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Background <p>Artificial intelligence (AI) is reshaping healthcare across various specialties. Thus, understanding how undergraduate students in healthcare specialties perceive and understand AI is important for evaluating their preparedness and digital competence as they enter clinical practice. This study aims to evaluate Jordanian undergraduate healthcare students’ knowledge, perceptions, and attitudes toward artificial intelligence in healthcare and examine their associations with demographic and educational characteristics.</p> Methods <p>A cross-sectional, multi-center study was conducted between July and October 2025, using an online close-ended questionnaire distributed to undergraduate students from five colleges representing dentistry, nursing, medicine, and nutritional sciences across Jordan. The study assessed basic AI knowledge and prior exposure, measurement of perceptions of AI, and evaluation of attitudes toward AI in healthcare. Descriptive statistics were calculated and Analysis of Variance (ANOVA) assessed variation by demographic factors. Data analyses were completed through SPSS version 25.</p> Results <p>A total of 474 students participated. Overall, students expressed interest in AI and moderate confidence in its use, but the majority still lacks the organized conceptual knowledge, training, and practical awareness of AI in healthcare. The mean perception score was 46.25 ± 11.96, reflecting moderate confidence in AI’s ability to perform selected clinical and administrative tasks. Attitudes toward the impact of AI on healthcare professions were mixed (34.95 ± 26.55), while attitudes toward the future role and benefits of AI were generally positive (74.76 ± 25.46). Age, gender, university, and discipline were significantly associated with one or more of the investigated aspects (knowledge, attitudes, or perceptions).</p> Conclusion <p>Healthcare students in Jordan expressed clear interest in AI and were generally positive about AI’s future role, however, the majority lacked conceptual knowledge, structured training and was uncertain about its limitations and risks. This highlights the need to integrate AI competencies into undergraduate education, and establish clear ethical and regulatory guidance.</p>

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Knowledge, perception, and attitude of healthcare students towards artificial intelligence: a multi-center cross sectional study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月28日

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  • Luma Ghazi Alzamel,
  • Layla Hassouneh,
  • Samar Thabet Jallad

摘要

Background

Artificial intelligence (AI) is reshaping healthcare across various specialties. Thus, understanding how undergraduate students in healthcare specialties perceive and understand AI is important for evaluating their preparedness and digital competence as they enter clinical practice. This study aims to evaluate Jordanian undergraduate healthcare students’ knowledge, perceptions, and attitudes toward artificial intelligence in healthcare and examine their associations with demographic and educational characteristics.

Methods

A cross-sectional, multi-center study was conducted between July and October 2025, using an online close-ended questionnaire distributed to undergraduate students from five colleges representing dentistry, nursing, medicine, and nutritional sciences across Jordan. The study assessed basic AI knowledge and prior exposure, measurement of perceptions of AI, and evaluation of attitudes toward AI in healthcare. Descriptive statistics were calculated and Analysis of Variance (ANOVA) assessed variation by demographic factors. Data analyses were completed through SPSS version 25.

Results

A total of 474 students participated. Overall, students expressed interest in AI and moderate confidence in its use, but the majority still lacks the organized conceptual knowledge, training, and practical awareness of AI in healthcare. The mean perception score was 46.25 ± 11.96, reflecting moderate confidence in AI’s ability to perform selected clinical and administrative tasks. Attitudes toward the impact of AI on healthcare professions were mixed (34.95 ± 26.55), while attitudes toward the future role and benefits of AI were generally positive (74.76 ± 25.46). Age, gender, university, and discipline were significantly associated with one or more of the investigated aspects (knowledge, attitudes, or perceptions).

Conclusion

Healthcare students in Jordan expressed clear interest in AI and were generally positive about AI’s future role, however, the majority lacked conceptual knowledge, structured training and was uncertain about its limitations and risks. This highlights the need to integrate AI competencies into undergraduate education, and establish clear ethical and regulatory guidance.