Aug 2026· Journal of Educational Evaluation for Health Professions· Vol 23, pp.
22
· 0 citations
Medicine
TL;DR
The TAILS-NS provides evidence of validity and reliability for measuring AI literacy among Thai nursing students and may serve as a standardized tool for curriculum evaluation.
Abstract
Purpose
This study aimed to develop and validate the Thai AI Literacy Scale for Nursing Students (TAILS-NS).
Methods
A cross-sectional study was conducted across multiple nursing institutions in Thailand from March to May 2026 to address the absence of a validated artificial intelligence (AI) literacy instrument for nursing students in Thai or Southeast Asian contexts. A total of 410 nursing students participated, yielding a response rate of 94.5%. The TAILS-NS was developed through item generation, expert content-validity assessment using the item-objective congruence index, and a 2-phase pilot study, resulting in a 40-item instrument comprising a 15-item knowledge test and 25 Likert-scale items across 6 domains. Exploratory factor analysis using maximum likelihood estimation and confirmatory factor analysis using the weighted least squares mean and variance-adjusted estimator, as well as internal consistency, convergent validity, and discriminant validity, were assessed. An independent validation sample (n=157) was recruited for cross-validation confirmatory factor analysis. Raw data are available as a supplement.
Results
Exploratory factor analysis supported a 6-factor structure: AI awareness, skills, ethics and professionalism, positive attitude, AI anxiety, and readiness. Confirmatory factor analysis showed acceptable model fit, although the root mean square error of approximation (RMSEA) indicated marginal fit (comparative fit index [CFI]=0.919, Tucker-Lewis index [TLI]=0.906, RMSEA=0.090). Reliability of the knowledge subscale was acceptable (Kuder-Richardson Formula 20=0.758). Internal consistency was excellent (α=0.810-0.934; total α=0.974; ω=0.989). Average variance extracted exceeded 0.50 for all factors, supporting convergent validity. Most heterotrait-monotrait ratios were below 0.90, supporting discriminant validity. Cross-validation confirmed factorial replicability (CFI=0.917, TLI=0.904).
Conclusion
The TAILS-NS provides evidence of validity and reliability for measuring AI literacy among Thai nursing students and may serve as a standardized tool for curriculum evaluation. Future studies should expand the AI anxiety subscale and explore cross-cultural applicability in Southeast Asian nursing contexts.
The K-MAIRS can be a valid and reliable instrument for assessing artificial intelligence readiness among Korean nursing students and supports global initiatives to incorporate artificial intelligence competencies into nursing education using culturally tailored assessment tools.
Minjae Lee, Nayeon Yi, Seunghyeon Lee et al.· Nursing and Health Sciences· 0 citations
Initial evidence is provided that the NAIRS is a valid and reliable instrument for assessing nursing students' readiness for artificial intelligence across knowledge/awareness, willingness to use AI, self-efficacy, and ethical awareness domains and may be useful for educational needs assessment and curriculum planning in nursing education.
Sumeyye Akçoban, Gülay Koca, S. Berşe· BMC Nursing· 0 citations
Aims To translate, revise and evaluate the Chinese‐version Nursing Leaders’ Readiness for Artificial Intelligence Scale and assess Chinese nursing leaders’ AI readiness. Design Cross‐sectional survey. Methods The research team conducted translation, cognitive interviews, a pilot survey and psychometric evaluation. Survey participants were 762 nursing managers. The reliability and validity of the Chinese‐version scale were examined. The status and influencing factors of AI readiness among Chinese nursing managers were investigated. Results The translated scale comprises 20 items. Cronbach’s α was 0.824. Regarding validity, the three‐factor model demonstrated a good fit. The square roots of the average variance extracted, absolute values of correlation coefficients among dimensions and content validity index values were acceptable. The mean AI readiness score was 65.27 ± 9.78. Of the participants, 624 scored above 60 points, 136 scored 40–60 points and 2 scored below 40 points. Scores differed significantly by hospital type, hospital level, department, training participation, prior AI tool or system use and frequency of AI usage. Conclusion The Chinese‐version scale demonstrated good reliability and validity and can effectively assess AI readiness among Chinese nursing managers. Nursing leaders generally demonstrated a favourable level of AI readiness; however, factors such as hospital type and level remain significant determinants influencing nursing leaders’ AI readiness. Implications for Nursing Management This study provides a standard measurement tool for Chinese hospitals to check how ready their nursing managers are for AI. These findings help us understand the current state of AI readiness among nursing managers in China. The results can help improve AI use strategies. In addition, they can help bring AI into nursing practice more smoothly. This study has important value for moving forward with digital change and smart nursing in China.
