Dataset Information

Exploring knowledge, attitudes, and practices towards artificial intelligence among health professions' students in Jordan.

ABSTRACT:

Introduction

The integration of Artificial Intelligence (AI) in medical education and practice is a significant development. This study examined the Knowledge, Attitudes, and Practices (KAP) of health professions' students in Jordan concerning AI, providing insights into their preparedness and perceptions.

Methods

An online questionnaire was distributed to 483 Jordanian health professions' students via social media. Demographic data, AI-related KAP, and barriers were collected. Quantile regression models analyzed associations between variables and KAP scores.

Results

Moderate AI knowledge was observed among participants, with specific understanding of data requirements and barriers. Attitudes varied, combining skepticism about AI replacing human teachers with recognition of its value. While AI tools were used for specific tasks, broader integration in medical education and practice was limited. Barriers included lack of knowledge, access, time constraints, and curriculum gaps.

Conclusions

This study highlights the need to enhance medical education with AI topics and address barriers. Students need to be better prepared for AI integration, in order to enable medical education to harness AI's potential for improved patient care and training.

SUBMITTER: Al-Qerem W

PROVIDER: S-EPMC10722664 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

Exploring knowledge, attitudes, and practices towards artificial intelligence among health professions' students in Jordan.

Al-Qerem Walid W Eberhardt Judith J Jarab Anan A Al Bawab Abdel Qader AQ Hammad Alaa A Alasmari Fawaz F Alazab Badi'ah B Husein Daoud Abu DA Alazab Jumana J Al-Beool Saed S

BMC medical informatics and decision making 20231214 1

<h4>Introduction</h4>The integration of Artificial Intelligence (AI) in medical education and practice is a significant development. This study examined the Knowledge, Attitudes, and Practices (KAP) of health professions' students in Jordan concerning AI, providing insights into their preparedness and perceptions.<h4>Methods</h4>An online questionnaire was distributed to 483 Jordanian health professions' students via social media. Demographic data, AI-related KAP, and barriers were collected. Qu ...[more]

PMID: 38098095

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Project description:IntroductionSurveys conducted internationally have found widespread interest in artificial intelligence (AI) amongst medical students. No similar surveys have been conducted in Western Australia (WA) and it is not known how medical students in WA feel about the use of AI in healthcare or their understanding of AI. We aim to assess WA medical students' attitudes towards AI in general, AI in healthcare, and the inclusion of AI education in the medical curriculum.MethodsA digital survey instrument was developed based on a review of available literature and consultation with subject matter experts. The survey was piloted with a group of medical students and refined based on their feedback. We then sent this anonymous digital survey to all medical students in WA (approximately 1539 students). Responses were open from the 7th of September 2021 to the 7th of November 2021. Students' categorical responses were qualitatively analysed, and free text comments from the survey were qualitatively analysed using open coding techniques.ResultsOverall, 134 students answered one or more questions (8.9% response rate). The majority of students (82.0%) were 20-29 years old, studying medicine as a postgraduate degree (77.6%), and had started clinical rotations (62.7%). Students were interested in AI (82.6%), self-reported having a basic understanding of AI (84.8%), but few agreed that they had an understanding of the basic computational principles of AI (33.3%) or the limitations of AI (46.2%). Most students (87.5%) had not received teaching in AI. The majority of students (58.6%) agreed that AI should be part of medical training and most (72.7%) wanted more teaching focusing on AI in medicine. Medical students appeared optimistic regarding the role of AI in medicine, with most (74.4%) agreeing with the statement that AI will improve medicine in general. The majority (56.6%) of medical students were not concerned about the impact of AI on their job security as a doctor. Students selected radiology (72.6%), pathology (58.2%), and medical administration (44.8%) as the specialties most likely to be impacted by AI, and psychiatry (61.2%), palliative care (48.5%), and obstetrics and gynaecology (41.0%) as the specialties least likely to be impacted by AI. Qualitative analysis of free text comments identified the use of AI as a tool, and that doctors will not be replaced as common themes.ConclusionMedical students in WA appear to be interested in AI. However, they have not received education about AI and do not feel they understand its basic computational principles or limitations. AI appears to be a current deficit in the medical curriculum in WA, and most students surveyed were supportive of its introduction. These results are consistent with previous surveys conducted internationally.

Project description:BackgroundIntegrating medical students in research at an early stage of their program is a crucial step to enhance the ability of future physicians to employ critical thinking and problem-solving processes, which in turn improves patients' health outcomes.MethodsA cross-sectional questionnaire-based survey was administered to medical school students at Al-Balqa Applied University. This study aims to analyze the attitudes, practices, and barriers faced by medical students in regard to engaging in medical research.ResultsA total of 333 students participated in the study with a mean age of 21.2 ± 1.5 years. A total of 60.1% were females. Female students had significantly higher knowledge scores (µ = 3.97, SD ± 1.81, P = 0.009) than males (µ = 3.44, SD ± 1.69). As students progress to higher academic years of their clinical program, their knowledge in research significantly increases in comparison to their knowledge in basic medical years (P < 0.001). Student age and academic year significantly correlated with the knowledge scores; each additional year of study increased the knowledge score by 0.25 (β = 0.25, P < 0.001, R2 = 0.63). The percentage of students who correctly answered each question on the knowledge scale was 37.5% (SD ± 12.5%). The most reported barriers to research participation were insufficient training in medical research, lack of sufficient research opportunities, and lack of stimulation and support from faculty.ConclusionsMedical students demonstrated a positive attitude toward research starting from their second year of study, despite having limited knowledge on the topic. They identified barriers that could be utilized to promote greater involvement of students in research. The implications for clinical practice suggest that policymakers and educators should consider the outcomes of this study and implement improvements in medical education, specifically by encouraging the early participation of students in the research process.

Dataset Information

Exploring knowledge, attitudes, and practices towards artificial intelligence among health professions' students in Jordan.

Introduction

Methods

Results

Conclusions

Publications

Exploring knowledge, attitudes, and practices towards artificial intelligence among health professions' students in Jordan.

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