Integrating Ethics, Professionalism, and Academic Integrity in Medical Education: A Systems-Based Conceptual Framework.

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Title: Integrating Ethics, Professionalism, and Academic Integrity in Medical Education: A Systems-Based Conceptual Framework.
Authors: Mir, Mohammad Muzaffar1, Alharthi, Muffarah Hamid2, Al Ameer, Ahmed Yahia3, Al Amri, Sultan Abdullah S.3, Mir, Gulzar Muzaffar4, Alremthi, Fahad5, Mir, Sadaf M.6, Al-Shahrani, Abdullah M.2, Abadi, Alsaleem Mohammed7, Alghamdi, Mushabab8, Patel, Ayyub Ali9, Mallick, Ayaz Khurram9, Senbel, Ahmed Mussad10, Sonpol, Hany M. A.11
Source: International Journal of Special Education. 2026 Special Issue, Vol. 41, p189-208. 20p.
Subject Terms: *Education ethics, *Educational evaluation, *Curriculum planning, *Medical education, Ethics, Professionalism, Professional identity, Systems theory
Abstract: Background Ethics, professionalism, and academic integrity are central to medical education and to sustaining public trust in the medical profession. However, ongoing transformations in health professions education, including competency-based reforms, intensified assessment cultures, digitalization, and the emergence of generative artificial intelligence, have introduced new and persistent challenges to their development. Increasing reports of ethical lapses, professionalism concerns, and academic misconduct suggest that traditional, fragmented approaches to ethics instruction and regulation may no longer be sufficient. Focus This paper examines ethics, professionalism, and academic integrity as socially situated and developmental processes rather than static competencies or solely individual attributes. Drawing on professional identity formation, sociocultural learning theory, the hidden curriculum, and systems thinking, it explores contemporary challenges related to role modelling, assessment pressures, learner moral distress, digital professionalism, and institutional governance. A systemsoriented conceptual framework is proposed, positioning professional identity formation as a central mediating process through which formal curricula, informal learning environments, assessment structures, and organizational cultures interact to shape ethical outcomes. Implications By interpreting ethical lapses as potential indicators of system misalignment rather than solely individual failure, this analysis highlights the importance of coherent, longitudinal, and institutionally aligned approaches to ethical development. The framework offers a structured lens to inform curriculum design, assessment practices, faculty development, and governance. Future work should prioritize theory-informed, longitudinal research and system-level interventions to better understand and support sustainable ethics, professionalism, and academic integrity in medical education [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Special Education is the property of International Journal of Special Education and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Integrating Ethics, Professionalism, and Academic Integrity in Medical Education: A Systems-Based Conceptual Framework.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Special+Education%22">International Journal of Special Education</searchLink>. 2026 Special Issue, Vol. 41, p189-208. 20p.
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  Data: Background Ethics, professionalism, and academic integrity are central to medical education and to sustaining public trust in the medical profession. However, ongoing transformations in health professions education, including competency-based reforms, intensified assessment cultures, digitalization, and the emergence of generative artificial intelligence, have introduced new and persistent challenges to their development. Increasing reports of ethical lapses, professionalism concerns, and academic misconduct suggest that traditional, fragmented approaches to ethics instruction and regulation may no longer be sufficient. Focus This paper examines ethics, professionalism, and academic integrity as socially situated and developmental processes rather than static competencies or solely individual attributes. Drawing on professional identity formation, sociocultural learning theory, the hidden curriculum, and systems thinking, it explores contemporary challenges related to role modelling, assessment pressures, learner moral distress, digital professionalism, and institutional governance. A systemsoriented conceptual framework is proposed, positioning professional identity formation as a central mediating process through which formal curricula, informal learning environments, assessment structures, and organizational cultures interact to shape ethical outcomes. Implications By interpreting ethical lapses as potential indicators of system misalignment rather than solely individual failure, this analysis highlights the importance of coherent, longitudinal, and institutionally aligned approaches to ethical development. The framework offers a structured lens to inform curriculum design, assessment practices, faculty development, and governance. Future work should prioritize theory-informed, longitudinal research and system-level interventions to better understand and support sustainable ethics, professionalism, and academic integrity in medical education [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Special Education is the property of International Journal of Special Education and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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