Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey

Abstract

Background: Artificial intelligence (AI) needs to be accepted and understood by physicians and medical students, but few have systematically assessed their attitudes. We investigated clinical AI acceptance among physicians and medical students around the world to provide implementation guidance.

Materials and methods: We conducted a two-stage study, involving a foundational systematic review of physician and medical student acceptance of clinical AI. This enabled us to design a suitable web-based questionnaire which was then distributed among practitioners and trainees around the world.

Results: Sixty studies were included in this systematic review, and 758 respondents from 39 countries completed the online questionnaire. Five (62.50%) of eight studies reported 65% or higher awareness regarding the application of clinical AI. Although, only 10-30% had actually used AI and 26 (74.28%) of 35 studies suggested there was a lack of AI knowledge. Our questionnaire uncovered 38% awareness rate and 20% utility rate of clinical AI, although 53% lacked basic knowledge of clinical AI. Forty-five studies mentioned attitudes toward clinical AI, and over 60% from 38 (84.44%) studies were positive about AI, although they were also concerned about the potential for unpredictable, incorrect results. Seventy-seven percent were optimistic about the prospect of clinical AI. The support rate for the statement that AI could replace physicians ranged from 6 to 78% across 40 studies which mentioned this topic. Five studies recommended that efforts should be made to increase collaboration. Our questionnaire showed 68% disagreed that AI would become a surrogate physician, but believed it should assist in clinical decision-making. Participants with different identities, experience and from different countries hold similar but subtly different attitudes.

Conclusion: Most physicians and medical students appear aware of the increasing application of clinical AI, but lack practical experience and related knowledge. Overall, participants have positive but reserved attitudes about AI. In spite of the mixed opinions around clinical AI becoming a surrogate physician, there was a consensus that collaborations between the two should be strengthened. Further education should be conducted to alleviate anxieties associated with change and adopting new technologies.

Keywords: acceptance; artificial intelligence (AI); attitude; medical students; physicians.

FIGURE 1

PRISMA (Preferred reporting items for systematic reviews and meta-analysis) systematic review flow diagram. Displayed is the PRISMA flow of each article selection process.

FIGURE 2

Geographic distribution of participants in the systematic review and the survey. The blue indicates the number of participants of studies included in the systematic review. The darker the color, the more participants. The orange dots indicate the number of participants in our questionnaire survey. The larger the dots, the more participants. Studies without providing specific locations are not shown in the figure. Please see Table 1 for detailed number and locations of participants.

FIGURE 3

Respondent perspectives toward clinical artificial intelligence (AI). 13 statements were set to assess respondent perspectives toward clinical AI from three dimensions. Statement 1 to 4 assessed respondent awareness and knowledge of clinical AI. Statement 5 to 9 assessed attitude and acceptability of clinical AI. Statement 10 to 13 assessed respondent perception of the relationship between physicians and clinical AI.

FIGURE 4

Factors related to use willingness, perceived relationship between physicians and artificial intelligence (AI), and challenges faced by clinical artificial intelligence (AI). (A) Factors associated with willingness to use clinical AI. F1: Accuracy; F2: Efficiency; F3: Ease of use; F4: Widely adopted; F5: Cost-effectiveness; F6: Interpretability; F7: Privacy protection capability. (B) Perceived relationship between physicians and clinical AI. A: Physicians don’t need to use clinical AI; B: Physicians lead the diagnosis and treatment process while clinical AI only plays an auxiliary role; C: Clinical AI completes the diagnosis and treatment process independently under the supervision and optimization of physicians; D: Clinical AI completely replaces physicians for diagnosis and treatment. (C) Challenges to be overcome in the development and implementation of clinical AI. C1: Inadequate algorithms and computational power of clinical AI; C2: Lack of high-quality data for clinical AI training; C3: Lack of inter-disciplinary talents with both medical and AI knowledge; C4: Lack of regulatory standards; C5: Difficulties in integrating clinical AI with existing medical process; C6: Insufficient understanding and acceptance of clinical AI among physicians and medical students.

FIGURE 5

Subgroup analysis of responses to 13 statements. (A) By clinical artificial intelligence (AI) use experience; (B) By identity; (C) By country specific income levels. Mann–Whitney U test, *p < 0.05, **p < 0.01, ***p < 0.001.