Evidence map›Paper›PMID 40597065›Full record

ArticleBMC nursing2025

The impact of an AI-focused ethics education program on nursing students' ethical awareness, moral sensitivity, attitudes, and generative AI adoption intention: a quasi-experimental study.

Mohammad Abuadas, Zainab Albikawi, Ahmad Rayani

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Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mohammad AbuadasNursing Faculty, Basic Nursing Department, Yarmouk University, Irbid, Jordan. mabuadas@yu.edu.jo.ORCID http://orcid.org/0000-0002-2739-7314
Zainab AlbikawiNursing Faculty, Clinical Nursing Department, Yarmouk University, Irbid, Jordan.ORCID http://orcid.org/0000-0002-9587-5242
Ahmad RayaniCommunity and Psychiatric Mental Health Nursing Department, College of Nursing, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe integration of Generative artificial intelligence (GAI) into healthcare is rapidly evolving, necessitating ethical preparedness among nursing students. GAI technologies present ethical challenges related to patient privacy, algorithmic bias, and informed consent, underscoring the need for structured AI ethics education in nursing curricula. This study aims to examine the impact of an ethics education program on nursing students' AI ethical awareness, moral sensitivity, attitudes, and intentions to use GAI in healthcare.

methodsA quasi experimental, pretest‒posttest study was conducted with 115 nursing students. The participants were randomly assigned to an intervention group (n = 57), which received a structured AI ethics education program, or a control group (n = 58), which did not receive the intervention. The validated scales measured AI ethical awareness, moral sensitivity, attitudes, and the intention to use AI before and after the intervention.

resultsCompared with the control group, the intervention group demonstrated a significant increase in AI ethical awareness (M = 57.28, SD = 22.28) (M = 47.43, SD = 24.04; p = .025, η² = 0.044). Moral sensitivity also showed a notable improvement in the intervention group (M = 74.33, SD = 29.93) compared with the control group (M = 60.26, SD = 22.52; p = .005, η² = 0.067). Compared with the control group, positive attitudes toward AI significantly increased postintervention (M = 39.46, SD = 11.51) (M = 23.21, SD = 11.72; p < .001, η² = 0.332), indicating a strong effect of ethics education. Furthermore, the intention to use AI technology improved significantly in the intervention group (M = 12.46, SD = 3.55) compared with the control group (M = 10.24, SD = 3.15; p = .001, η² = 0.099). However, negative attitudes toward GAI did not significantly change postintervention.

conclusionThis study highlights the effectiveness of structured AI ethics education in enhancing ethical competencies among nursing students. Integrating such programs into nursing curricula is essential to prepare future nurses for ethical decision-making in AI-driven healthcare. These findings support the development of standardized ethics training modules to guide responsible AI use in clinical practice and inform future curriculum design. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

AI attitudesArtificial intelligenceEthical awarenessEthics educationHealthcare technologyMoral sensitivityNursing students

Identifiers

PMID40597065
PMCPMC12211453

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.