Assessing artificial intelligence knowledge among Al-Zahraa university students: A cross-sectional study

Introduction

Artificial intelligence (AI) is a powerful and disruptive area of computer science, with the potential to fundamentally transform the practice of medicine and the delivery of healthcare.¹

As future healthcare leaders and physicians, medical students occupy an essential part in the clinical adoption of AI-powered solutions.²

Artificial Intelligence (AI) has a significant impact on both our personal and professional lives. University students must gain a basic knowledge of AI in order to deal with its problems and recognize its benefits.³

Artificial intelligence has gained popularity recently due of its apparent developing application in the field of medicine.⁴

Learning computer programming or other forms of technology is not the only way to get ready for artificial intelligence. A adequate understanding of data science, biostatistics, basic and clinical medicine, and evidence-based medicine should be attained. It is not acceptable for medical students to acquiesce to media and online articles about artificial intelligence (AI) in medicine.⁵

The general media's anxieties that artificial intelligence (AI) would replace radiologists might negatively impact medical students' impressions of radiology as an exciting field of study.⁶

Medical professionals and students need to accept and understand artificial intelligence (AI), but few have invested the time to properly evaluate their points of view.⁷

Artificial intelligence (AI) in medicine had a direct impact on medical care, but it's also becoming more and more linked to a number of ethical concerns. Furthermore, a change in medical education is necessary for successfully educating future practitioners for the ethical issues that come with using AI and AI-based applications like ChatGPT. This is because the usage of AI and these applications is developing.⁸

In the near future, robotics is expected to explode, spreading across all regions of the world and drastically surpassing traditional application sectors. Thus, it's critical to research local perceptions of robots in order to enable efficient worldwide adaptation of robot designs and to enable a more seamless and harmonious introduction of these tools into daily life.⁹

Artificial intelligence (AI) is a rapidly maturing field that has the potential to fundamentally transform medicine. But the rapid growth of AI has not kept up with medical education. The implementation of AI education in undergraduate medical education (UME) has been sluggish despite multiple calls to action.¹⁰

The World Medical Association stresses the addition of AI education into medical schools as artificial intelligence (AI) becomes more and more prevalent in the health care sector, with applications like robotic surgery and image analysis.¹¹

Information related to artificial intelligence (AI) is developing quickly and is present in many facets of peoples' daily lives. The likelihood of effective implementation of artificial intelligence and its worth in the medical sector are increased by medical students' attitude for the use of AI in the field.¹²

Medical students are nevertheless passionate about the current uses of machine learning (AI) in healthcare.¹³

International surveys have revealed that health care students are broadly passionate about artificial intelligence (AI).¹⁴

As technology expands in the twenty-first century, novel approaches for helping students learn artificial intelligence (AI) technologies have been found. Thus, it is vital that university instructors embrace practical learning and assist students develop their hands-on competencies in order to constantly improve the process of acquiring knowledge.¹⁵

Students must understand the significance of artificial intelligence (AI) today in medical practice if they want to implement innovations in medical education.¹⁶

Within the near future, doctors can be anticipated to encounter patients in very distinctive wellbeing care settings compared with the present time. As a result, artificial intelligence will be an essential tool.¹⁷

The fourth industrial revolution's core technology, artificial intelligence (AI), has been widely used in numerous fields and significantly changed human society. Yet, AI has also raised a number of ethical concerns about societal order, private safety, basic rights of humans, and other topics. Governments from different nations and international organizations are trying to create AI laws and ethical standards in order to keep a balance between innovation in technology and AI ethics.¹⁸

Methods

From 5August 2024 to 28November 2024, data from Al-Zahraa University for Women students was obtained through an online questionnaire in a cross-sectional survey study. Students' level of understanding and appreciation of AI, together with the main aspects of AI-related material that needs to be taught in medical schools, were identified based on the quantitative data from the questionnaire. Data was downloaded to an Excel file from Google Forms following it was gathered. The questionnaire's quantitative data was imported and analyzed. Both qualitative and quantitative techniques will be utilized during the data synthesis method; the first type will compute effect estimates for important measures, while the other will concentrate on thematic shifts in policy and socioeconomic effects.

A literature search was performed on PubMed, Scopus and Web of Science pertaining to survey data on AI knowledge. Every group of students, from second year to fourth-year students, had an introductory chat on the purpose and importance of this study to find out whether all the elements are clear before being given the link to the Google form which had the consent and questionnaire.

The questionnaire's items were lifted from a previously validated study (Swed¹Syrian study). Using a pre-validated, semi-structured questionnaire, 419 medical students in Al-Zahraa university for women engaged in a cross-sectional study. To ensure internal validity, it was then examined by a team of medical students, professionals in qualitative research (a health information system specialist from the Iraqi Ministry of Health), an AI specialist (two assistant professors from the Karbala faculty of medicine), and a clinician-scientist with a background in AI research.

