Exploring Medical Doctors’ Confidence in Artificial Intelligence: The Role of Specialty, Experience, and Perceived Job Security

<b>Background:</b> Artificial intelligence (AI) is increasingly integrated into healthcare, offering transformative potential across diagnostics, treatment, and clinical decision-making. As its adoption grows, understanding how medical doctors perceive and respond to AI, particularly in relation to their specialty, experience, and job security, is critical for effective implementation and acceptance. This study investigates the confidence of medical doctors in AI technologies and their role in healthcare, focusing on the impact of specialty, experience, and perceived job security. <b>Method:</b> A cross-sectional survey was conducted among 187 medical doctors across various specialties in Riyadh, Saudi Arabia, with a final sample of 176 participants. The survey assessed awareness, confidence, and concerns regarding AI integration into clinical practice. The survey was conducted across multiple healthcare hospitals in Riyadh, Saudi Arabia. Hospitals from both public and private sectors were included to ensure a diverse sample of healthcare professionals from different organizational structures. <b>Results:</b> A statistically significant association was found between specialty and confidence level (χ<sup>2</sup> = 14.5, <i>p</i> = 0.001). Among specialists, the majority (80%) reported high confidence in AI use compared to 45% of general practitioners and 38% of surgeons. Conversely, moderate confidence was most common among surgeons (46%), followed by general practitioners (35%) and specialists (13%). Additionally, participants with 11-20 years of experience reported the highest confidence, whereas those aged 55+ years showed the lowest perceived impact of AI on patient outcomes. Multivariate regression analysis identified specialty as the strongest predictor of AI confidence, with specialists being four times more likely to express high confidence in AI use (β = 0.89, <i>p</i> = 0.001) compared to general practitioners. Job displacement concerns negatively influenced confidence in AI, while age and years of experience had less impactful effects. <b>Conclusions:</b> The study concludes that addressing barriers to AI adoption will be crucial for enhancing its integration into healthcare and improving patient care. These findings underscore the importance of specialty-specific training and highlight the need for targeted educational programs, particularly for lower confidence groups such as general practitioners and surgeons. Lower confidence levels in these groups may result in a hesitant or incorrect use of AI tools, potentially compromising patient safety. Therefore, equipping all healthcare professionals with the necessary knowledge and confidence is essential for the safe and effective use of AI in clinical practice.

Authors

Institutions

Publication Details

Journal
Healthcare
Published
2025-09-22
DOI
https://doi.org/10.3390/healthcare13182377
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring Medical Doctors’ Confidence in Artificial Intelligence: The Role of Specialty, Experience, and Perceived Job Security

Fahad Abdulaziz Alrashed, Shimaa A. Mahmoud, Muneera Mohammed Almurdi, Tauseef Ahmad et al.
1 citations
Healthcare
Artificial Intelligence in Healthcare and Education
0.65
article

Exploring Medical Doctors’ Confidence in Artificial Intelligence: The Role of Specialty, Experience, and Perceived Job Security

Fahad Abdulaziz Alrashed, Shimaa A. Mahmoud, Muneera Mohammed Almurdi, Tauseef Ahmad, Ahmed Othman Alsabih, Hamza Mohammad Abdulghani
article en
1 citations

Abstract

<b>Background:</b> Artificial intelligence (AI) is increasingly integrated into healthcare, offering transformative potential across diagnostics, treatment, and clinical decision-making. As its adoption grows, understanding how medical doctors perceive and respond to AI, particularly in relation to their specialty, experience, and job security, is critical for effective implementation and acceptance. This study investigates the confidence of medical doctors in AI technologies and their role in healthcare, focusing on the impact of specialty, experience, and perceived job security. <b>Method:</b> A cross-sectional survey was conducted among 187 medical doctors across various specialties in Riyadh, Saudi Arabia, with a final sample of 176 participants. The survey assessed awareness, confidence, and concerns regarding AI integration into clinical practice. The survey was conducted across multiple healthcare hospitals in Riyadh, Saudi Arabia. Hospitals from both public and private sectors were included to ensure a diverse sample of healthcare professionals from different organizational structures. <b>Results:</b> A statistically significant association was found between specialty and confidence level (χ<sup>2</sup> = 14.5, <i>p</i> = 0.001). Among specialists, the majority (80%) reported high confidence in AI use compared to 45% of general practitioners and 38% of surgeons. Conversely, moderate confidence was most common among surgeons (46%), followed by general practitioners (35%) and specialists (13%). Additionally, participants with 11-20 years of experience reported the highest confidence, whereas those aged 55+ years showed the lowest perceived impact of AI on patient outcomes. Multivariate regression analysis identified specialty as the strongest predictor of AI confidence, with specialists being four times more likely to express high confidence in AI use (β = 0.89, <i>p</i> = 0.001) compared to general practitioners. Job displacement concerns negatively influenced confidence in AI, while age and years of experience had less impactful effects. <b>Conclusions:</b> The study concludes that addressing barriers to AI adoption will be crucial for enhancing its integration into healthcare and improving patient care. These findings underscore the importance of specialty-specific training and highlight the need for targeted educational programs, particularly for lower confidence groups such as general practitioners and surgeons. Lower confidence levels in these groups may result in a hesitant or incorrect use of AI tools, potentially compromising patient safety. Therefore, equipping all healthcare professionals with the necessary knowledge and confidence is essential for the safe and effective use of AI in clinical practice.

HealthcareVol. 13(18)
King Saud Medical City (SA), King Saud University (SA)
Openalex Percentile: Top 21%
Artificial Intelligence in Healthcare and Education
0.65
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.