Hui Yang, Yuanzhi Guo, Yaxin Qiao et al.· Journal of Nursing Managemen...· 0 citations
Aim: This study was conducted to examine the psychometric properties of the Turkish version of the Nursing Practice Readiness Scale (NPRS).Design: The present research was designed as a methodological study. Data collection was carried out between February and May 2023, from a total of 225 participants, including 85 newly graduated nurses and 140 fourth-year nursing students.Methods: During the cultural adaptation process of the scale, forward translation was performed by three independent translators, the Turkish version was developed based on expert opinions, language equivalence was evaluated through back-translation, and a pilot study was conducted. Data were collected using a Descriptive Information Form, the NPRS, and the Work Readiness Scale for Graduate Nurses (WRS-GN). The scale’s language, content, and construct validity were assessed, while reliability was evaluated using Cronbach’s alpha coefficient, item-total score correlations, and parallel-form reliability. Data were analyzed using descriptive statistics, Pearson correlation analysis, and confirmatory factor analysis.Results: The content validity index of the scale was found to be 0.90. Items 33 and 35 were excluded due to low factor loading (0.579) and high residual covariance (5.775), respectively. After item removal, confirmatory factor analysis indicated acceptable model fit. The overall Cronbach’s alpha coefficient was calculated as 0.96, and item-total correlation coefficients ranged from 0.56 to 0.77. A statistically significant positive relationship was observed between NPRS and WRS-GN scores (r=0.739;p<0.001).Conclusions: The findings indicate that the 33-item Turkish version of the NPRS is a valid and reliable instrument for assessing the readiness of newly graduated nurses for clinical practice.
Aim To develop and psychometrically validate an instrument to assess the competencies (knowledge, skills, and attitudes) of nurses and nursing students regarding the effects of climate change on the health of older people. Methods Cross‐sectional descriptive study of questionnaire construction and validation developed in four phases: creation and elaboration of the initial items, content validation by an expert panel, pilot test, and psychometric validation. A tool was developed consisting of a knowledge questionnaire, a skills scale, and an attitude scale. Data were collected from a convenience sample of 708 individuals (210 nurses and 498 nursing students) between January and April 2024. Content validation was carried out by consulting a panel of 13 experts and a pilot test. Psychometric validation was carried out using Item Response Theory, specifically the Rasch model for the knowledge questionnaire and Andrich’s rating scale model for the skills and attitude scales. The STROBE checklist for cross‐sectional studies was followed. Results Reliability for the set of items and for individuals was excellent (0.99 and 0.90, respectively). Item separation index was above 2 in all three parts of the instrument, although somewhat more limited for people. Internal consistency was acceptable in the knowledge questionnaire (11 items, Cronbach’s α 0.68) and excellent in the skills (13 items, Cronbach’s α 0.91) and attitudes (11 items, Cronbach’s α 0.93) scales. Conclusion Nursing Competencies Questionnaire on Older People’s Environmental Health is a useful and reliable instrument for measuring knowledge, skills, and attitudes in nurses and nursing students.
E. M. Montoro-Ramírez, Laura Parra-Anguita, Carmen Álvarez-Nieto et al.· Nursing Research and Practic...· 0 citations
The Turkish version of the FtAIS is a valid and reliable instrument for assessing fear of AI among nursing students and demonstrates acceptable content and construct validity and good internal consistency.
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