Evidence map›Paper›PMID 39337240›Full record

ArticleHealthcare (Basel, Switzerland)2024

Psychological Wellbeing and Life Satisfaction among Chinese Older Immigrants in Canada across the Early and Late Stages of the COVID-19 Pandemic.

Lixia Yang, Andrea D Y Lee, Linying Dong

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

3 authors.

Lixia YangDepartment of Psychology, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada.ORCID 0000-0003-2938-8363
Andrea D Y LeeDepartment of Psychology, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada.
Linying DongTed Rogers School of Information Technology Management, Toronto Metropolitan University, Toronto, ON M5G 2C3, Canada.ORCID 0000-0002-0776-7410

Funding

RBC Immigrant, Diversity, and Inclusion Project (Partnership for Change)SSHRC Explore Grant from the Office of the Vice-president, Research and Innovation (OVPRI), Toronto Metropolitan UniversitySSHRC PEG 892-2022-3086
6 · The paper itself

Abstract

objectivesThis study compared the psychological wellbeing, life satisfaction, and perceived social support in Chinese older immigrants living in Canada between the early (i.e., Wave 1: September-November 2020) and late (i.e., Wave 2: January-February 2023) stages of the COVID-19 pandemic. Additionally, it assessed perceived social support from family, friends, or others as predictors for psychological wellbeing and life satisfaction in this population.

methodsThese questions were addressed with a cross-sectional survey design with two independent samples at Wave 1 (n = 171) and Wave 2 (n = 191), respectively.

resultsThe results revealed lower levels of psychological wellbeing, life satisfaction, and perceived social support in Wave 2 compared to Wave 1. The hierarchical regression models identified social support from friends (but not from family or others) as a significant predictor for psychological wellbeing and life satisfaction. Additionally, a higher level of income and being a male predicted better psychological wellbeing. A higher level of income and a lower level of education predicted greater life satisfaction.

conclusionsThe findings suggest a deterioration in psychological wellbeing and life satisfaction from the early to late stages of the pandemic and highlight the protective effect of social support from friends among Chinese older immigrants.

Indexed as

Chinese older adultsCOVID-19life satisfactionsocial supportwellbeing

Identifiers

PMID39337240
PMCPMC11431511

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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.