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Accepted for/Published in: JMIR Human Factors

Date Submitted: Sep 26, 2023
Date Accepted: Jun 22, 2024

The final, peer-reviewed published version of this preprint can be found here:

Patients’ Attitudes Toward the Use of Artificial Intelligence as a Diagnostic Tool in Radiology in Saudi Arabia: Cross-Sectional Study

Baghdadi LR, Mobeirek AA, Alhudaithi DR, Albenmousa FA, Alhadlaq LS, Alaql MS, Alhamlan SA

Patients’ Attitudes Toward the Use of Artificial Intelligence as a Diagnostic Tool in Radiology in Saudi Arabia: Cross-Sectional Study

JMIR Hum Factors 2024;11:e53108

DOI: 10.2196/53108

PMID: 39110973

PMCID: 11339559

Patients’ Attitudes toward the Use of Artificial Intelligence as a Diagnostic Tool in Radiology in Saudi Arabia: A Cross-sectional Study

  • Leena R. Baghdadi; 
  • Arwa A. Mobeirek; 
  • Dania R. Alhudaithi; 
  • Fatimah A. Albenmousa; 
  • Leen S. Alhadlaq; 
  • Maisa S. Alaql; 
  • Sarah A. Alhamlan

ABSTRACT

Background:

Artificial intelligence (AI) is widely used in various medical fields, including diagnostic radiology as a tool for greater efficiency, precision, and accuracy. The number of scans to be evaluated and diagnosed has increased. Thus, the need for trained radiologists in certain specialties is increasing. The use of AI as a radiological diagnostic tool decreases any delays in diagnosis that could affect patients’ prognosis and treatment outcomes. The literature shows conflicting results regarding patients’ attitudes to AI as a diagnostic tool. To the best of our knowledge, no similar study has been conducted in Saudi Arabia.

Objective:

The objectives of this study were to examine patients’ attitudes toward the use of AI as a tool in diagnostic radiology at King Khalid University Hospital, Saudi Arabia and assess associations, if any, between patients’ attitudes and selected sociodemographic factors.

Methods:

This analytical cross-sectional study was conducted in a tertiary care hospital. A convenience sampling technique was used to recruit participants. Data were collected from patients scheduled for radiological imaging through a validated self-administered questionnaire. The main outcome was to measure patients’ attitudes to the use of AI in radiology by calculating mean scores of five factors, distrust and accountability, procedural knowledge, personal interaction and communication, efficiency, and methods of providing information to patients. Data were analyzed using SPSS.

Results:

Three hundred and eighty-two participants (71.5% women, 28.5% men) completed the surveys and were included in the analysis. The mean age of the respondents was 39.51±13.26 years. Participants’ responses were in favor of physicians for procedural knowledge (factor 2), personal interaction (factor 3), and being informed (factor 5). However, the participants demonstrated a neutral attitude for distrust and accountability (factor 1) and efficiency (factor 4). Significant associations were found between a few factors and marital status, field of specialization, and self-reported health status.

Conclusions:

Patients had mixed views toward AI, which should be a consideration in future policy development and integration. Future research involving multicenter studies in different regions of Saudi Arabia is required.


 Citation

Please cite as:

Baghdadi LR, Mobeirek AA, Alhudaithi DR, Albenmousa FA, Alhadlaq LS, Alaql MS, Alhamlan SA

Patients’ Attitudes Toward the Use of Artificial Intelligence as a Diagnostic Tool in Radiology in Saudi Arabia: Cross-Sectional Study

JMIR Hum Factors 2024;11:e53108

DOI: 10.2196/53108

PMID: 39110973

PMCID: 11339559

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