Exploring occupations and well-being before and during the COVID-19 pandemic in adults with and without inflammatory arthritis
Bibliographic record
Abstract
To decrease the spread of the COVID-19 virus, public health officials in British Columbia, Canada ordered large-scale physical distancing requirements, leading to school and business closures, banning of large gatherings, and travel restrictions. These requirements shifted people’s occupational repertoires, with vulnerable populations (e.g., those with chronic health conditions) possibly being differentially impacted. To learn more about people’s occupational changes, we conducted a before-and-after study during the first wave of COVID-19 on occupations and well-being of adults with and without inflammatory arthritis (IA). We invited participants from a prior study to repeat selected measures to assess the impact of pandemic restrictions. Occupations, occupational balance, stress, life satisfaction, and physical and mental health were measured in participants during pre-pandemic (April 2019-March 12, 2020; Time 1) and phase one pandemic restrictions (March 16-May 19, 2020, Time 2). Of 143 adults from the pre-pandemic study, 71 agreed to participate in a Time 2 online survey. Six categories of occupation were identified at Time 1, using Personal Projects Analysis (a tool to explore and measure occupation). At Time 2, there was less variety in health-related occupations, along with a decrease in community-oriented occupations and an increase in occupations around the home. Occupations were characterized as having greater time adequacy at Time 2 than Time 1. Occupational balance and stress scores were higher at Time 2 in both groups, and mental health scores lower at Time 2 only in the healthy comparison group. These pre/post and between-group comparisons contribute to nuanced understandings of the impact of chronic illness and short-term societal disruptions on occupations and well-being.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".