Work

Knowledge, attitudes, and practices toward artificial intelligence in pharmacy education and practice among pharmacy students and faculty in Bangladesh: a cross-sectional study

Year: 2026

Type: article

Abstract: Background Artificial intelligence (AI) is transforming healthcare systems, pharmaceutical innovation, and professional education globally. However, digital readiness for AI integration remains uneven across low- and middle-income countries (LMICs), raising concerns about equity, governance, and workforce readiness. Understanding institutional and individual readiness is crucial for sustainable execution within health systems. Objective To assess knowledge, attitudes, and practices (KAP) regarding AI among pharmacy students and faculty in Bangladesh and identify predictors of implementation readiness. Methods A multi-institutional cross-sectional study was conducted among 447 participants (382 students; 65 faculty) from accredited pharmacy programs following a stratified convenience sampling method. A validated KAP instrument was administered electronically. Group differences were analyzed using independent-sample t -tests, while associations and predictors were examined using Pearson correlation and multiple regression models. Results Faculty demonstrated higher AI knowledge scores than students (4.22 ± 0.57 vs. 3.95 ± 0.73; p = 0.005; Cohen's d = 0.41). Students showed stronger support for curricular integration ( p = 0.034). Knowledge was moderately correlated with positive attitudes ( r = 0.42, p < 0.001). Regression analysis identified prior exposure (β = 0.18, p < 0.05) and workshop participation (β = 0.25, p < 0.001) as significant predictors of positive attitudes ( p < 0.01, Adj R 2 = 0.28). Despite limited institutional funding (23.1%), 72.3% of participants expressed willingness to engage in the development of national AI guidelines. Concerns regarding data privacy and regulatory oversight were consistently reported. Conclusion Findings indicate emerging AI readiness within pharmacy education in Bangladesh, but structural capacity gaps persist. Framed through digital readiness and implementation science perspectives, the results highlight the need for coordinated curriculum reform, faculty development, and governance frameworks. Bangladesh may serve as a scalable LMIC model for ethically grounded, workforce-aligned AI integration in health systems.

Source: Dialogues in Health

DOI: 10.1016/j.dialog.2026.100365

Authors: Md. Masud Morshed, Jannatul Ferdoush, Abu Tayab Moin, Sharmin Sultana Dina, Farjana Akter Nipa, Rukyea Yeasmin Mysha

Institutions: University of Science and Technology Chittagong, Bangladesh Medical University, Daffodil International University, International Islamic University Chittagong

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDGs: Quality education, Good health and well-being

Open Access status: gold

Estimated APC paid: $1,130