Browsing by Author "Munabi, Ian G."

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    “I can no longer give take-home exams”: health professionals educators’ experiences and perceptions regarding the use of artificial intelligence in health professions education in Uganda.
    (BMC, 2025) Mukunya, David; Nantale, Ritah; Paungholi, Kennedy; Epuitai, Joshua; Kayemba, Frank; Jemba, Brian; Ajalo, Elizabeth; Afodun, Adam; Musaba, Milton W.; Munabi, Ian G.; Kiguli, Sarah; Mubuuke, A. G.
    Introduction: Artificial intelligence (AI) tools offer immense opportunities and challenges for medical education. However, there is limited information about the use of AI among health professional educators, particularly in low and middle-income countries. We aimed to explore the experiences and perceptions regarding AI use in health professional education. Methods and materials: We collected qualitative data using in-depth interviews with 19 health professional educators. The interviews were audio-recorded and transcribed verbatim. We used Atlas Ti version 9.1 to organise the data. We used Braun and Clarke’s six-step thematic analysis for data analysis. The study was approved by the Busitema University Research and Ethics Committee (BUFHS-2023-79). Results: Three major themes were identified from the data: uptake and use of AI, perceived benefits of AI in health professional education, and concerns regarding AI use. We noted initial reluctance to support AI use, while its use varied from no or infrequent use to frequent use. Health professional educators used AI for various reasons, such as for teaching, student assessment, research, and personal work. AI was perceived to be beneficial in improving the clarity of writing, providing access to individual-tailored information, teaching, learning, and assessment, and research purposes. The barriers to AI use included a lack of institutional policies to guide AI use, limited capacity to afford paid AI versions, and reluctance to use AI. AI was seen to have inherent limitations, which included inaccurate information and a lack of contextual information for resource-limited settings. The fears of AI use included the risk of over-reliance on AI, academic misconduct, examination malpractice, ethical conflicts, and integrity. Conclusion: AI use in health professional education was perceived to have some benefits, amidst concerns that may derail its use in health professional education. The lack of policy and guidelines to govern the use of AI in health professions education underscores the need to develop policies and guidelines that safeguard and promote responsible and ethical use of AI. Keywords Health professional education, Artificial intelligence, Educators, Uganda
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    Specialty career preferences among final year medical students at Makerere University College of health sciences, Uganda :
    (BMC, 2021) Kuteesa, Job; Musiime, Victor; Munabi, Ian G.; Mubuuke, Aloysius G.; Opoka, Robert; Mukunya, David; Kiguli, Sarah
    Background: Uganda has an imbalanced distribution of the health workforce, which may be influenced by the specialty career preferences of medical students. In spite of this, there is inadequate literature concerning the factors influencing specialty career preferences. We aimed to determine the specialty career preferences and the factors influencing the preferences among fifth year medical students in the School of Medicine, Makerere University College of Health Sciences (MakCHS). Methods: A sequential explanatory mixed methods study design with a descriptive cross-sectional study followed by a qualitative study was used. A total of 135 final year medical students in MakCHS were recruited using consecutive sampling. Self-administered questionnaires and three focus group discussions were conducted. Quantitative data was analysed in STATA version 13 (StataCorp, College Station, Tx, USA) using descriptive statistics, chi-square tests and logistic regression. Qualitative data was analysed in NVIVO version 12 (QRS International, Cambridge, MA) using content analysis. Results: Of 135 students 91 (67.4%) were male and their median age was 24 years (IQR: 24, 26). As a first choice, the most preferred specialty career was obstetrics and gynecology (34/135, 25.2%), followed by surgery (27/135, 20.0%), pediatrics (18/135, 13.3%) and internal medicine (17/135, 12.6%). Non-established specialties such as anesthesia and Ear Nose and Throat (ENT) were not selected as a first choice by any student. Female students had 63% less odds of selecting surgical related specialties compared to males (aOR = 0.37, 95%CI: 0.17–0.84). The focus group discussions highlighted controlled lifestyle, assurance of a good life through better financial remuneration and inspirational specialists as facilitators for specialty preference. Bad experience during the clinical rotations, lack of career guidance plus perceived poor and miserable specialists were highlighted as barriers to specialty preference. Conclusion: Obstetrics and Gynecology, Surgery, Pediatrics and Internal Medicine are well-established disciplines, which were dominantly preferred. Females were less likely to select surgical disciplines as a career choice. Therefore, there is a need to implement or establish career guidance and mentorship programs to attract students to the neglected disciplines. Keywords: Career, Medical, Preferences, Specialty, Student