Impact of the Covid-19 pandemic on mental health of persons with disabilities: Insights from the 2021 Canadian Housing Survey
Bibliographic record
Abstract
Mental health (MH) remains a major public health concern in Canada and has been exacerbated by the unprecedented challenges of the COVID-19 pandemic and the associated restrictions on physical movement. While considerable work has been done on the impact of COVID-19 on the physical and MH of the general population, relatively less work has focused on the MH of persons with disabilities (PWDs). Although the COVID-19 containment measures including lockdowns, social distancing, quarantine, and closure of nonessential services were intended to reduce the direct risks of COVID-19, the socioeconomic consequences of those restrictions and the uncertainties surrounding the virus, inadvertently had adverse impact on the MH and well-being of Canadian residents, particularly, among already marginalized groups such as PWDs. Moreover, PWDs were identified as disproportionately vulnerable to the psychological impacts of the pandemic containment measures which compromised their overall Positive Mental Health (PMH): a state of well-being where individuals can realize their full potential, manage life's stresses, work productively, and contribute to society. This study addresses the research gap by examining the effect of the pandemic on the MH of PWDs in Canada using a cross-sectional analysis of the 2021 Canadian Housing Survey (N = 15,626), a subset of people who reported disabilities. Logistic regression models were employed for this cross-sectional analysis. The results show that females (OR = 0.789; P < 0.001), those who experienced COVID-19 economic hardship (OR = 0.703; P < 0.001), and dwelling dissatisfaction (OR = 0.585; P < 0.001), significantly reported about 0.79, 0.70, and 0.59 times lower odds of positive Mental Health (PMH), respectively. On the other hand, those who had post-secondary educational attainment (OR = 1.210; P < 0.001), strong sense of community belonging (OR = 2.056; P < 0.001), and civic engagement with their communities (OR = 1.204; P < 0.001), were significantly associated with 1.21, 2.06, and 1.20 times higher odds of PMH, respectively. Additionally, immigration status, household type, the province of residence, and neighborhood-specific challenges such as race-based harassments, and drug use/dealings emerged as significant predictors of PMH. The findings underscore the positive impacts of empowering elements such as strong community ties on the MH of PWDs during public health crisis. Also, the findings prompt the pressing need for identifying and addressing the unique challenges of PWDs in Canada, particularly, the less educated and socioeconomically disadvantaged, as part of effort to foster PMH in the country. Overall, these findings suggest the need to prioritize and strengthen disability-inclusive MH programs for future public health crises.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".