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Record W4311943512 · doi:10.1080/26892618.2022.2153958

COVID-19 Pandemic Experiences across the Shelter-Care Continuum in Older Adults

2022· article· en· W4311943512 on OpenAlexafffundabout
Paneet Gill, Gloria Gutman, Mojgan Karbakhsh, Robert Beringer, Brian de Vries

Bibliographic record

VenueJournal of Aging and Environment · 2022
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of VictoriaSimon Fraser UniversityPublic Health OntarioUniversity of Toronto
FundersCanadian Frailty NetworkGovernment of Canada
KeywordsPandemicPsychosocialCoronavirus disease 2019 (COVID-19)Social isolationFeelingIsolation (microbiology)GerontologyContinuum of care2019-20 coronavirus outbreakPsychologyAging in placeMedicineOutbreakHealth carePolitical scienceSocial psychologyPsychiatryDiseaseVirology

Abstract

fetched live from OpenAlex

The COVID-19 pandemic's impact on older adults (55+) living at the mid-point of the shelter-care continuum, in seniors housing (SH) and assisted living (AL), remains largely unexplored. This study compares survey responses of SH and AL residents with those of age peers living in private conventional community-based dwellings (CD) in British Columbia, Canada. Despite more SH/AL residents reporting feelings of isolation and changes to social support access, the pandemic appears to have had a greater negative impact on the routines of CD older adults. AL residents were more likely to engage in advance care planning discussions before and since the COVID-19 outbreak. These data are important for improving response to current and future disasters across the shelter-care continuum, particularly in ways to reduce the psychosocial effects of isolation or routine disruption, and strategies to increase advance care planning engagement.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.028
GPT teacher head0.365
Teacher spread0.337 · 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 designQualitative
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

Citations1
Published2022
Admission routes3
Has abstractyes

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