The relationships of personality traits on perceptions and attitudes of dentistry students towards AI

Abstract Introduction Artificial intelligence (AI) has gained significant attention in dentistry due to its potential to revolutionize practice and improve patient outcomes. However, dentists’ views and attitudes toward technology can affect the application of AI. This perception and attitude can be...

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Main Authors: Furkan Ozbey, Yasin Yasa
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Medical Education
Subjects:
Online Access:https://doi.org/10.1186/s12909-024-06630-5
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author Furkan Ozbey
Yasin Yasa
author_facet Furkan Ozbey
Yasin Yasa
author_sort Furkan Ozbey
collection DOAJ
description Abstract Introduction Artificial intelligence (AI) has gained significant attention in dentistry due to its potential to revolutionize practice and improve patient outcomes. However, dentists’ views and attitudes toward technology can affect the application of AI. This perception and attitude can be affected by the personality traits of individuals. This study aims to evaluate the perceptions and attitudes of dentistry students toward AI. Methods This cross-sectional study was conducted on dental students at Ordu University Faculty of Dentistry, involving a sample of 83 students. The study utilized the Big Five 50 Test to evaluate personality traits and a 5-point Likert scale to gather data on 20 statements regarding AI in dentistry. Data were analyzed using IBM SPSS Statistics software, and a chi-square test was employed to assess the relationship between the personality traits of dental students and their attitudes towards artificial intelligence, as well as the relationship between the gender of dental students and their attitudes towards artificial intelligence. Statistical significance was set at P < 0.05. Results The study involved 83 participants, with 29 male and 54 female participants. The most common personality traits were Openness and Agreeableness, whereas the least common was Extraversion. Participants found AI useful and believed it could help dentists evaluate radiographs. However, the least agreed statement was that they would trust AI more than a dentist in evaluating radiograph results. A statistically significant difference was found between personal traits of dental students and in expressions comparing dentists and AI. Males were more familiar with AI than females. Conclusion This study found that attitudes towards AI in dentistry vary based on personality traits. Developing educational strategies tailored to these traits can help foster more positive attitudes and improve AI integration into dental practice.
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spelling doaj-art-8a9dae5e60e54e6585e4fbb0cad21d5f2025-01-12T12:28:16ZengBMCBMC Medical Education1472-69202025-01-012511810.1186/s12909-024-06630-5The relationships of personality traits on perceptions and attitudes of dentistry students towards AIFurkan Ozbey0Yasin Yasa1Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Ordu UniversityDepartment of Dentomaxillofacial Radiology, Faculty of Dentistry, Ordu UniversityAbstract Introduction Artificial intelligence (AI) has gained significant attention in dentistry due to its potential to revolutionize practice and improve patient outcomes. However, dentists’ views and attitudes toward technology can affect the application of AI. This perception and attitude can be affected by the personality traits of individuals. This study aims to evaluate the perceptions and attitudes of dentistry students toward AI. Methods This cross-sectional study was conducted on dental students at Ordu University Faculty of Dentistry, involving a sample of 83 students. The study utilized the Big Five 50 Test to evaluate personality traits and a 5-point Likert scale to gather data on 20 statements regarding AI in dentistry. Data were analyzed using IBM SPSS Statistics software, and a chi-square test was employed to assess the relationship between the personality traits of dental students and their attitudes towards artificial intelligence, as well as the relationship between the gender of dental students and their attitudes towards artificial intelligence. Statistical significance was set at P < 0.05. Results The study involved 83 participants, with 29 male and 54 female participants. The most common personality traits were Openness and Agreeableness, whereas the least common was Extraversion. Participants found AI useful and believed it could help dentists evaluate radiographs. However, the least agreed statement was that they would trust AI more than a dentist in evaluating radiograph results. A statistically significant difference was found between personal traits of dental students and in expressions comparing dentists and AI. Males were more familiar with AI than females. Conclusion This study found that attitudes towards AI in dentistry vary based on personality traits. Developing educational strategies tailored to these traits can help foster more positive attitudes and improve AI integration into dental practice.https://doi.org/10.1186/s12909-024-06630-5Artificial IntelligenceDental StudentsPersonal Traits
spellingShingle Furkan Ozbey
Yasin Yasa
The relationships of personality traits on perceptions and attitudes of dentistry students towards AI
BMC Medical Education
Artificial Intelligence
Dental Students
Personal Traits
title The relationships of personality traits on perceptions and attitudes of dentistry students towards AI
title_full The relationships of personality traits on perceptions and attitudes of dentistry students towards AI
title_fullStr The relationships of personality traits on perceptions and attitudes of dentistry students towards AI
title_full_unstemmed The relationships of personality traits on perceptions and attitudes of dentistry students towards AI
title_short The relationships of personality traits on perceptions and attitudes of dentistry students towards AI
title_sort relationships of personality traits on perceptions and attitudes of dentistry students towards ai
topic Artificial Intelligence
Dental Students
Personal Traits
url https://doi.org/10.1186/s12909-024-06630-5
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