Evidence map›Paper›PMID 41402860›Full record

ArticleBMC nursing2025

Categorizing missed nursing care to effectively investigate its influencing factors among pediatric nurses: a regional cross-sectional survey.

Shuai Xie, Mengqin Dai, Miyan Wang, Feng Yin, Fan Wang, Yan Zhu, Yun Qiu, Xiaohong Chen, Yuwei Yang

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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

9 authors.

Shuai Xie *Pediatric Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, P. R. China.
Mengqin Dai *Pediatric Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, P. R. China.
Miyan WangDepartment of Pediatric Surgery, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, P. R. China.
Feng YinPediatric Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, P. R. China.
Fan WangPediatric Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, P. R. China.
Yan ZhuPediatric Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, P. R. China.
Yun QiuPediatric Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, P. R. China. 1606585803@qq.com.
Xiaohong ChenDepartment of Laboratory Medicine, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, P. R. China. xiaohongch@aliyun.com.
Yuwei YangDepartment of Laboratory Medicine, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, P. R. China. yyw318@sc-mch.cn.

Funding

Mianyang Central Hospital, University of Electronic Science and Technology of China MR-51-25-037671
6 · The paper itself

Abstract

background and purposeMissed nursing care (MNC) are omissions that compromise patient care quality and are harder to detect than errors, posing greater risks to patient safety. However, current scales lack a cohesive framework, limiting the modelled association analysis between MNCs and self-reported causes. This study aims to classify MNCs, explore their relationships with self-reported causes, and examine the influence of sociodemographic factors among pediatric nurses.

methodsA total of 459 pediatric nurses from 24 hospitals completed the Chinese-translated MISSCARE Survey-Ped. Exploratory factor analysis classified the MNCs, whose path analysis was subsequently performed based on self-reported causes. Sociodemographic factors were then analyzed to identify independent predictors across MNC quartile groups.

resultsThe occurrence of pediatric MNCs was 67.7%, and the causes related to labor resources, material resources, and communication were reported at rates of 86.6%, 70.5%, and 72.0% respectively. Parallel analysis suggested a two-factor solution, which was subsequently extracted via EFA, classifying 28 MNCs into two distinct clusters in the Rotated Factor Space plot based on loadings > 0.4, characterized as Timely and Behavioral MNCs, respectively. Based on the two principal categories, a satisfactory path model was developed (CFI = 0.997, TLI = 0.979, RMSEA = 0.058, SRMR = 0.062). In this model, self-reported causes showed a positive overall effect on MNCs (Standardized-beta[95%CI] = 0.201[0.091, 0.311], P < 0.001). Negative effects were observed in path of labor resources → material resources (Standardized-beta[95%CI]=-0.578[-0.386, -0.770], P < 0.001), communication → labor resources (Standardized-beta[95%CI]=-0.120[-0.046, -0.194], P < 0.001), and communication → material resources (Standardized-beta[95%CI]=-0.856[-0.827, -0.885], P < 0.001). Additionally, Timely and Behavioral MNCs exhibited opposing mutual effects (Standardized-beta[95%CI]=-0.361[-0.216, -0.506] and 0.807[0.787, 0.827], both P < 0.001). Multivariate logistic regression revealed that factors such as communication, labor and material resources, position, education, fertility status, and hospital grade were independently linked to mild to severe MNC groups, with some showing negative correlations (OR = 0.433 ~ 0.525, all P < 0.05), and others positive correlations (OR = 1.068 ~ 1.799, all P < 0.05).

conclusionsThis study proposes a classification that divides MNCs into two categories, quantifies the modelled associations between MNCs and self-reported causes, and identifies independent factors that influence MNCs, offering evidence for effective interventions. IMPLICATIONS FOR NURSING MANAGEMENT: Our innovative category of MNC behaviors supports path analysis and reveals the underlying modelled associations between MNCs and self-reported causes. As MNC severity increases, influencing factors follow a progression: individual factors → resource constraints → communication failure, offering insights for effective interventions.

trial registrationNational Universal Health Security Information Platform of National Health Commission (Registration No.: MR-51-25-037671, Date: Feb. 24, 2025).

Indexed as

CategoryCauseIndependent factorMissed nursing carePediatricsStructural modeling

Identifiers

PMID41402860
PMCPMC12822166

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LicenceCC BY-NC-ND
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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.