Evidence map›Paper›PMID 39319050›Full record

ArticleJournal of multidisciplinary healthcare2024

Construction and Evaluation of a Predictive Model for Grassroots Nurses' Risk Perception of "Internet + Nursing Services": A Multicenter Cross-Sectional Study.

Peiran Guo, Yuting Tan, Li Feng, Cui Liu, Jin Sun, Rong Cheng, Yanling Xiao, Xingxin Zhan, Lingjie Yang, Zhixia Zhang

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
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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

10 authors.

Peiran Guo *Tianyou Hospital, Wuhan University of Science and Technology, Wuhan, Hubei, People's Republic of China.ORCID 0009-0001-1954-9576
Yuting Tan *Tianyou Hospital, Wuhan University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Li FengSchool of Public Health and Nursing, Hubei University of Science and Technology, Xianning, Hubei, People's Republic of China.
Cui LiuGeriatric Hospital Affiliated with Wuhan University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Jin SunYiling Hospital of Yichang City, Yichang, Hubei, People's Republic of China.
Rong ChengTianyou Hospital, Wuhan University of Science and Technology, Wuhan, Hubei, People's Republic of China.ORCID 0009-0000-3613-6020
Yanling XiaoTianyou Hospital, Wuhan University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Xingxin ZhanSchool of Public Health, Xinyu University, Xinyu, Jiangxi, People's Republic of China.
Lingjie YangTianyou Hospital, Wuhan University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Zhixia ZhangTianyou Hospital, Wuhan University of Science and Technology, Wuhan, Hubei, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The development of "Internet + nursing services" can effectively solve the problem of population aging, and grassroots nurses are the primary providers of such services in rural areas. This study aimed to analyze the factors affecting grassroots nurses' risk perception of "Internet + nursing services" and construct a predictive model. Patients and Methods: A multicenter cross-sectional study of 2220 nurses from 27 secondary hospitals and 36 community health centers in Hubei Province was conducted from August to December 2023 using a multi-stage cluster sampling method. Information was collected through a structured anonymous questionnaire. A Chi-square test, a Welch Results: A total of 2050 valid questionnaires were collected, demonstrating that 51.95% of grassroots nurses thought that "Internet + nursing services" was a medium-high risk. Age, other sources of income, knowledge about "Internet + nursing services", personal safety, physical function, occupational exposure, social psychosocial, and time risk ( Conclusion: The prediction model constructed in this study has good prediction ability. Most grassroots nurses believe that "Internet + nursing services" are risky and influenced by several factors. It is suggested that the government and hospitals should formulate a unified charging standard, improve the safety guarantee, and gradually eliminate the concerns of grassroots nurses.

Indexed as

grassroots nurseInternet + nursing servicespredictive modelrisk perception

Identifiers

PMID39319050
PMCPMC11420900

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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.