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Record W4387780835 · doi:10.1080/10530789.2023.2270267

Profiles of quality of life among residents in permanent supportive housing during the COVID-19 pandemic

2023· article· en· W4387780835 on OpenAlexafffundabout
Lia Gentil, Guy Grenier, Marie‐Josée Fleury

Bibliographic record

VenueJournal of Social Distress and the Homeless · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteDouglas College
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsQuality of life (healthcare)PandemicContext (archaeology)Supportive housingMental healthMedicineGerontologySocial supportCoronavirus disease 2019 (COVID-19)Environmental healthPsychologyPsychiatryNursingDiseaseGeography

Abstract

fetched live from OpenAlex

This study identified profiles of quality of life (QoL) deterioration among permanent supportive housing (PSH) residents during the COVID-19 pandemic, which hasn’t been reported on yet. Between November 2020 and April 2022, 231 PSH residents from Quebec (Canada) were interviewed. Patient profiles were identified with Cluster Analysis based on the participants’ sociodemographic and clinical characteristics, and service use were compared (p < 0.05). Three QoL profiles were identified, with 62% of sample reporting QoL deterioration. Profile 1 (26% of sample) included middle-aged men living mostly in congregate PSH since 5 + years, having high social support, few health problems, and perceiving low deterioration of their health conditions and QoL. Profile 2 (44%) included residents living in PSH less than 2 years, with low social support, highly affected by serious mental disorders, few by COVID-19, perceiving deterioration of their mental health conditions and QoL. Profile 3 (30%) included younger residents living in congregate PSH for 2–5 years, with low social support, high health problems, and perceived deterioration of health conditions and QoL. The study underlined the importance of sustaining housing and care access in a pandemic context for individuals with the most unmet needs, more at risk of QoL deterioration.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.794

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.089
GPT teacher head0.434
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2023
Admission routes3
Has abstractyes

Explore more

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