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All Journal Asian Journal of Public Health and Nursing Journal of Applied Artificial Intelligence in Education
Lida, Vann
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Computer Science & IT Education Medicine & Pharmacology Nursing Public Health

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Socioeconomic Inequalities in Pregnancy Termination among Young Women in Cambodia: A Cross-sectional Analysis of the 2021–22 Demographic and Health Survey Sokha, Yem; Sokunthea, Kem; Lida, Vann; Sreypeov, Tun
Asian Journal of Public Health and Nursing Vol. 3 No. 1 (2026)
Publisher : Queeva Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62377/75j94f08

Abstract

Background: Pregnancy termination among adolescents and young women reflects gaps in contraceptive access, unmet need for family planning, and unequal access to sexual and reproductive health information and services. In Cambodia, limited recent national evidence exists on socioeconomic patterns and determinants of pregnancy termination among young women, despite persistent adolescent fertility and early marriage. This study aimed to estimate the prevalence of pregnancy termination among adolescents and young women in Cambodia and examine socioeconomic patterns and associated factors using data from the Cambodia Demographic and Health Survey (CDHS) 2021–22. Methods: This cross-sectional secondary analysis used nationally representative data from the CDHS 2021–22 women's questionnaire. The study population included women aged 15–24 years (N=5,783). The outcome was a self-reported history of pregnancy termination, based on DHS standard definitions. Key exposures included wealth index, education level, and place of residence. Additional covariates included age group, marital status, parity, employment status, media exposure, and contraceptive use. Survey-weighted descriptive statistics and multivariable logistic regression were used to examine associations while accounting for complex survey design. Results: The overall prevalence of pregnancy termination was 5.28% (95% CI: 4.52–6.16). Prevalence varied significantly by socioeconomic status: 3.8% among women from poor households, 5.3% among middle-income, and 6.8% among wealthy households (p<0.001). Women with secondary or higher education had higher prevalence (6.2%) compared to those with no education (3.9%, p<0.001). In multivariable analysis, factors significantly associated with increased odds of pregnancy termination included wealthier households (aOR=1.82, 95% CI: 1.24–2.67), higher education (aOR=1.58, 95% CI: 1.09–2.29), urban residence (aOR=1.44, 95% CI: 1.08–1.92), older age 20–24 years (aOR=2.15, 95% CI: 1.61–2.88), union status (aOR=3.42, 95% CI: 2.48–4.71), and women with two or more children (aOR=5.68, 95% CI: 3.92–8.23). Conclusion: Pregnancy termination among young Cambodian women shows a distinct positive socioeconomic gradient, with higher prevalence among wealthier and more educated women, contrasting with patterns in some high-income countries. The strong association with parity indicates that termination is primarily used for birth spacing and limiting. These findings highlight the need for strengthening youth-focused sexual and reproductive health services and ensuring equitable access to quality contraception across all socioeconomic groups.
AI-Powered Tools to Enhance Critical Thinking and Clinical Reasoning in Nursing Education: A Scoping Review with Implications for Low- and Middle-Income Countries YEM, Sokha; YIM, Sovannra; KEM, Sokunthea; TUN, Sreypeov; Lida, Vann
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.
Co-Authors KEM, Sokunthea Sokha, Yem Sokunthea, Kem Sreypeov, Tun TUN, Sreypeov YEM, Sokha YIM, Sovannra