Evidence map›Paper›PMID 38854459›Full record

ArticleGerontology & geriatric medicine

Working Experiences of Care Aides in Long-Term Care Institutions Following the Relaxation of COVID-19 Regulations in Taiwan: A Qualitative Study.

Hui-Chun Huang, Chen-Yuan Hsu, Chen-I Shih, Hsiu-Chen Huang, Hui-Fei Yang, Sheng-Yu Fan

Abstract read
In one paragraph

Article in Gerontology & geriatric medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Hui-Chun HuangPau-Kan Social Welfare and Charitable Foundation, Chia-Yi, Taiwan.
Chen-Yuan HsuDa-Yeh University, Changhua, Taiwan.
Chen-I ShihDitmanson Medical Foundation Chia-Yi Christian Hospital, Chia-Yi, Taiwan.
Hsiu-Chen HuangDitmanson Medical Foundation Chia-Yi Christian Hospital, Chia-Yi, Taiwan.
Hui-Fei YangDitmanson Medical Foundation Chia-Yi Christian Hospital, Chia-Yi, Taiwan.
Sheng-Yu FanNational Cheng Kung University, Tainan, Taiwan.ORCID https://orcid.org/0000-0001-7932-2405

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Care aides in long-term care (LTC) institutions care for older disabled residents at high risk for COVID-19. However, they experienced many stressors during the COVID-19 pandemic. This study aims to explore the working experiences of care aides in LTC institutions following the relaxation of COVID-19 regulations in Taiwan. This qualitative descriptive study included 20 care aides who had cared for residents with COVID-19. Data were obtained via semi-structured interviews. Caring for residents with COVID-19 and the difficulties, resources and teamwork, and impact of care aides' work on their lives were discussed. Consequently, four themes were identified. First, difficulties in care, which included physical limitations by protection, workload, and impact of work schedule on the lives of the care aides. Second, psychological impact, such as worry, social isolation, and burnout. Third, interpersonal relationships with supervisors, colleagues, residents, and their families. Fourth, infection control policy from the institution and government. When infection control policies were relaxed, care aides had difficulties in caring for residents; furthermore, their family and social lives were also affected. They were required to learn knowledge of and skills for COVID-19 management. Institutions were required to provide support in materials, care processes, environment, and management.

Indexed as

care aidsCOVID-19long-term carenursing home

Identifiers

PMID38854459
PMCPMC11159543

What OpenQuestion holds

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LicenceCC BY-NC
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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.