Evidence map›Paper›PMID 37039443›Full record

ArticleNursing open2023

Prevalence and associated factors of alexithymia in intensive care unit nurses.

Ruiling Nan, Li Ma, Hui Yan, Yabin Zhang, Juhong Pei, Haixia Chen, Xinglei Wang, Xinman Dou

Abstract read
In one paragraph

Article in Nursing open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

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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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

8 authors.

Ruiling NanDepartment of Critical Care Medicine, Lanzhou University Second Hospital, Lanzhou, China.
Li MaSchool of Nursing, Lanzhou University, Lanzhou, China.ORCID 0000-0001-8455-6708
Hui YanDepartment of Nursing, Lanzhou University Second Hospital, Lanzhou, China.
Yabin ZhangFirst Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Juhong PeiFirst school of clinical medicine, Lanzhou University, Lanzhou, China.
Haixia ChenDepartment of Surgical Oncology, Lanzhou University Second Hospital, Lanzhou, China.
Xinglei WangDepartment of Liver Disease branch, Lanzhou University Second Hospital, Lanzhou, China.
Xinman DouSchool of Nursing, Lanzhou University, Lanzhou, China.ORCID 0000-0001-5663-721X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThe aim of this study was to investigate the incidence of alexithymia in intensive care unit nurses and determine the associated factors.

designA multi-center, cross-sectional study.

methodsIn total, 485 nurses in intensive care unit were recruited from 53 hospitals in China. Data collection tools used in the study included demographic characteristics, the Social Support Rating Scale (SSRS), Emotional Intelligence Scale (EIS), and the 20-item Toronto Alexithymia Scale (TAS-20). SPSS 25.0 software (Corp., Armonk, NY, USA) was used to preform data analysis.

resultsAbout 43.7% of intensive care unit nurses were classified as alexithymia in the whole sample (males: 50%, females: 43%). The median TAS-20 score was 60 (interquartile range = 9). The study found that alexithymia was significantly associated with marital status, whether living alone, working years, and social support (Adjusted R Squared = 0.194, F = 6.466, p < 0.01), while emotional intelligence was not statistically significant with alexithymia.

conclusionsAlexithymia is a psychological problem with high incidence in intensive care unit nurses. In this study, being unmarried or divorced, living alone, and having fewer years of work (≤5 years) were associated with a higher risk of alexithymia. Interventions that strengthen social support may also help improve the mental health of ICU nurses.

Indexed as

Affective SymptomsNursesCross-Sectional StudiesEmotionsFemaleHumansMalePrevalencealexithymiaemotional intelligenceintensive care units nursessocial support

Identifiers

PMID37039443
PMCPMC10277406

What OpenQuestion holds

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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.