Aug 2026· International Journal of Medical Education· Vol 17, pp.
121-130
· 0 citations
Medicine
TL;DR
Effective AI adoption in psychiatric care and education can be facilitated by clearly delineating tasks, embedding digital literacy into training, communicating robust governance structures, and introducing peer-led communities of practice.
Abstract
Objectives
This study aimed to understand how AI's perceived role interacts with emerging barriers and facilitators to identify factors influencing its adoption across clinical and educational professions in Singapore.
Methods
This study followed a qualitative approach guided by a medical-pedagogical theoretical framework. Semi-structured interviews were conducted between May and July 2025 and followed an interview guide based on the medical-pedagogical framework. Twenty-four people participated, including eight nurses, six psychiatrists, and 10 allied health professionals. All were clinicians and educators. Data were analysed using thematic analysis, with attention to emergent patterns across patient care and educational contexts.
Results
Participants recognised significant potential for AI in patient care and healthcare professions education, particularly for information access, retrieval, clinical documentation, AI-augmented training methods such as virtual patients and educational content creation. Barriers included fears of professional skill degradation, role confusion, lack of familiarity with capabilities and the need for personal evidence of benefit. Enablers encompassed integrated, context-specific training, clear governance frameworks, and peer networks facilitating experiential learning and responsible use. Participants emphasised maintaining human connection and reflective practice as essential to psychiatric care and education.
Conclusions
Effective AI adoption in psychiatric care and education can be facilitated by clearly delineating tasks, embedding digital literacy into training, communicating robust governance structures, and introducing peer-led communities of practice. Relevant stakeholders should be engaged to align AI deployment with real clinical workflows, optimising both patient care and educational outcomes.
Dedicated time for AI education for CHNs is needed to address how recommendations are generated and the significance to give to AI recommendations, clear policies and guidelines need to be established to inform CHNs use of AI.
M. H. Betkus, D. Banner, L. Currie et al.· The Canadian journal of nurs...· 0 citations
Insight is provided into developing AI-ready medical education models that balance technical competence with humanistic values and factors influencing AI adoption in medical training, including performance expectancy, effort expectancy, social influence, and facilitating conditions.
T. Murphy, Ginger Vaughn, Rob E. Carpenter et al.· International Medical Educat...· 0 citations
It was concluded that the integration of AI into the training of health professionals requires a deliberate pedagogical approach, the strengthening of faculty digital competencies, and specific institutional ethical frameworks.
Katherine Jazmín Gaibor Veloz, Diana Ivonne Castro Córdova, Belén Estefanía Albán Manzano et al.· MENTOR revista de investigac...· 0 citations
Objectives: To explore current understanding of patient centered care (PCC), its teaching and assessment practices and perceived factors influencing PCC learning in undergraduate and postgraduate medical education within a traditional cultural context.
Methodology: An exploratory qualitative descriptive study was conducted from January to September 2024 in public sector hospitals in different provinces of Pakistan. Data was collected through focus group discussions with interns and residents of medicine, surgery and pediatrics selected through purposive sampling. Actor Network Theory informed data analysis and thematic analysis done using Braun and Clarke method.
Results: Six focus groups were held with 33 participants in total. Four main themes and 14 subthemes emerged from analysis: Comprehending Patient-Centered Care, Teaching and Learning Practices, Influencing Factors, and Practice Implications. The central point highlighted was treating the patient as a whole, involving them in their care and giving consideration to personal values and preferences. Some PCC skills identified were technical expertise, communication skills, professionalism and understanding patient’s culture. Current teaching practices were theoretical with limited practical training with insufficient assessment. Curriculum, Faculty, Service, Personal and Patient-related factors were recognized as influencing factors.
Conclusion: This study provides insights into learners’ perspectives and current teaching and assessment of patient-centered care within Pakistani context. The study highlights that to achieve the goal of trained workforce, changes in teaching and assessment practices, curriculum design and policy development at both institutional and national level are required while taking into account the sociocultural context. Addressing these factors could enhance preparation of future healthcare professionals to deliver holistic, patient-centered care.
Afifa Tabassum, Usman Mahboob, S. Ali· Pakistan Journal of Medical...· 0 citations
Although baseline knowledge of AI among medical students and faculty members was limited, both groups demonstrated strong positive attitudes and a clear demand for further training, highlighting the importance of integrating structured AI education into medical curricula to support the responsible and effective use of emerging technologies.
Ay Sıla Çaloğlu, Halid Durna, Zeynep Naz Ergen et al.· Journal of Medical Education...· 0 citations
Generative AI presents a paradox in nursing education as it enables innovation and personalised learning, but poses risks to academic integrity and deep learning when implementation lacks ethical consideration and pedagogical rigour.
Lucie Ramjan, Belinda McGrath, C. Walters et al.· Journal of Clinical Nursing· 0 citations
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