Evidence map›Paper›PMID 39015329›Full record

ArticleFrontiers in psychology2024

Current status and needs of in-service training for psychiatric nurses in 24 provinces of China: a cross-sectional survey.

Xiaolin Tan, Minghao Pan, Zhiying Wan, Ying Yang, Lijuan Zhang, Yu Fang, Xiaofen Li, Meiyu Shen

Abstract read
In one paragraph

Article in Frontiers in psychology, 2024. 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

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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Xiaolin Tan *Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China.
Minghao Pan *Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China.
Zhiying WanDepartment of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China.
Ying YangRehabilitation Business Department of the Second Hospital of Huangshi City, Huangshi City, China.
Lijuan ZhangObstetrics and Gynecology Department of Huangshi Second Hospital, Huangshi City, China.
Yu FangDepartment of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China.
Xiaofen LiDepartment of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China.
Meiyu ShenDepartment of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: To investigate the current situation and need for post-competence training for psychiatric nurses in China and provide a reference for the development of training programs for psychiatric nurses. Design: A cross-sectional design. Methods: A cross-sectional study was conducted from August to October 2023 with 435 psychiatric nurses from 34 hospitals in 24 provinces of mainland China. A self-administered questionnaire was used for data collection. Descriptive statistics, non-parametric tests, and chi-square tests were used for data analysis. Results: The training content for psychiatric nurses is extensive, and the training load is large. Psychiatric nurses have high training demands for first aid knowledge, emergency handling ability, and anti-riot skills. Nurses with different years of experience have different training needs. The training needs of psychiatric nurses in specialized and general hospitals also different. Conclusion: The training status of psychiatric nurses is not consistent with the demand. Managers should combine this with psychiatric nurses' own work needs to develop practical and effective training programs.

Indexed as

Chinacross-sectional surveyin-service trainingneedspsychiatric nurses

Identifiers

PMID39015329
PMCPMC11249737

What OpenQuestion holds

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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.