Attitudes and readiness to adopt artificial intelligence among healthcare practitioners in Pakistan's resource-limited settings

Abstract

Background: Artificial Intelligence (AI) can empower clinicians to make data-driven decisions, treatments and streamline administrative tasks. However, it is vital to understand their perception towards AI for seamless implementation in practice. Therefore, the study aimed to assess the attitude, receptivity and readiness of medical and dental practitioners towards the use of AI in clinical practice.

Methods: A cross-sectional study employing non-probability convenience sampling was conducted from April to August 2024. A questionnaire was distributed among practitioners working in public and private sector hospitals. The questionnaire included a validated tool, the General Attitude towards Artificial Intelligence Scale (GAAIS), comprising of total 20 items with two subscales; positive and negative attitudes. They were rated on a 5-point Likert scale, ranging from strongly disagree (1) to strongly agree (5). The items of negative attitudes were reverse coded. Self-formulated questions to assess the readiness of medical and dental practitioners to incorporate AI in practice were also included. Data was analyzed using IBM SPSS v.25. Results were reported as frequencies and percentages. Statistical analysis was performed using Mann-Whitney U, and Chi-squared test for continuous and categorical variables. The association between two continuous variables was assessed through Spearman's correlation.

Results: A total of 451 responses were analyzed. The mean score for positive attitudes toward AI was 3.6 ± 0.54, whereas for negative attitudes it was estimated to be 2.8 ± 0.71. Approximately 187 (41.5%) respondents believed AI was superior to humans in routine jobs. About 190 (42.1%) respondents agreed that AI can make errors. Most respondents 334 (74.1%) were aware of AI applications in healthcare, and 329 (72.9%) reported familiarity with AI technologies. However, only 153 (33.9%) felt confident in operating AI systems. While 282 (62.5%) expressed eagerness to incorporate AI into diagnosis and treatment planning, a significant difference was observed between groups, with dental practitioners showing greater willingness (p = 0.004). Additionally, dentists exhibited higher confidence in using AI compared to medical practitioners (p = 0.047).

Conclusions: The findings suggest that most practitioners had a positive attitude towards AI and were receptive towards incorporating the technology as a beneficial tool in their practice. Ethical guidelines and extensive training can mitigate negative perceptions associated with the use of AI technology. It is also imperative that resources should be provided, specially to public-sector healthcare systems as they serve underprivileged communities. This will help practitioners gain familiarity with AI technology and will enable them to develop proficiency in AI use.

Keywords: Artificial intelligence; Attitudes; Dentists; General practitioner; Specialists.