Evidence map›Paper›PMID 41382269›Full record

ArticleBMC nursing2025

Evaluation of the Chinese version of the attitude of people toward male nurses questionnaire.

Wenbo Li, Yuying Fan, Guangming Chang, Qingfang Ye, Qiujie Li

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. 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

5 authors.

Wenbo LiThe Second Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
Yuying FanDepartment of Nursing, Harbin Medical University, Harbin, 150001, China.
Guangming ChangThe Second Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
Qingfang YeDepartment of Nursing, Harbin Medical University, Harbin, 150001, China.
Qiujie LiThe Second Affiliated Hospital of Harbin Medical University, Harbin, 150001, China. liqiujie1949@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe nursing profession in China is predominantly female, with male nurses significantly underrepresented. Societal attitudes and stereotypes contribute to this gender disparity. A reliable instrument to measure public attitudes toward male nurses in China is crucial for addressing these issues.

methodsThis methodological study validated the Chinese version of the Attitude of People Toward Male Nurses Questionnaire (AMnQ) using a cross-sectional design conducted among 480 Chinese adults from both urban and rural areas. To enhance the generalizability of the findings and capture broader societal attitudes, the sample included both healthcare and non-healthcare participants. The original AMnQ was translated into Chinese following standardized forward–backward translation procedures. Psychometric assessment covered internal consistency, split-half reliability, test–retest reliability, expert review, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA).

resultsThe Chinese version of the AMnQ demonstrated strong internal consistency (Cronbach’s α = 0.823) and reliability (split-half = 0.904; test-retest = 0.747). Content validity was robust, with an S-CVI of 0.981. EFA revealed a three-factor structure, which was further validated by CFA, showing acceptable model fit indices.

conclusionThe Chinese AMnQ is a reliable and valid tool for assessing public attitudes toward male nurses in China. This instrument can guide interventions aimed at reducing gender bias and fostering diversity within the nursing profession. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

AttitudeMaleNursePsychometric propertiesReliability and validity

Identifiers

PMID41382269
PMCPMC12801637

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.