Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis
Ontology highlight
ABSTRACT:
SUBMITTER: Amiri H
PROVIDER: S-EPMC11017500 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
Similar Datasets
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.
| S-EPMC10470885 | biostudies-literature
Project description:IntroductionThe 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.MethodsAn 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.ResultsModerate 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.ConclusionsThis 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.
| S-EPMC10722664 | biostudies-literature
Project description:OBJECTIVES:To explore the attitudes of United Kingdom (UK) medical students regarding artificial intelligence (AI), their understanding, and career intention towards radiology. We also examine the state of education relating to AI amongst this cohort. METHODS:UK medical students were invited to complete an anonymous electronic survey consisting of Likert and dichotomous questions. RESULTS:Four hundred eighty-four responses were received from 19 UK medical schools. Eighty-eight percent of students believed that AI will play an important role in healthcare, and 49% reported they were less likely to consider a career in radiology due to AI. Eighty-nine percent of students believed that teaching in AI would be beneficial for their careers, and 78% agreed that students should receive training in AI as part of their medical degree. Only 45 students received any teaching on AI; none of the students received such teaching as part of their compulsory curriculum. Statistically, students that did receive teaching in AI were more likely to consider radiology (p = 0.01) and rated more positively to the questions relating to the perceived competence in the post-graduation use of AI (p = 0.01-0.04); despite this, a large proportion of students in the taught group reported a lack of confidence and understanding required for the critical use of healthcare AI tools. CONCLUSIONS:UK medical students understand the importance of AI and are keen to engage. Medical school training on AI should be expanded and improved. Realistic use cases and limitations of AI must be presented to students so they will not feel discouraged from pursuing radiology.
| S-EPMC7002761 | biostudies-literature
Project description:BackgroundTo investigate the attitude and formal suggestions on talent cultivation in the field of medical artificial intelligence (AI).MethodsAn electronic questionnaire was sent to both medical-related field or non-medical field population using the WenJuanXing web-application via social media. The questionnaire was designed to collect: (I) demographic information; (II) perception of medical AI; (III) willingness to participate in the medical AI related teaching activities; (IV) teaching content of medical AI; (V) the role of medical AI teaching; (VI) future career planning. Respondents' anonymity was ensured.ResultsA total of 710 respondents provided valid answers to the questionnaire (57.75% medical related, 42.25% non-medical). About 73.8% of respondents acquired related information from network and social platform. More than half the respondents had basic perception of AI applicational scenarios and specialties in medicine, meanwhile were willing to participate in related general science activities (conference and lectures). Respondents from medical healthcare related fields, with high academic qualifications of male ones demonstrated showed significant better understanding and stronger willingness (P<0.05). The majority agreed medical AI courses should be set as major elective (42.82%) during undergraduate stages (89.58%) involving medical and computer science contents. An overwhelming majority of respondents (>80%) acknowledged the potential roles of medical AI teaching. Surgeon, ophthalmologist, physicians and researchers are the top tier considerations for ideal career regardless of AI influence. Radiology and clinical laboratory subjects are more preferred considering the development of medical AI (P>0.05).ConclusionsThe potential role of medical AI talent cultivation is widely acknowledged by public. Medical related professions demonstrated higher level of perception and stronger willingness for medical AI educational events. Merging subjects as radiology and clinical laboratory subjects are preferred with broad talents demands and bright prospects.
| S-EPMC7327345 | biostudies-literature
Project description:BackgroundAdequate communication skills in healthcare professionals are one of the key elements required for achieving high-quality healthcare. Thus, measurement instruments able to assess the dimensions related to these skills, including attitudes towards communication, are useful and convenient tools.ObjectivesTo (a) cross-culturally adapt and validate a scale to measure attitudes towards communication in a sample of nursing students in the Spanish environment; (b) describe the perceived attitudes of nursing degree students towards communication.MethodsWe conducted an instrumental study. First, we adapted the scale by applying a standardised linguistic validation procedure. After that, we determined its structural equivalence and evaluated its psychometric properties.ParticipantsA total of 255 students participated; their average age was 22.66 years (SD = 4.75) and 82% were female.ResultsThe internal consistency of the scale was adequate (0.75), and the data fit well with the model (CFI = 0.99; TLI = 0.99; RMSEA = .01 95% CI [.00-.05]). The overall instrument score poorly correlated with the self-efficacy in communication skills variable.ConclusionsThe attitudes towards communication scores for these nursing students were high. The Spanish version of the Attitudes Towards Health Communication scale had adequate psychometric properties and this tool could quickly and easily be applied to assess the attitudes of health profession students.
