Aug 2026· Journal of Umm Al-Qura University for Medical Science· Vol 12· 0 citations· 22 references
TL;DR
A high reliance on informal, self-directed AI learning exists among students, revealing a critical gap in formal education and necessitate the urgent integration of structured, equitable AI curricula into Ghana’s nursing and midwifery training programs.
Abstract
Artificial Intelligence (AI) offers transformative potential for healthcare education, yet its adoption among key frontline cadres in low-resource settings remains poorly understood. This study is the first to investigate the predictors of AI usage and knowledge among nursing and midwifery students in Ghana. An analytical cross-sectional study was conducted with 676 students from the University of Health and Allied Sciences, recruited via convenience sampling. A validated questionnaire assessed AI knowledge, usage patterns, and sources of information. Data were analyzed using descriptive statistics, binary logistic regression, and ROC analysis in STATA v17.0. Most participants (78.6%) used AI, with significantly higher odds among males (aOR: 2.33, 95% CI;1.21–4.47, p = 0.011) and final-year students (aOR: 3.05, 95% CI;1.64–5.67, p = 0.001). While 73.7% demonstrated adequate knowledge, acquisition occurred primarily through informal sources (internet/media), with ChatGPT being the dominant tool. Predictive models for AI usage and knowledge demonstrated significant associations but modest discriminative power (AUC range: 0.58–0.63), indicating the role of unmeasured factors. A high reliance on informal, self-directed AI learning exists among students, revealing a critical gap in formal education. Despite strong adoption, significant demographic disparities and a clear “usage-knowledge disconnect” necessitate the urgent integration of structured, equitable AI curricula into Ghana’s nursing and midwifery training programs.
OBJECTIVES
To evaluate the knowledge of nursing students about Social Determinants of Health (SDH) at a public nursing school in Tunisia and identify associations with education, prior knowledge, socioeconomic status, and civic participation.
DESIGN
A Quantitative analytical cross-sectional study was conducted from January to March 2024.
SAMPLE
Out of 386 eligible nursing students, 241 participated (response rate: 62.4%), primarily female (sex ratio: 0.65) with a mean age of 20.28 years.
MEASUREMENTS
A structured electronic survey assessed participants' demographics, socioeconomic status, civic engagement, and knowledge of SDH through multiple-choice questions and a scoring system (0-20 points).
INTERVENTION
None.
RESULTS
The mean SDH knowledge score was 13.44/20, with gaps observed in understanding key structural factors such as political policies, profit motive, and housing conditions. Media and personal experiences correlated with higher scores (P = 0.001), while perceived curriculum inclusion and socioeconomic status had no significant effect. Most students found SDH content non-engaging or irrelevant to practice.
CONCLUSIONS
Knowledge deficits among nursing students highlight a need for curriculum reform. Strategies such as active learning, simulations, and integration of SDH into clinical rotations are recommended. Increased political engagement and advocacy training are essential for addressing systemic health inequities effectively.
Mouhamed Kammoun, F. Zaouali, Yasmine Sakly et al.· Public Health Nursing· 0 citations
Background: Generative Artificial Intelligence (GenAI) is increasingly integrated into nursing education, yet structured AI literacy training and ethical guidance remain limited. Consequently, nursing students often rely on informal learning, resulting in variability in AI readiness, confidence, and responsible use. Aims: This study was conducted to examine (1) whether AI literacy was positively associated with AI self-efficacy and AI attitudes and (2) whether AI self-efficacy mediated the relationship between AI literacy and AI attitudes. Methods: A cross-sectional survey using convenience sampling was conducted with 100 prelicensure nursing students in New York City. Data were collected using the AI Literacy Scale (AILS), AI Self-Efficacy Scale (AISES), and Generative AI Attitude Scale (GAIAS). Correlation and path analyses were performed using SPSS and Amos 30.0. Results: The participants had a mean age of 30.25 years, and 71% were women. AI literacy and AI self-efficacy were both positively associated with AI attitudes (all p < 0.001). Path analysis showed that AI literacy significantly predicted AI self-efficacy (β = 0.39, p < 0.001) and AI attitudes (β = 0.28, p = 0.003). AI self-efficacy significantly predicted AI attitudes (β = 0.31, p = 0.001) and partially mediated the relationship between AI literacy and AI attitudes. Conclusions: AI self-efficacy partially mediated the relationship between AI literacy and AI attitudes. Nursing curricula may benefit from structured AI education that integrates guided GenAI practice, case-based learning, and faculty feedback. Such educational frameworks warrant further empirical investigation regarding their potential to foster AI literacy, AI self-efficacy, and positive attitudes toward responsible AI integration, particularly through longitudinal studies assessing subsequent behavioral outcomes.
Shinhi Han, H. Kang, P. Gimber et al.· Nursing Reports· 0 citations
Background: Dementia is a growing public health challenge, and nurses require adequate knowledge to provide safe, person-centred care. Limited curricular coverage and restricted clinical exposure may leave nursing students insufficiently prepared.
Objective: To assess dementia-related knowledge among undergraduate and postgraduate nursing students at the University of Elbasan, Albania, and to examine whether knowledge differed by selected sociodemographic and educational characteristics.
Methods: A cross-sectional survey was conducted among 252 third-year Bachelor’s and Master’s nursing students. Knowledge was measured using the 21-item Dementia Knowledge Assessment Tool 2.0 (D-KAT2). Descriptive statistics and independent-samples t-tests were performed in IBM SPSS Statistics version 27.0.
Results: The mean D-KAT2 score was 13.94 ± 2.67 out of 21 (66.4% of the maximum). The lowest correct-response rates concerned sudden increases in confusion (25.4%), the effect of environmental changes (31.7%), and recognition of pain in advanced dementia (35.7%). Knowledge scores did not differ significantly by gender, residence, education level, or previous care experience (all p > 0.05).
Conclusion: Students demonstrated partial dementia knowledge, with important gaps in clinical recognition and care. Dedicated dementia modules, simulation-based learning, and structured clinical exposure should be strengthened within nursing curricula in Albania.
Ilma Toci, Gazmend Koduzi, Sabina Tosuni et al.· World Journal of Advanced Re...· 0 citations
Syrian pharmacy faculty demonstrate moderate CBL awareness and favorable adoption attitudes, particularly among younger and female faculty, and a fully validated CBL knowledge-and-attitudes scale is recommended.
Manal M. Yousef, Ziena Malek, M. Dashash· F1000Research· 0 citations
The findings highlight the need for a supportive educational environment with guidance to enable nursing students to use artificial intelligence appropriately and responsibly when needed, particularly among vocational college students and those from socioeconomically disadvantaged backgrounds.
Hui-Ying Fan, Qing Zhou, Lili Deng et al.· BMC Nursing· 0 citations
Overall, the CTBLQ demonstrated satisfactory psychometric properties and provides a standardized diagnostic instrument for identifying barriers to Team-Based Learning implementation and may support evidence-informed curriculum evaluation, educational planning, and future research in nursing education while contributing to the advancement of health workforce education through improved implementation of collaborative learning.
P. Kien, Leslie F. Lazaro· International Journal of Nur...· 0 citations