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All Journal Indonesian Journal of Health Research and Development Journal of Applied Artificial Intelligence in Education
Sokha YEM
university of puthisastra
Computer Science & IT Education Health Professions Medicine & Pharmacology Nursing Public Health

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AI-Powered Tools to Enhance Critical Thinking and Clinical Reasoning in Nursing Education: A Scoping Review with Implications for Low- and Middle-Income Countries Sokha YEM; Sovannra YIM; Sokunthea KEM; Sreypeov TUN; Vann Lida
Journal of Applied Artificial Intelligence in Education Vol 2, No 1 (2026): July 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/jaaie.v2i1.396

Abstract

Artificial Intelligence (AI) is increasingly integrated into educational systems worldwide, offering innovative approaches to improve learning outcomes in health professions education. In nursing, AI-powered tools such as ChatGPT, intelligent tutoring systems (ITS), virtual patient simulation platforms, and automated assessment systems have shown potential to strengthen critical thinking (CT) and clinical reasoning (CR), which are essential competencies for safe and evidence-based practice. However, their scope, effectiveness, and applicability remain underexplored, particularly in low- and middle-income countries (LMICs), where limited digital infrastructure, faculty capacity gaps, and resource constraints hinder implementation. This scoping review aimed to map existing evidence on AI-powered tools used in nursing and health professions education to enhance CT and CR, identify implementation gaps and barriers, and derive context-specific implications for LMICs, with particular attention to Cambodia. Following the Arksey and O’Malley framework, refined by Levac et al. and Peters et al., and guided by PRISMA-ScR, a systematic search was conducted in PubMed, Scopus, and CINAHL for peer-reviewed publications from January 2015 to October 2024. Forty-two studies from 15 countries were included. Four categories of AI tools were identified: conversational agents (n = 14), intelligent tutoring systems (n = 11), virtual patient simulations (n = 10), and automated assessment systems (n = 7). Most studies reported positive outcomes, with seven of eight RCTs showing significant CT improvement and virtual simulations consistently enhancing CR. Nevertheless, infrastructure limitations, faculty unpreparedness, ethical concerns, and licensing costs remain major barriers. Sustainable AI integration in LMIC nursing education requires context-sensitive infrastructure, capacity-building, governance, and stronger longitudinal research.
A Low Prevalence and Complementary Nature of Traditional Medicine Use in Maternal Healthcare: Evidence from Cambodia Demographic and Health Survey 2021-22: Traditional Medicine Use in Cambodia Sokha Yem; Kem Sokunthea; Tun Sreypeov
Indonesian Journal of Health Research and Development Vol. 4 No. 2 (2026): Indonesian Journal of Health Research and Development
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijhrd.v4i2.607

Abstract

Background: Cambodia has achieved substantial gains in modern maternal healthcare coverage, yet nationally representative evidence on residual traditional birth attendant (TBA) use and home delivery, and whether these persist alongside or instead of modern care, remains limited. This study estimated the prevalence and correlates of TBA use and home delivery in Cambodia.Aims: This study estimated the prevalence, patterns, and correlates of TBA use and home delivery in maternal healthcare in Cambodia.Methods: We analyzed data on 6,968 women with a birth in the five years preceding the Cambodia Demographic and Health Survey (CDHS) 2021–22. TBA/home-delivery (TBA/HD) care was defined as antenatal care from a TBA, delivery assisted by a TBA, or home (non-facility) delivery. Weighted prevalence and survey-adjusted multivariable logistic regression identified correlates.Results: Overall prevalence of TBA/HD care was 1.25% (95% CI: 0.92–1.69%; 154/6,968 unweighted) and was markedly higher among rural than urban women, among women with no education than higher education, among the poorest than the richest wealth quintile, and among women with four or more children than one child (all p<0.001). In the fully adjusted model, the poorest quintile had over six times the odds of TBA/HD care versus the richest (aOR=6.82, 95% CI: 2.10–22.13), p=0.001), and women with one child had 69% lower odds versus those with four or more (aOR=0.31, 95% CI: 0.16–0.61). p=0.001). Residence and education were not independently significant after adjustment.Conclusion: TBA use and home delivery are uncommon in Cambodia and concentrated among the poorest and highest-parity women; wealth and parity, more than education or residence, distinguish residual TBA/HD care after adjustment. Findings support targeting the poorest women rather than population-wide campaigns.
Co-Authors Kem Sokunthea Sokunthea KEM Sovannra YIM Sreypeov TUN Tun Sreypeov Vann Lida