Evidence map›Paper›PMID 41702684›Full record

ArticleNursing & health sciences2026

Feelings and Experiences of Return-to-Work Among Nurses Occupationally Infected With COVID-19 During the Late Phase of the Pandemic in Japan.

Noriko Shinkai, Kayoko Ohnishi, Hisako Yano

Abstract read
In one paragraph

Article in Nursing & health sciences, 2026. 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

3 authors.

Noriko ShinkaiDepartment of Nursing, Faculty of Health Sciences, Aomori University of Health and Welfare, Aomori, Japan.ORCID https://orcid.org/0009-0001-6497-0466
Kayoko OhnishiGraduate School of Nursing, Nagoya City University, Nagoya, Japan.ORCID https://orcid.org/0000-0002-6762-4788
Hisako YanoGraduate School of Nursing, Aichi Medical University, Nagakute, Japan.ORCID https://orcid.org/0009-0005-3584-8073

Funding

Japan Society for the Promotion of Science (JSPS) KAKENHI 22K17441
6 · The paper itself

Abstract

This study explored the feelings of nurses occupationally infected with COVID-19 during the late pandemic phase in Japan, from diagnosis to return to work, to provide suggestions for safe and continuous employment. Semi-structured interviews were conducted among 11 nurses infected during the late phase of the pandemic (August 2022 to February 2023). The data were analyzed using a qualitative inductive approach. At diagnosis, nurses experienced shock and a strong sense of guilt and self-blame arising from the feeling of being blamed by others. Negative emotions during the infection period influenced postreturn feelings, leading to distrust stemming from insufficient infection control measures and a desire to leave their workplace. Conversely, gratitude for the support from managers and colleagues during the recuperation period fostered their determination to return. Furthermore, a sense of achievement, such as improved nursing expertise and reaffirmation of professional values, facilitated a positive transformation of the infection experience, supporting work motivation. These findings suggest that managers and colleagues recognize the importance of alleviating nurses' self-blame, improving environments, and organizational support, enabling nurses to maintain achievement by reframing their experiences positively.

Indexed as

COVID-19EmotionsNursesReturn to WorkAdultFemaleFrontline WorkersHumansJapanMaleMiddle AgedPandemicsQualitative ResearchSARS-CoV-2WorkplaceCOVID‐19feelingsinterviewlate phase of the pandemicnursesoccupational infectionqualitative study

Identifiers

PMID41702684
PMCPMC12912892

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.