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Record W4210474464 · doi:10.1186/s12877-022-02769-2

Multimorbidity resilience and COVID-19 pandemic self-reported impact and worry among older adults: a study based on the Canadian Longitudinal Study on Aging (CLSA)

2022· article· en· W4210474464 on OpenAlexafffundabout
Andrew Wister, Lun Li, Theodore D. Cosco, Jacqueline M. McMillan, Lauren E. Griffith, Andrew P. Costa, Laura N. Anderson, Cynthia Balion, Susan Kirkland, Christina Wolfson, Nicole E. Basta, Benoît Cossette, Mélanie Levasseur, Scott M. Hofer, Theone Paterson, David B. Hogan, Teresa Liu‐Ambrose, Verena Menec, Philip St. John, Gerald Mugford, Zhiwei Gao, Vanessa Taler, Patrick S. R. Davidson, Paminder Raina

Bibliographic record

VenueBMC Geriatrics · 2022
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsMemorial University of NewfoundlandUniversity of British ColumbiaUniversity of OttawaSimon Fraser UniversityMcGill University Health CentreCapital District Health AuthorityUniversité de SherbrookeMcMaster UniversityManitoba HealthUniversity of VictoriaImpactUniversity of CalgaryUniversity of Manitoba
FundersCanadian Institutes of Health ResearchGovernment of CanadaPublic Health AgencyPublic Health Agency of CanadaMcMaster University
KeywordsWorryMedicinePandemicLongitudinal studyPsychological resilienceGerontologyCoronavirus disease 2019 (COVID-19)DemographyLogistic regressionPopulationEnvironmental healthPsychologyDiseasePsychiatryInternal medicineAnxiety

Abstract

fetched live from OpenAlex

BACKGROUND: The Coronavirus Disease-2019 (COVID-19) pandemic has created a spectrum of adversities that have affected older adults disproportionately. This paper examines older adults with multimorbidity using longitudinal data to ascertain why some of these vulnerable individuals coped with pandemic-induced risk and stressors better than others - termed multimorbidity resilience. We investigate pre-pandemic levels of functional, social and psychological forms of resilience among this sub-population of at-risk individuals on two outcomes - self-reported comprehensive pandemic impact and personal worry. METHODS: This study was conducted using Follow-up 1 data from the Canadian Longitudinal Study on Aging (CLSA), and the Baseline and Exit COVID-19 study, conducted between April and December in 2020. A final sub-group of 9211 older adults with two or more chronic health conditions were selected for analyses. Logistic regression and Generalized Linear Mixed Models were employed to test hypotheses between a multimorbidity resilience index and its three sub-indices measured using pre-pandemic Follow-up 1 data and the outcomes, including covariates. RESULTS: The multimorbidity resilience index was inversely associated with pandemic comprehensive impact at both COVID-19 Baseline wave (OR = 0.83, p < 0.001, 95% CI: [0.80,0.86]), and Exit wave (OR = 0.84, p < 0.001, 95% CI: [0.81,0.87]); and for personal worry at Exit (OR = 0.89, p < 0.001, 95% CI: [0.86,0.93]), in the final models with all covariates. The full index was also associated with comprehensive impact between the COVID waves (estimate = - 0.19, p < 0.001, 95% CI: [- 0.22, - 0.16]). Only the psychological resilience sub-index was inversely associated with comprehensive impact at both Baseline (OR = 0.89, p < 0.001, 95% CI: [0.87,0.91]) and Exit waves (OR = 0.89, p < 0.001, 95% CI: [0.87,0.91]), in the final model; and between these COVID waves (estimate = - 0.11, p < 0.001, 95% CI: [- 0.13, - 0.10]). The social resilience sub-index exhibited a weak positive association (OR = 1.04, p < 0.05, 95% CI: [1.01,1.07]) with personal worry, and the functional resilience measure was not associated with either outcome. CONCLUSIONS: The findings show that psychological resilience is most pronounced in protecting against pandemic comprehensive impact and personal worry. In addition, several covariates were also associated with the outcomes. The findings are discussed in terms of developing or retrofitting innovative approaches to proactive coping among multimorbid older adults during both pre-pandemic and peri-pandemic periods.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.222
Threshold uncertainty score0.446

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.108
GPT teacher head0.376
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2022
Admission routes3
Has abstractyes

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