Evidence map›Paper›PMID 36180902›Full record

ArticleBMC nursing2022

Influence of AI ethics awareness, attitude, anxiety, and self-efficacy on nursing students' behavioral intentions.

Yeunhee Kwak, Jung-Won Ahn, Yon Hee Seo

Abstract read
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In one paragraph

Article in BMC nursing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed, 4 pooled it
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

71 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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11 more citing papers are in PubMed but not listed here.

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.

Yeunhee KwakRed Cross College of Nursing, Chung-Ang University, 84, Heukseok-ro, Dongjak-gu, 06974, Seoul, Korea.ORCID http://orcid.org/0000-0002-9884-0635
Jung-Won AhnDepartment of Nursing, Gangneung-Wonju National University, 150, Namwon-ro, Heungeop-myeon, 26403, Wonju-si, Gangwon-do, Korea.ORCID http://orcid.org/0000-0001-5389-3189
Yon Hee SeoDepartment of Nursing, Yeoju Institute of Technology, 338, Sejong-ro, 12652, Yeoju-si, Gyeonggi-do, Korea. yseo017@naver.com.ORCID http://orcid.org/0000-0002-1344-3607

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) technology has recently seen rapid advancement, with an expanding role and scope in nursing education and healthcare. This study identifies the influence of AI ethics awareness, attitude toward AI, anxiety, and self-efficacy on nursing students' behavioral intentions to use AI-based healthcare technology.

methodsThe participants included 189 nursing students in Gyeonggi-do, with data collected from November to December 2021 using self-reported questionnaires. We analyzed the data using the SPSS/WIN 26.0 program, including a t-test, Pearson's correlation coefficient, and hierarchical multiple linear regression.

resultsThe results revealed that AI ethical awareness (t = - 4.32, p < .001), positive attitude toward AI (t = - 2.60, p = .010), and self-efficacy (t = - 2.65, p = .009) scores of the third and fourth-year nursing students were higher, while their anxiety scores were lower (t = 2.30, p = .022) compared to the scores of the first and second-year nursing students. The factors influencing behavioral intention included a positive attitude toward AI (β = 0.58) and self-efficacy (β = 0.22). The adjusted R

conclusionIt is necessary to inculcate a positive attitude toward AI and self-efficacy by providing educational programs on AI-based technology in healthcare settings.

Indexed as

AI ethics awarenessAnxietyAttitude toward AIBehavioral intentionSelf-efficacy

Identifiers

PMID36180902
PMCPMC9526272

What OpenQuestion holds

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LicenceCC BY
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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.