazar Kaydı

Yazar Adı GÜLER MEHMET AKİF,Dağ Sümeyra,Kayal Senem,Can Merve,Şimşekkaya Sena Nur
YÖKSİS ID 9330757

Metrikler

Scopus Atıf 5
Havuz Atıfları 0
JCR Quartile Q1
Teşvik Puanı 3,60
Yazar Sayısı 5