Most Al-Zahraa Medical School students got an anonymous online survey. Only medical students were specifically selected from the study institution because the goal of the study was to evaluate the preparedness of medical students for artificial intelligence (AI); students from additional programs, such as faculty of education, were left out in the study. Two components made up the questionnaire: (1) demographic information, (2) AI perceptions of the students. Since the participants had not begun their studies by the time the poll took place, first-year students had been excluded from the study. All medical students in grades 2, 3, and 4 were sent the link to the questionnaire via the university email system in attempt to gather data.

Results

The total number of participants was 498 participants; however, 89 students refused to answer the questions, which reduced the sample size to 409. As a result, the response rate is 82.1%.

Participation in this research is entirely voluntary. The mean age of the students was 21.44 ± year and most of the students (84%) were between 18 and 22 years of age (Figure 1).

Figure 1. The age distribution of students at Al-Zahraa University in Kerbala/Iraq (n=409).

The demographic characteristics of the sample showed that about two thirds were in the second study year, 88.5% were single, 61.1% from second study year, 88.1% single and 80.2% of the students were from Kerbala governorate (Table 1).

Most of the students (90%) reported to be familiar or somewhat familiar with Artificial Intelligence, while only one tenth of the students mentioned to be not familiar with AI (Figure 2).

Figure 2. Familiarity with Artificial Intelligence Among Students at Al-Zahraa University in Kerbala/Iraq (n=409).

More than one half of the students (57.7%) know AI, whereas a smaller percentage (42.7%) reported to know AI medical application. With regards AI applications in various medical fields, approximately 17.1% were aware of AI applications in radiology, while a similar proportion (18.8%) reported knowledge of AI applications in pathology. However, most of the students (80.7%) believe in AI positive impact; and more than one half of them (56.5%) were interested in pursuing AI studies (Table 2). For machine Deep learning, only one quarter (25.7%) reported having knowledge about this discipline. A clear deficit in students’ knowledge might be to poor education about AI, where only a small minority (8.1%) reported being taught about AI (Table 2).

More than 90% of the participants were confident to understand Artificial Intelligence technologies in medical fields (Figure 3).

Figure 3. The proportion of being confident to understand Artificial Intelligence technologies in medical fields by students at Al-Zahraa University in Kerbala/Iraq (n=409).

Only a small minority of the students (5%) reported that Artificial Intelligence is not important for the medical fields; while almost one half (49%) of the students considered it as extremely important, and another half evaluated it to be somewhat important (Figure 4).

Figure 4. Evaluation of importance of AI in medical fields by students at Al-Zahraa University in Kerbala/Iraq (n=409).

The associations of different questions about being familiar with AI and age groups were mostly not significant. Although knowledge about AI was not significantly (p=0.079) associated with age; almost double proportion of younger students answered to be somewhat familiar with AI compared to higher age group (35.1% of 18–22-year aged students vs. 22.8% of 23–28-year group). Aligned with this finding; double proportion of older group reported to know nothing about AI compared to the younger students (39.1% of 18–22-year aged students vs. 17.5% of 23–28-year group). When comparison was restricted only to these two age groups and those above 28 years were excluded, the trend chi-square test was significant (p=0.011). The same trend was also applicable for being interested in pursuing AI studies, but here the difference was significant (p=0.035). A bigger proportion of younger students were somewhat interested to pursuing AI studies compared to higher age group (58.8% of 18–22-year aged students vs. 49.1% of 23-28 year group), and the opposite was true for the those not interested to pursuing AI studies compared to the younger students (35.1% of 18-22 year aged students vs. 23.7% of 23-28 year group) (Table 3).

p=0.035

As expected, highly significant positive association (p<0.001) was found between Knowledge about AI and being taught about AI and also with many other details about AI applications including: being familiar with AI; knowing machine deep learning; know AI medical application; know AI radiology and pathology applications; believe in AI positive impact; think AI poses ethical concerns and being interested pursuing AI studies. Additionally, highly significant negative association (p<0.001) was found between Knowledge about AI and study year (70.8%of second year students were somewhat knowledgeable about AI compared to 20.8% in the third year and 8.5% in the fourth year). On the other hand, many additional aspects concerning AI applications were highly positively correlated (p<0.001) with learning about AI and believed in its beneficial effects.

Discussion

The aim of this study was to examine Al-Zahraa university for women undergraduate medical students' preparedness for AI.

It is necessary to modify expectations, roles, and job definitions for healthcare workers as the information age fades and the artificial intelligence period becomes more prevalent.¹⁹

The research concentrates on medical students' opinions on artificial intelligence in medicine, which reflects their uncertainties and fears about the field. The aim of this study was to determine the knowledge of undergraduate medical students for AI.

In this study, the majority of the students (90%) reported to be familiar or somewhat familiar with Artificial Intelligence which is in line with Samer study²⁰ The outcomes showed that an impressive majority of participants (97.2%) were familiar with artificial intelligence ( Figure 2).

