Multimorbidity, COVID-19 and Mental Health: Canadian Longitudinal Study on Aging (CLSA) Longitudinal Analyses
Bibliographic record
Abstract
OBJECTIVES: This paper examines the longitudinal effects of the COVID-19 pandemic on older adults (65+) with multimorbidity on levels of depression, anxiety, and perceived global impact on their lives. METHODS: Baseline (2011-2015) and Follow-up 1 (2015-2018) data from the Canadian Longitudinal Study on Aging (CLSA), and the Baseline and Exit waves of the CLSA COVID-19 study (April-December, 2020) (n = 18,099). Multimorbidity was measured using: a) an additive scale of chronic conditions; and b) six chronic disease clusters. Linear Mixed Models were employed to test hypotheses. RESULTS: Number of chronic conditions pre-pandemic was associated with pandemic levels of depression (estimate = 0.40, 95% CI: [0.37,0.44]); anxiety (estimate = 0.20, 95% CI: [0.18, 0.23]); and perceived negative impact of the pandemic (OR = 1.04, 95% CI: [1.02, 1.06]). The associations between multimorbidity and anxiety decreased during the period of the COVID-19 surveys (estimate = -0.02, 95% CI: [-0.05, -0.01]); whereas the multimorbidity association with perceived impact increased (OR = 1.03, 95% CI: [1.01, 1.05]). CONCLUSIONS: This study demonstrates that pre-pandemic multimorbidity conditions are associated with worsening mental health. CLINICAL IMPLICATIONS: Clinicians treating mental health of older adults need to consider the joint effects of multimorbidity conditions and pandemic experiences to tailor counseling and other treatment protocols.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".