Medical Trainee Survey on AI in Healthcare, UAE 2026

154 survey responses and 16 qualitative interviews from medical and dental trainees in the United Arab Emirates explore their knowledge, attitudes, and educational needs regarding AI in healthcare. The explanatory sequential mixed-methods study was authored by Asma F. Syeda and last updated in June 2026. Findings highlight moderate AI awareness, limited formal training, and strong support for structured, ethically grounded AI education.

Use Cases

• Analyze perceived value and normalization of AI in clinical workflows based on qualitative interview themes.
• Assess educational needs and readiness for AI integration based on survey responses from 154 trainees.
• Study concerns related to trust, human oversight, and ethical governance of AI in medicine.
• Identify system-level preconditions for responsible AI adoption in healthcare education.

Strengths

• Includes mixed-methods data from 154 survey respondents and 16 in-depth interviews, allowing for triangulation.
• Focuses on a specific, understudied population of medical and dental trainees in the United Arab Emirates.
• Released under a permissive CC-BY-4.0 license, enabling reuse and redistribution.

Limitations

• The 53.9 KB size suggests the PDF contains a summary report, not the underlying raw survey or interview data.
• Row count and column-level documentation for any underlying quantitative data are unknown.
• Geographic scope is limited to the UAE, which may limit generalizability to other regions.

Provenance

Source

figshare, authored by Asma F. Syeda.

Collection Method

Explanatory sequential mixed-methods design using an online survey and semi-structured interviews.

Freshness

Last updated 2026-06-02 04:21:27

Geography

United Arab Emirates (UAE)