Evidence map›Paper›PMID 35614503›Full record

ArticleBMC nursing2022

The resilience of nursing staffs in nursing homes: concept development applying a hybrid model.

Sung Ok Chang, Eun Young Kim

Abstract read
In one paragraph

Article in BMC nursing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Trial
  2. Development and Validation of a Resilience Scale for Nursing Home Staff.International journal of older people nursing · 2026
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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

2 authors.

Sung Ok ChangCollege of Nursing and BK21 FOUR R&E Center for Learning Health Systems, Korea University, Seoul, Republic of Korea.
Eun Young KimCollege of Nursing, Korea University, 145, Anam-ro, Seongbuk-gu, 02841, Seoul, Republic of Korea. magic0614@korea.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe resilience of nursing home (NH) nursing staff is emphasized to improve the quality of care provided, but the concept has not been clearly defined. By composing such a definition through concept development, a basis for active research in the future can be established.

aimTo identify the definition and conceptual characteristics of the concept of resilience of NH nursing staffs.

methodIn this study, the concept was developed using Schwartz-Barcott and Kim's hybrid model, which included theoretical, fieldwork, and final analysis stages. In the theoretical stage, a literature review on the definition and measurement of concepts was performed. For the fieldwork stage, 22 interviews were conducted with 7 participants, and a content analysis was performed. During the final analysis stage, the results of the theoretical and field work stages were integrated.

resultsThree dimensions, eight attributes, and three types were identified. The three dimensions are internal resources, external support, and positive coping with situations as they arise; the eight attributes are optimism, patience, mindfulness, supportive relationships, available resources, work-life boundary setting, self-development, and growth; and the three types are those who want to adapt themselves to the situation, those who actively seek to cope with stressful situations, and those who hold positive expectations for the future.

conclusionCoping with difficult situations using internal resources and external support was a unique trait revealed in the resilience of NH nursing staff members. This study provided future research directions to improve the resilience of NH nursing staffs by revealing the characteristics of their resilience.

Indexed as

Nursing homesNursing staffQualitative researchResilience, psychological

Identifiers

PMID35614503
PMCPMC9132673

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LicenceCC BY
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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.