Patients' attitudes toward artificial intelligence in dentistry and their trust in dentists

被引:0
作者
Bahadir, Hasibe Sevilay [1 ]
Keskin, Neslihan Busra [2 ]
Cakmak, Emine Sebnem Kursun [3 ]
Gunec, Gurkan [4 ]
Cesur Aydin, Kader [5 ]
Peker, Fatih [3 ]
机构
[1] Ankara Yildirim Beyazit Univ, Fac Dent, Dept Restorat Dent, Ankara, Turkiye
[2] Ankara Yildirim Beyazit Univ, Fac Dent, Dept Endodont, Ankara, Turkiye
[3] Ankara Yildirim Beyazit Univ, Fac Dent, Dept Dentomaxillofacial Radiol, Ankara, Turkiye
[4] Hlth Sci Univ, Hamidiye Fac Dent, Dept Endodont, Istanbul, Turkiye
[5] Istanbul Medipol Univ, Fac Dent, Dept Dentomaxillofacial Radiol, Istanbul, Turkiye
关键词
Artificial intelligence; Communication; Diagnosis; Dentist trust; Machine learning; Patients;
D O I
10.1007/s11282-024-00775-1
中图分类号
R78 [口腔科学];
学科分类号
1003 ;
摘要
Objectives This study intended to evaluate patients' attitudes toward the use of AI in dental radiographic detection of occlusal caries and the impact of AI-based diagnosis on their trust in dentists. Methods A total of 272 completed questionnaires were included in this study. In the first part of the study, approval was obtained from the patients, and data were collected about their socio-demographic characteristics. In the second part the 11-item Dentist Trust Scale was applied. In the third and fourth parts, there were questions about two clinical scenarios, the patients' knowledge of attitudes toward AI, and how the AI-based diagnosis had affected their trust. Evaluation was performed using a Likert-type scale. Data were analyzed with the Chi-square, one-way ANOVA, and ordinal logistic regression tests (p < 0.05). Results The patients believed that "AI is useful" (3.86 +/- 1.03) and were not afraid of the use of AI in dentistry (2.40 +/- 1.05). Educational level was considerably related to the patients' attitudes to the use of AI for dental diagnostics (p < 0.05). The patients stated that "dentists are extremely thorough and careful" (4.39 +/- 0.77). Conclusions The patients displayed a positive attitude to AI-based diagnosis in the dental field and appear to exhibit trust in dentists. The use of Al in routine clinical practice can provide important benefit to physicians as a clinical decision support system in dentistry and understanding patients' attitudes may allow dentists to shape AI-supported dentistry in the future.
引用
收藏
页码:52 / 59
页数:8
相关论文
共 23 条
  • [1] Do people trust dentists? Development of the Dentist Trust Scale
    Armfield, J. M.
    Ketting, M.
    Chrisopoulos, S.
    Baker, S. R.
    [J]. AUSTRALIAN DENTAL JOURNAL, 2017, 62 (03) : 355 - 362
  • [2] Patients' perspectives on the use of artificial intelligence in dentistry: a regional survey
    Ayad, Nasim
    Schwendicke, Falk
    Krois, Joachim
    van den Bosch, Stefanie
    Berge, Stefaan
    Bohner, Lauren
    Hanisch, Marcel
    Vinayahalingam, Shankeeth
    [J]. HEAD & FACE MEDICINE, 2023, 19 (01)
  • [3] Deep-learning approach for caries detection and segmentation on dental bitewing radiographs
    Bayrakdar, Ibrahim Sevki
    Orhan, Kaan
    Akarsu, Serdar
    Celik, Ozer
    Atasoy, Samet
    Pekince, Adem
    Yasa, Yasin
    Bilgir, Elif
    Saglam, Hande
    Aslan, Ahmet Faruk
    Odabas, Alper
    [J]. ORAL RADIOLOGY, 2022, 38 (04) : 468 - 479
  • [4] Artificial Intelligence in Medicine: A Multinational Multi-Center Survey on the Medical and Dental Students' Perception
    Bisdas, Sotirios
    Topriceanu, Constantin-Cristian
    Zakrzewska, Zosia
    Irimia, Alexandra-Valentina
    Shakallis, Loizos
    Subhash, Jithu
    Casapu, Maria-Madalina
    Leon-Rojas, Jose
    Pinto dos Santos, Daniel
    Andrews, Dilys Miriam
    Zeicu, Claudia
    Bouhuwaish, Ahmad Mohammad
    Lestari, Avinindita Nura
    Abu-Ismail, Lua'i
    Sadiq, Arsal Subbah
    Khamees, Almu'atasim
    Mohammed, Khaled M. G.
    Williams, Estelle
    Omran, Aya Ibrahim
    Ismail, Dima Y. Abu
    Ebrahim, Esraa Hasan
    [J]. FRONTIERS IN PUBLIC HEALTH, 2021, 9
  • [5] Perceptions of Artificial Intelligence Among Healthcare Staff: A Qualitative Survey Study
    Castagno, Simone
    Khalifa, Mohamed
    [J]. FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2020, 3
  • [6] Applications of deep learning in dentistry
    Corbella, Stefano
    Srinivas, Shanmukh
    Cabitza, Federico
    [J]. ORAL SURGERY ORAL MEDICINE ORAL PATHOLOGY ORAL RADIOLOGY, 2021, 132 (02): : 225 - 238
  • [7] Factors Associated with Dental Fear and Anxiety in Children Aged 7 to 9 Years
    Dahlander, Andreas
    Soares, Fernanda
    Grindefjord, Margaret
    Dahllof, Goran
    [J]. DENTISTRY JOURNAL, 2019, 7 (03)
  • [8] A Novel Deep Learning-Based Approach for Segmentation of Different Type Caries Lesions on Panoramic Radiographs
    Dayi, Burak
    Uzen, Huseyin
    Cicek, Ipek Balikci
    Duman, Suayip Burak
    [J]. DIAGNOSTICS, 2023, 13 (02)
  • [9] A Survey on the Use of Artificial Intelligence by Clinicians in Dentistry and Oral and Maxillofacial Surgery
    Eschert, Tim
    Schwendicke, Falk
    Krois, Joachim
    Bohner, Lauren
    Vinayahalingam, Shankeeth
    Hanisch, Marcel
    [J]. MEDICINA-LITHUANIA, 2022, 58 (08):
  • [10] Ex vivo evaluation of new 2D and 3D dental radiographic technology for detecting caries
    Gaalaas, Laurence
    Tyndall, Donald
    Mol, Andre
    Everett, Eric T.
    Bangdiwala, Ananta
    [J]. DENTOMAXILLOFACIAL RADIOLOGY, 2016, 45 (03)