Factors associated with stress about returning to pre-pandemic routines among Canadians
Bibliographic record
Abstract
The COVID-19 pandemic continues to be a public health concern, with important impacts on individuals' mental health. Many people have experienced significant changes to their daily routines due to the pandemic and for some, returning to pre-pandemic routines could create elevated stress. The present study explored factors associated with stress about returning to pre-pandemic routines (SRPR). A web-based, cross-sectional survey of 1,001 Canadian adults aged 18 years and older was conducted on July 9-13, 2021. SRPR was assessed by asking the respondents how much stress they have been feeling about returning to their pre-pandemic routines. Sociodemographic variables, anxiety, depression, loneliness, and COVID-19-related worry were examined in relation to SRPR. Overall, 28.8% of respondents reported moderate to extreme SRPR. After adjusting for covariates, factors associated with elevated SRPR included: younger age (AOR = 2.29, 95%CI 1.30-4.03), higher education (AOR = 2.08, 95%CI 1.14-3.79), being very worried about getting COVID-19 (AOR = 4.14, 95%CI 2.46-6.95), switching to working from home (AOR = 2.43, 95%CI 1.44-4.11), having anxiety (AOR = 5.02, 95%CI 3.19-7.89), feeling depressed (AOR = 1.93, 95%CI 1.14-3.25), and feeling lonely (AOR = 1.74, 95%CI 1.07-2.83). The findings of this study suggest that individuals experiencing mental health concerns (anxiety, feeling depressed, feeling lonely) may be especially likely to feel elevated SRPR and may therefore need additional support in making the transition back to prior routines.
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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 | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".