Sense of control and positive mental health outcomes among adults in Canada during the COVID-19 pandemic
Bibliographic record
Abstract
Background: During the COVID-19 pandemic in Canada, there was a decrease in population positive mental health (PMH); however, many individuals still reported high levels of PMH. One potential protective factor could be a sense of control, which involves perceptions of personal mastery and minimal perceived constraints. Limited Canadian research has been conducted on the link between sense of control and PMH during the pandemic. Data and methods: This study used cross-sectional data from the 2020 and 2021 Survey on COVID-19 and Mental Health, which included adults (18 years and older) living in the 3 territorial capitals and 10 provinces in Canada. Two facets of sense of control were measured with the Sense of Mastery Scale: personal mastery and perceived constraints. Three PMH outcomes were measured using single-item measures of self-rated mental health (SRMH), community belonging, and life satisfaction. Regression analyses were conducted to examine associations between the two sense of control facets and the three PMH outcomes. Results: Higher personal mastery was associated with higher average life satisfaction and a greater likelihood of high SRMH and strong community belonging. In contrast, greater perceived constraints were associated with lower average life satisfaction and a lower likelihood of high SRMH and strong community belonging. Sociodemographic differences on the facets were observed. Interpretation: Adults in Canada with a higher sense of control during the pandemic tended to have better PMH than those who felt like they had less control. Further research on mental health promotion efforts involving sense of control is needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".