Evidence map›Paper›PMID 37501062›Full record

ArticleBMC nursing2023

Analysis of the information ability of nurses in county hospitals in northern Henan province: a survey.

Xizheng Li, Guirui Ma, Kuihong Qiao, Yuwen Yan, Huizhong Zhang, Yan Zhang

Abstract read
In one paragraph

Article in BMC nursing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Xizheng LiDepartment of Nursing, School of Nursing and Health, Zhengzhou University, No. 101, Science Avenue, Zhengzhou City, 450001, Henan Province, China.
Guirui MaDepartment of Nursing, School of Nursing and Health, Zhengzhou University, No. 101, Science Avenue, Zhengzhou City, 450001, Henan Province, China.
Kuihong QiaoDepartment of Nursing, The People's Hospital of Qi xian, Hebi, China.
Yuwen YanDepartment of Nursing, The People's Hospital of Xun xian, Hebi, China.
Huizhong ZhangDepartment of Nursing, School of Nursing and Health, Zhengzhou University, No. 101, Science Avenue, Zhengzhou City, 450001, Henan Province, China.
Yan ZhangDepartment of Nursing, School of Nursing and Health, Zhengzhou University, No. 101, Science Avenue, Zhengzhou City, 450001, Henan Province, China. zhangy32an@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the status quo of nursing information ability of nurses in county-level hospitals and analyze its influencing factors.

methodsIn June 2022, a total of 303 on-the-job clinical nurses from 3 county-level hospitals in Hebi City, Henan Province were selected as subjects by convenience sampling method. General data questionnaire and self-rating nursing information ability scale were used to investigate them.

resultsThe total score of nursing information ability of 303 nurses in county hospitals of Hebi City, Henan Province was (77.72 ± 18.76). There were statistically significant differences in the scores of nursing information ability among different ages, working years, positions, education, marriage, monthly income, whether they had learned computer-related knowledge and skills, and whether they had participated in the learning or training of nursing information system (all p < 0.05).Multiple linear regression analysis showed that age, years, position, monthly income and whether they had learned computer-related knowledge and skills were the main influencing factors of nursing information ability of county-level nurses (all p < 0.05).

conclusionsThe nursing information ability of nurses in county-level hospitals in northern Henan is at a medium level. The government or society should provide training and guidance on nursing information ability, so as to provide more opportunities for nurses in county-level hospitals to participate in and learn nursing information technology to improve their ability.

Indexed as

County hospitalInformation capabilityNursing

Identifiers

PMID37501062
PMCPMC10375611

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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.