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Awareness and Perception Regarding the Use of Artificial Intelligence (AI) among Teaching Faculty at Indus Hospital and Health Network

2025·0 Zitationen·National Journal of Health SciencesOpen Access
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2025

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Abstract

Abstract: Background: Artificial intelligence (AI) is gaining traction in medical education, yet faculty awareness and acceptance in countries like Pakistan remain underexplored. Objective: This study was designed to evaluate awareness and perceptions towards artificial intelligence (AI) among the teaching faculty of Indus Hospital and Health Network (IHHN). Materials and Methods: A two-month cross-sectional study was conducted from 15th December 2023 to 15th April 2024 at Indus Hospital and Health Network (IHHN). Data collection was completed during this period. All teaching faculty members were invited to participate through an anonymous, self-administered questionnaire distributed via the RedCap system, after obtaining informed consent. The questionnaire was self-developed and pilot-tested for clarity and reliability (Cronbach’s alpha = 0.812). It covered demographic details, awareness, perceptions, perceived impact, and prior AI-related training. Data were analyzed using SPSS version 28. Descriptive statistics were computed, and associations between categorical variables were assessed using Chi-square or Fisher’s exact tests, with a significance level set at p < 0.05. Result: Overall, 77.5% of participants were aware of AI use in medical education. Among the 81 respondents (70.4% female), most were aged 35-44 years (40.7%) and had 1-5 years of teaching experience (28.8%). While 72.8% had no prior AI training, gender and age differences were noted: women favored AI in worksheet design (p = 0.040), and younger faculty showed both greater interest in slide creation (p = 0.042) and more fear of AI (p = 0.001). Conclusion: The results emphasize the necessity for formal AI training programs to facilitate faculty preparedness and generational issues in medical education. Keywords: Artificial intelligence (AI), Medical education, Teaching faculty, Awareness, Perceptions, AI training.

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