Evidence map›Paper›PMID 31244632›Full record

ArticleFrontiers in human neuroscience2019

Exploring the Neural Correlates in Adopting a Realistic View: A Neural Structural and Functional Connectivity Study With Female Nurses.

Yuichi Ogino, Hiroaki Kawamichi, Takahiro Kakeda, Shigeru Saito

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Yuichi OginoDepartment of Anesthesiology, Gunma University Graduate School of Medicine, Maebashi, Japan.
Hiroaki KawamichiGraduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan.
Takahiro KakedaDepartment of Nursing, Faculty of Nursing, Graduate School of Nursing, Kansai University of Social Welfare, Hyogo, Japan.
Shigeru SaitoDepartment of Anesthesiology, Gunma University Graduate School of Medicine, Maebashi, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Empathizing leads to positive and negative consequences. To avoid empathy-induced distress, adopting a realistic view (dealing with a situation practically and efficiently independent of one's emotional state) is important. We hypothesized that empathy-demanding professions (e.g., nursing) may require individuals to adopt a realistic view, which may demonstrate modulated neural structure and functional connectivity. We confirmed that female nurses showed a higher tendency, compared to controls, to adopt a realistic view, using the Fantasy subscale of the Interpersonal Reactivity Index (IRI; inverse scale of the realistic view). We then employed voxel-based morphometry (VBM) and resting-state functional magnetic resonance imaging (rs-fMRI) to explore the neural underpinnings related to realistic view adoption. Nurses exhibited significantly lower gray-matter volume (GMV) in the right striatum. In multiple regression analysis, only the Fantasy subscale score showed a significant positive correlation with GMV within the striatum cluster. Moreover, nurses exhibited lower functional connectivity between the right striatum and the right lateral prefrontal cortex (PFC), representing emotional regulation. These findings show that structural differences in the striatum correlated with the realistic view. Furthermore, lower functional connectivity between the striatum and lateral PFC suggests that nurses may use efficient coping strategies that may lessen the recruitment of effortful emotional regulation.

Indexed as

emotion-demanding professionnurserealistic viewresting state fMRIVBM

Identifiers

PMID31244632
PMCPMC6579875

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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.