ArticleNursing open2026
Compassion and Self-Compassion in Relation to Nursing Students' Attitudes Toward Artificial Intelligence.
Article in Nursing open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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Who cites it
1 citing paper in PubMed.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimTo examine the relationships between compassion, self-compassion and nursing students' attitudes toward artificial intelligence.
designA descriptive cross-sectional study.
methodsData were collected between April and December 2025 from undergraduate nursing students enrolled at a public university. A total of 377 students participated. Data were collected using a Personal Information Form, the Compassion Scale, the Self-Compassion Scale and the General Attitudes toward Artificial Intelligence Scale. Data were analysed using descriptive statistics, independent samples t-tests, ANOVA, Pearson correlation and PROCESS-based mediation analysis. The study was reported in accordance with STROBE guidelines.
resultsCompassion showed a small but statistically significant positive correlation with the positive attitudes subscale and a similarly small positive correlation with the reverse-scored negative attitudes subscale of the GAAIS. Because higher scores on the reverse-scored negative attitudes subscale indicate less negative and more accepting attitudes toward artificial intelligence, this finding suggests that higher compassion was associated with both more positive and less negative attitudes toward artificial intelligence. Both associations reflected a limited amount of shared variance.
conclusionsCompassion may influence how nursing students interpret and evaluate artificial intelligence, whereas self-compassion does not appear to have a direct role. These findings indicate that attitudes toward artificial intelligence in nursing education may not be explained solely by cognitive factors and highlight the relevance of affective characteristics. IMPLICATIONS FOR NURSING PRACTICE: Educational approaches that integrate technological competencies with attention to emotional, ethical and relational aspects of care may support the development of balanced and patient-centred perspectives on artificial intelligence. IMPACT: This study highlights the role of compassion as an affective factor shaping attitudes toward artificial intelligence among nursing students, contributing to a more comprehensive understanding of technology acceptance in nursing education. REPORTING
methodThe study adhered to the STROBE guidelines. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. The study involved nursing students only.
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