The researcher study reported that 57.7% Know artificial intelligence and 25.7% Know machine Deep learning which is not similar to Lebanon study²⁰ The participants' knowledge of deep learning and machine learning was only 33.5% and 44.4%, respectively. Also agree with Marwa study¹⁹, which concluded that 187 (49%) of the subjects knew about AI ( Table 1).

In this study 330(80.7%) of the students believe in AI positive impact in their future work which is consistent with Jackson study¹¹ which concluded that About 49% of the participants said AI could make healthcare more accessible and also consistent with Chen study⁷ which indicated that 77% were optimistic about the prospect of clinical AI.

Students in this study are aware of the use of AI in Radiology 70 (17.1%) and Pathology 77 (18.8%) which is almost inconsistent with those in Sarya study⁴, which found that AI is crucial in pathology and radiology, respectively 445(29.5) and 396(26.3) strongly agreeing. According to participants in the Pinto study,²¹ AI may be able to identify defects in radiological examinations (83%) but not completely diagnose them (56%). According to Stewart study¹⁴, students identified pathology (58.2%), and radiology (72.6%) as the specialties most likely to be affected by AI.

The percentage of medical students in the current study who did not believe AI contributes to ethical concerns was 118, or 28.8%. This is far lower than the findings of the Jackson study¹¹, which found that more than 50% of medical students were unsure about maintaining patient confidentiality while adopting AI. Additionally, 53.5% of the poll participants said AI might result in a breach of professional confidentiality.

The researcher reported that 107 (26.1%) Interested in pursuing AI studies, while in Kamel study¹³ About two-thirds of students strongly agreed or agreed that AI would become common in the future (67.9%, 237) and would revolutionize medical fields (68.7%, 240). Ali study¹⁶ reported that 289 (82.1%) thought AI training or instruction should be offered to medical students. Comparing to the researcher's study, both studies show higher percentages.

Also the researcher notice that 91% of Al-Zahraa university students understand Artificial Intelligence technologies in medical fields. Ali study¹⁶ reported that Most students (213, 60.5%) understand the fundamentals of artificial intelligence.

In this study almost one half (49%) of the students considered AI extremely important, and another half evaluated it to be somewhat important (Figure 4). Mona study¹⁷reported that1.4% of the students stated that teaching AI would be helpful to those pursuing careers in medicine, and 89% of the students thought that AI was vital in the medical industry.

Interestingly, almost double proportion of younger students answered to be somewhat familiar with AI and interested pursing AI study compared to higher age group which might be responsible for why younger people may be more educated and interested in AI than older individuals. For the same reason, a significantly significant negative correlation (p<0.001) between study year and AI knowledge was found (70.8% of second-year students had some knowledge of AI, compared to 20.8% in the third year and 8.5% in the fourth).

Conclusion

To successfully prepare medical graduates for the future incorporation of artificial intelligence in medicine, more study will be essential to analyze and reconcile these outcomes. The study discovered that while Al-Zahraa students understand artificial intelligence (AI) well, they know not much about deep learning, machine learning, and AI applications in radiology and pathology. nevertheless, the majority of them are eager to continue their AI education.

The lack of understanding in this area can lead to difficulty educating students about AI, underscoring the pressing need for a comprehensive approach to medical education. AI seems to be of interest to Al-Zahraa University for Women students. They feel they have no idea the fundamental computing concepts or the constraints of AI, nevertheless, as they have not had any instruction around the subject. Students believed it was essential to pick up all the knowledge and capabilities needed to be successful in medical use of artificial intelligence.

It is important that AI and AI ethics be built into medical education in order to ensure that students will be able to use AI responsibly and efficiently when the demands of future medical practice arise, as well as to improve students' AI literacy.

Limitation

Because this study was limited to one private medical facility and participants were chosen by non-probability sampling, it might happen that the results will not hold true in other contexts. The sample's make up places restrictions on the study's findings. The majority of participants participate in medical programs and attending medical universities. As a result, it is difficult to make conclusions about the general level of AI literacy among Iraqi or even global students. Furthermore, as the study was voluntary, there may have been a selection bias since the students who took part may have been more interested in or taught about AI than those who did not.

Consent

Prior to the research, ethical approval (permit no. HREC 84) was given by the independent ethics committee of Al-Zahraa University for Women in Karbala, Iraq.

Consent communications explaining the meaning of the study and the researcher's right to privacy were emailed to everyone who received a questionnaire.

Participants decided that a statement explaining the importance of the study and their right to share their responses with the researcher while respecting their privacy would be emailed to everyone on the questionnaire's recipient list. They were advised that they might opt out of the study at any time without providing explanation, and they were given the choice to decline participation. This procedure was approved by the Ethics committee (permit no. HREC 84).