Evidence map›Paper›PMID 40598528›Full record

ArticleBMC nursing2025

Factors associated with patient privacy concerns in AI-based health monitoring devices among nursing students: a cross-sectional study.

Yang Yang, Hui Wang, Kunshuo Du, Xue Wang, Jiukai Zhao, Dong Han, Yu Yang, Shuang Zang

Abstract read
In one paragraph

Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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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

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No citing paper in PubMed yet.

4 · The record

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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

8 authors.

Yang Yang *Department of Community Nursing, School of Nursing, China Medical University, No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, 110122, China.ORCID https://orcid.org/0009-0003-8685-0275
Hui Wang *School of Nursing, Peking University, 38 Xueyuan Road, Beijing, Haidian District, 110122, China.ORCID https://orcid.org/0000-0003-2134-581X
Kunshuo DuDepartment of Community Nursing, School of Nursing, China Medical University, No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, 110122, China.ORCID https://orcid.org/0009-0005-4259-3697
Xue WangDepartment of Community Nursing, School of Nursing, China Medical University, No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, 110122, China.ORCID https://orcid.org/0000-0002-0371-4004
Jiukai ZhaoDepartment of Community Nursing, School of Nursing, China Medical University, No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, 110122, China.ORCID https://orcid.org/0009-0000-7286-0155
Dong HanSchool of Information Science and Technology, Northeast Normal University, No.2555 Jingyue Street, Changchun, Jilin Province, 130000, China. handong@nenu.edu.cn.ORCID https://orcid.org/0009-0004-2280-308X
Yu YangDepartment of Vascular Surgery, The First Hospital of China Medical University, No.155 Nanjing Bei Street, Heping District, Shenyang, Liaoning Province, 110001, China. xgjzxyy@163.com.ORCID https://orcid.org/0000-0003-2383-1520
Shuang ZangDepartment of Community Nursing, School of Nursing, China Medical University, No.77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province, 110122, China. zangshuang@cmu.edu.cn.ORCID https://orcid.org/0000-0001-7814-8011

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe rapid integration of artificial intelligence (AI) into healthcare has raised important patient privacy concerns, particularly regarding AI-based health monitoring devices. As future healthcare professionals, nursing students will play a critical role in adopting and implementing AI-based health monitoring devices.

objectiveThis study aims to evaluate the level of patient privacy concerns in AI-based health monitoring devices among nursing students and analyze the associated factors.

methodsA group of 967 nursing students was extracted from the 2023 Chinese Population Psychology and Behavior Survey (PBICR). The multivariate generalized linear model analysis was used to evaluate the associated factors of the level of patient privacy concerns in AI-based health monitoring devices among nursing students.

resultThe mean score of nursing students' level of patient privacy concerns in AI-based health monitoring devices was 69.00 (50.00,88.00) (range 0-100). Family health [Tertile 2: 35 ~ 39 (β = 0.03), Tertile 3: 40 ~ 50 (β = 0.03)], anxiety symptoms [Tertile 2: 2 ~ 7 (β = 0.07), Tertile 3: 8 ~ 21 (β = 0.10)], resilience [Tertile 2: 4 ~ 6 (β = 0.02), Tertile 3: 7 ~ 8 (β = 0.10)], and with no sibling (β=-0.02) were associated with patient privacy concerns in AI-based health monitoring devices among nursing students.

conclusionThe results of the study indicate that nursing students have certain concerns about AI-based health monitoring devices. The study emphasizes the need for targeted educational programs to mitigate patient privacy concerns and enhance the acceptance of AI-based health monitoring devices in nursing education based on their associated factors. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Artificial intelligenceCross-sectional studyHealth monitoring devicesNursing ethicsNursing students

Identifiers

PMID40598528
PMCPMC12210904

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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.