Longitudinal Analysis of the Behavioral and Occupational Factors Present in Individuals Living with Inflammatory Bowel Disease during the COVID-19 Pandemic in Calgary, Alberta
Bibliographic record
Abstract
The COVID-19 pandemic caused by the SARS-CoV-2 virus resulted in a public health emergency. Routine behaviours such as shopping were considered high-risk during the pandemic. Research on how people with inflammatory bowel disease (IBD) altered their behaviour during the pandemic is lacking. Therefore, we aimed to understand how the behaviours of persons with IBD were altered during the pandemic, and whether behavioural exposures were associated with COVID-19 disease. At recruitment, 556 participants with a confirmed diagnosis of IBD were administered a self-report, online questionnaire. The primary baseline questionnaire captured demographic and occupational factors as well as the frequency of social behaviours at two time periods: 1. January–March 2020 (i.e., prior to pandemic lockdown), and 2. January–September 2021 (i.e., restriction period). A follow-up questionnaire investigating the same exposures from January–March 2022 (Omicron era) was completed by a subset of 223 participants between September 1st, 2022, and October 20th, 2022. Proportions for high frequency behaviours (daily to once per week) across the three time periods were reported. Multivariable logistic regression was used to analyze behaviours and Omicron-era COVID-19 cases. Behavioural changes were observed across all three time periods. The proportion of highly frequent behaviours dropped for almost all behaviour measures (except for outdoor exercise and online groceries) between January–March 2020 and January–September 2021. The proportion of most behaviours increased between January–September 2021 and January–March 2022 but did not match pre-pandemic levels (except online groceries, outdoor fitness, and travelling). Participants who visited restaurants frequently (i.e., daily to once per week) had 3.24 times the odds of getting COVID-19 compared with those who visited a restaurant infrequently (i.e., less than once per week). Over a two-year period, those with IBD changed their behaviours and lifestyle, perhaps in response to policy and restriction changes in Alberta. Individuals with IBD resorted to lower risk behaviours such as outdoor exercise, and activities with higher risk of exposure (e.g., indoor fitness) did not return to pre-pandemic levels.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".