Anxiety among Medical Students Regarding Generative Artificial Intelligence Models: A Pilot Descriptive Study DOI Open Access
Malik Sallam,

Kholoud Al-Mahzoum,

Yousef Mubrik N. Almutairi

и другие.

Опубликована: Авг. 16, 2024

Despite the potential benefits of generative Artificial Intelligence (genAI), concerns about its psy-chological impact on medical students, especially with regard to job displacement, are apparent. This pilot study, conducted in Jordan during July–August 2024, aimed examine specific fears, anxieties, mistrust, and ethical students could harbor towards genAI. Using a cross-sectional survey design, data were collected from 164 studying across various academic years, employing structured self-administered questionnaire an internally consistent FAME scale—representing Fear, Anxiety, Mistrust, Ethics comprising 12 items, three items for each construct. The results indicated variable levels anxiety genAI among participating students: 34.1% reported no role their future careers (n = 56), while 41.5% slightly anxious 61), 22.0% somewhat 36), 2.4% extremely 4). Among constructs, Mistrust was most agreed upon (mean: 12.35±2.78), followed by construct 10.86±2.90), Fear 9.49±3.53), Anxiety 8.91±3.68). Sex, level, Grade Point Average (GPA) did not significantly affect students’ perceptions However, there notable direct association between general elevated scores constructs scale. Prior exposure previous use modify These findings highlighted critical need refined educational strategies address integration training. demonstrated pervasive anxiety, fear, regarding deployment healthcare, indicating necessity curriculum modifi-cations that focus specifically these areas. Interventions should be tailored increase familiarity competency, which would alleviate apprehension equip physicians engage this inevitable technology effectively. study also importance incorporating discussions into courses mistrust human-centered aspects Conclusively, calls proactive evolution education prepare AI-driven healthcare practices shortly ensure well-prepared, confident, ethically informed professional interactions technologies.

Язык: Английский

Artificial Intelligence in Health Professions Education assessment: AMEE Guide No. 178 DOI
Ken Masters, Heather MacNeill, Jennifer Benjamin

и другие.

Medical Teacher, Год журнала: 2025, Номер unknown, С. 1 - 15

Опубликована: Янв. 9, 2025

Health Professions Education (HPE) assessment is being increasingly impacted by Artificial Intelligence (AI), and institutions, educators, learners are grappling with AI's ever-evolving complexities, dangers, potential. This AMEE Guide aims to assist all HPE stakeholders helping them navigate the uncertainty before them. Although impetus AI, grounds its path in pedagogical theory, considers range of human responses, then deals types, challenges, AI roles as tutor learner, required competencies. It discusses difficult ethical issues, ending considerations for faculty development technicalities acknowledgment assessment. Through this Guide, we aim allay fears face change demonstrate possibilities that will allow educators harness full potential

Язык: Английский

Процитировано

1

Human versus Artificial Intelligence: ChatGPT-4 Outperforming Bing, Bard, ChatGPT-3.5 and Humans in Clinical Chemistry Multiple-Choice Questions DOI Creative Commons
Malik Sallam,

Khaled Al‐Salahat,

Huda Eid

и другие.

Advances in Medical Education and Practice, Год журнала: 2024, Номер Volume 15, С. 857 - 871

Опубликована: Сен. 1, 2024

Artificial intelligence (AI) chatbots excel in language understanding and generation. These models can transform healthcare education practice. However, it is important to assess the performance of such AI various topics highlight its strengths possible limitations. This study aimed evaluate ChatGPT (GPT-3.5 GPT-4), Bing, Bard compared human students at a postgraduate master's level Medical Laboratory Sciences.

Язык: Английский

Процитировано

6

Generative AI Techniques and Models DOI
Rajan T. Gupta, Sanju Tiwari, Poonam Chaudhary

и другие.

Lecture notes on data engineering and communications technologies, Год журнала: 2025, Номер unknown, С. 45 - 64

Опубликована: Янв. 1, 2025

Процитировано

0

Anxiety among Medical Students Regarding Generative Artificial Intelligence Models: A Pilot Descriptive Study DOI Open Access
Malik Sallam,

Kholoud Al-Mahzoum,

Yousef Mubrik N. Almutairi

и другие.

Опубликована: Авг. 16, 2024

Despite the potential benefits of generative Artificial Intelligence (genAI), concerns about its psy-chological impact on medical students, especially with regard to job displacement, are apparent. This pilot study, conducted in Jordan during July–August 2024, aimed examine specific fears, anxieties, mistrust, and ethical students could harbor towards genAI. Using a cross-sectional survey design, data were collected from 164 studying across various academic years, employing structured self-administered questionnaire an internally consistent FAME scale—representing Fear, Anxiety, Mistrust, Ethics comprising 12 items, three items for each construct. The results indicated variable levels anxiety genAI among participating students: 34.1% reported no role their future careers (n = 56), while 41.5% slightly anxious 61), 22.0% somewhat 36), 2.4% extremely 4). Among constructs, Mistrust was most agreed upon (mean: 12.35±2.78), followed by construct 10.86±2.90), Fear 9.49±3.53), Anxiety 8.91±3.68). Sex, level, Grade Point Average (GPA) did not significantly affect students’ perceptions However, there notable direct association between general elevated scores constructs scale. Prior exposure previous use modify These findings highlighted critical need refined educational strategies address integration training. demonstrated pervasive anxiety, fear, regarding deployment healthcare, indicating necessity curriculum modifi-cations that focus specifically these areas. Interventions should be tailored increase familiarity competency, which would alleviate apprehension equip physicians engage this inevitable technology effectively. study also importance incorporating discussions into courses mistrust human-centered aspects Conclusively, calls proactive evolution education prepare AI-driven healthcare practices shortly ensure well-prepared, confident, ethically informed professional interactions technologies.

Язык: Английский

Процитировано

4