Evidence map›Paper›PMID 36992843›Full record

ArticleHabitat international2023

Housing and psychosocial well-being during the COVID-19 pandemic.

Yushu Zhu, Meg Holden

Open access · hybridAbstract read
In one paragraph

Article in Habitat international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
12.7field-weighted citation impact, top 1% of its field
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

4 citing papers in PubMed, 22 citations in OpenAlex.

  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

2 authors at 1 institution in 1 country.

Yushu ZhuSimon Fraser University, 515 W Hastings St, Vancouver, BC, V6B 5K3, Canada.
Meg HoldenSimon Fraser University, 515 W Hastings St, Vancouver, BC, V6B 5K3, Canada.
Simon Fraser University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The loss of psychosocial well-being is an overlooked but monumental consequence of the COVID-19 pandemic. These effects result not only from the pandemic itself but, in a secondary way, from the Non-Pharmaceutical Interventions (NPIs) made to curb the spread of disease. The unprecedented physical distancing and stay-at-home requirements and recommendations provide a unique window for housing researchers to better understand the mechanisms by which housing affects psychosocial well-being. This study draws on a survey conducted with over 2,000 residents of the neighbouring Canadian provinces of British Columbia and Alberta in 2021. We propose a new multi-dimensional model to examine the relationships between the Material, Economic, Affordances, Neighbourhood, and Stability (MEANS) aspects of housing and psychosocial well-being. Our analysis reveals the direct and indirect pathways by which deficiencies in each of these areas had negative effects on psychosocial well-being. Residential stability, housing affordances, and neighbourhood accessibility exert stronger direct impacts on psychosocial well-being than material and economic housing indicators (e.g. size of living space and tenure). Notably, we find no significant well-being differences between different homeowners and renters when we account for other housing MEANS. These findings have important implications for housing policy across pandemic and post-pandemic contexts, suggesting a need for research and policy focus on understanding housing and well-being in terms of non-material aspects, such as residential stability and affordances that housing provides.

Indexed as

AffordanceCanadaHousingPath analysisPsychosocial well-being

Identifiers

PMID36992843
PMCPMC10033258
OpenAlexW4360620105

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.