JMIR Publications

ABSTRACT

Background:

Artificial Intelligence (AI) has been developing for decades, but in recent years its use in the field of healthcare has experienced an exponential increase. Today, there are few who doubt that these tools have come to transform clinical practice. Therefore, it is important to know how the population perceives its implementation in order to be able to propose strategies for acceptance and implementation, and to improve or prevent problems arising from future application.

Objective:

To describe the population's perception and knowledge of the use of AI, as a health support tool, and its application to radiology through a validated survey, in order to develop strategies aimed at increasing acceptance of AI use and reducing possible resistance to change.

Methods:

Cross-sectional observational study, through an anonymous and voluntary validated survey, aimed at the entire population of Catalonia aged 18 years or older. The survey addresses four dimensions defined to describe users' perception of the use of AI in radiology: (1) distrust and accountability, (2) personal interaction, (3) efficiency and (4) being informed, all with questions in Likert format. Results closer to 5 refer to a negative perception of the use of AI, while results closer to 1 express a positive perception.

Results:

A total of 379 users responded to the survey, with an average age of 43.9 years (SD = 17.52) and 59.8% female. 89.8% of respondents indicated that they understood the concept of AI. Of the four dimensions analysed, distrust and accountability obtained a mean score of 3.37 (SD = 0.53), personal interaction a mean score of 4.37 (SD = 0.60), efficiency a mean score of 3.06 (SD = 0.73) and being informed a mean score of 3.67 (SD = 0.57).

Conclusions:

The results of the study show that the majority of the population reported being familiar with the concept of AI, with varying degrees of acceptance of its implementation in the field of radiology. It is clear that the most conflictive dimension is personal interaction, whereas efficiency is where there is the greatest acceptance, being the dimension in which there are the best expectations for the implementation of AI in radiology.