Unmet health care needs during the COVID-19 pandemic among adults: a prospective cohort study in the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic affected access to health care services in Canada; however, limited research examines the influence of the social determinants of health on unmet health care needs during the first year of the pandemic. The objectives of this study were to describe unmet health care needs during the first year of the pandemic and to investigate the association of unmet needs with the social determinants of health. METHODS: We conducted a prospective cohort study of 23 972 adults participating in the Canadian Longitudinal Study on Aging (CLSA) COVID-19 Study (April-December 2020) to identify the social determinants of health associated with unmet health care needs during the pandemic. Using logistic regression, we assessed the association between several social determinants of health on the following 3 outcomes (separately): experiencing any challenges in accessing health care services, not going to a hospital or seeing a doctor when needed, and experiencing barriers to accessing testing for SARS-CoV-2 infection. RESULTS: From September to December 2020, 25% of participants experienced challenges accessing health care services, 8% did not go to a hospital or see a doctor when needed and 4% faced barriers accessing testing for SARS-CoV-2 infection. The prevalence of all 3 unmet need outcomes was lower among older age groups. Differences were observed by sex, region, education, income and racial background. Immigrants (odds ratio [OR] 1.18, 95% confidence interval [CI] 1.09-1.27) or people with chronic conditions (OR 1.35, 95% CI 1.27-1.43) had higher odds of experiencing challenges accessing health care services and had higher odds of not going to a hospital or seeing a doctor (immigrants OR 1.26, 95% CI 1.11-1.43; chronic conditions OR 1.45, 95% CI 1.31-1.61). Prepandemic unmet health care needs were strongly associated with all 3 outcomes. INTERPRETATION: Substantial unmet health care needs were reported by Canadian adults during the first year of the pandemic. The results of this study have important implications for health equity.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".