| S-EPMC8162233 | biostudies-literature
Project description:BackgroundLiving safely sexuality and without risk to one's health is an international priority. The youth age group has specific characteristics that make it a particularly vulnerable group for adverse consequences such as unwanted pregnancies or sexually transmitted infections. Health professionals are an important group to address this issue; however, to achieve a good result, sufficient knowledge is required to solve all the issues. This study aimed to assess the level of knowledge of young university students studying a nursing or a medical degree.MethodsA descriptive cross-sectional study of young medical and nursing students was conducted. The selection of participants was made by convenience. The Sexuality and Contraceptive Knowledge Instrument scale was used to measure knowledge level. A bivariate analysis was conducted using the Mann-Whitney U test or the Kruskal-Wallis H test, depending on the number of categories of the independent variable. Finally, a multivariate analysis was conducted using a multiple linear regression model, establishing the level of knowledge as the dependent variable and all variables that obtained statistical significance in the bivariate analysis as predictors. Data collection was carried out from October 2020 to March 2021.ResultsThe sample comprised 657 health university students. Participants had a good level of knowledge, with 77.9% answering 50% of the questions correctly. Before training, 34.15% of the participants did not pass 50% of the questions asked. This percentage decreased to 12.87% after receiving sexuality training during their university degrees. The main training gaps were found for the items on hormonal contraceptive methods. The bivariate analysis showed that female participants had significantly higher knowledge scores, as did those who had used a hormonal contraceptive method during the most recent intercourse or were aware of family planning centers. These variables maintained their significant effect at the multivariate level, obtaining two models with good explanatory power for participants of both university degrees.ConclusionThe general level of knowledge of the healthcare students was high and sufficient after receiving training during the university degree (87.13% of the participants obtain more than 50% of items correct). The main training gap was found for items on hormonal contraceptive methods, which should be emphasized in future training programs.
| S-EPMC10134607 | biostudies-literature
Project description: Not available
| S-EPMC10724669 | biostudies-literature
Project description:Human papillomavirus (HPV), which is linked to specific types of cancer, can be prevented by vaccination. This study aimed to determine the knowledge and attitudes of nursing students about HPV and its vaccine as well as their intentions towards personal vaccination. A total of 536 Spanish nursing students were invited to complete the Spanish version of the questionnaire "Knowledge, attitudes and intentions towards HPV". Overall, 367 surveys were completed (68.4% response rate). Data analysis included the calculation of three scores: the knowledge score, categorized into low (<33%), moderate (33%-66%), and good knowledge (>66%); the attitude score, sorted into positive (<2.5), neutral (2.5-3.5), and negative attitude (>3.5); and the intention score, categorized into not favorable (<4), neutral (4-7), and favorable intention (>7). Knowledge about HPV and its vaccine was moderate (54.34 ± 0.9%), and the attitude towards vaccination was positive (2.34 ± 0.03). The intention towards personal vaccination increased significantly after completing the questionnaire (before: 4.14 ± 0.27, after: 6.02 ± 0.28; p < 0.001). The present study highlights the need of training future nurses about HPV and its vaccine, considering the important role it plays in the prevention of sexually transmitted diseases.
| S-EPMC6888169 | biostudies-literature
Project description:Digital technologies in health care, including artificial intelligence (AI) and robotics, constantly increase. The aim of this study was to explore attitudes of 2020 medical students' generation towards various aspects of eHealth technologies with the focus on AI using an exploratory sequential mixed-method analysis. Data from semi-structured interviews with 28 students from five medical faculties were used to construct an online survey send to about 80,000 medical students in Germany. Most students expressed positive attitudes towards digital applications in medicine. Students with a problem-based curriculum (PBC) in contrast to those with a science-based curriculum (SBC) and male undergraduate students think that AI solutions result in better diagnosis than those from physicians (p < 0.001). Male undergraduate students had the most positive view of AI (p < 0.002). Around 38% of the students felt ill-prepared and could not answer AI-related questions because digitization in medicine and AI are not a formal part of the medical curriculum. AI rating regarding the usefulness in diagnostics differed significantly between groups. Higher emphasis in medical curriculum of digital solutions in patient care is postulated.
| S-EPMC9027704 | biostudies-literature
Project description:BackgroundArtificial intelligence (AI) application is increasingly used in all fields, especially, in medicine. However, for the successful incorporation of AI-driven tools into medicine, healthcare professional should be equipped with the necessary knowledge. From that, we aimed to assess the AI readiness among medical students in Jordan.MethodsA cross-sectional survey was conducted among medical students across 6 Jordanian universities. Prevalidated Medical Artificial Intelligence Readiness Scale for Medical Students questionnaire was used. The questionnaire was distributed through social media groups of students. SPSS v.27 was used for analysis.ResultsA total of 858 responses were collected. The mean AI readiness score was 64.2%. Students scored more in the ability domain with a mean of 22.57. We found that academic performance (Grade point average) positively associated with overall AI readiness (P = .023), and prior exposure to AI through formal education or experience significantly enhances readiness (P = .009). In contrast, AI readiness levels did not significantly vary across different medical schools in Jordan. Notably, most students (84%) did not receive a formal education about AI from their schools.ConclusionIncorporation of AI education in medical curricula is crucial to close knowledge gaps and ensure that students are prepared for the use of AI in their future career. Our findings highlight the importance of preparing students to engage with AI technologies, and to be equipped with the necessary knowledge about its aspect.
| S-EPMC11437586 | biostudies-literature