Immigrants’ Use of Online Mental Health Services during the COVID-19 Pandemic
Bibliographic record
Abstract
Purpose: Canadian immigrants tend to have poorer mental health than Canadians and lower access to mental health resources. Online mental health services (OMHS) offer promise in improving access to mental health care and has not been well-researched for Canadian immigrants. Thus, this study characterized Canadian immigrants’ OMHS use during the COVID-19 pandemic considering confounders (i.e., age and previous OMHS use) and effect modifiers (i.e., gender and income). Methods: Data collected by Mental Health Research Canada were used to evaluate the prevalence of OMHS use and immigrants’ access to OMHS. Immigrant groups were defined by generation status and newcomer status, examined with separate models. First generation immigrants were defined by being born abroad, second generation by being born in Canada with at least one parent born abroad, and third generation by being born in Canada with both parents. Multiple logistic regressions accounted for confounders and effect modifiers. Pandemic phase was explored as a hierarchical variable, but included as a covariate instead due to insufficient evidence suggesting clustering. Results: From February 2021 to July 2022, self-reported OMHS use was 11.5%, nearly double the pre-pandemic prevalence of 6.5%. First generation immigrants had significantly lower odds of OMHS use (OR=0.558, 95% CI: 0.409-0.761) compared to third generation Canadians, while second generation Canadians had similar odds (OR=0.987, 95% CI: 0.726-1.342), controlling for covariates. Younger age, self-identifying as female, low income, previous OMHS use, and later pandemic phase increased the odds of OMHS use compared to older age, being male, medium or high income, no previous OMHS use, and earlier pandemic phase. Interactions between immigrant status with income and gender were significant only for first generation immigrants. The second model indicated similar odds of OMHS use for immigrants who lived in Canada for less than five years and those who lived in Canada for more than five years when controlling for age and previous OMHS use (OR= 0.961, 95% CI: 0.722-1.279). Conclusion: This study provided an understanding of immigrants’ OMHS access in Canada and factors influencing OMHS use. It highlighted the need for strategies to increase access for first generation immigrants to ensure equitable OMHS access.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".