A cross-sectional study of pain status and psychological distress among individuals living with chronic pain: the Chronic Pain & COVID-19 Pan-Canadian Study
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has had a disproportionate impact on vulnerable populations, including individuals with chronic pain. We examined associations between geographical variations in COVID-19 infection rates, stress and pain severity, and investigated factors associated with changes in pain status and psychological distress among individuals living with chronic pain during the pandemic. METHODS: This investigation is part of a larger initiative, the Chronic Pain & COVID-19 Pan-Canadian Study, which adopted a cross-sectional observational design. A total of 3159 individuals living with chronic pain completed a quantitative survey between 16 April and 31 May 2020. RESULTS: Two-thirds (68.1%) of participants were between 40 and 69 years old, and 83.5% were women. Two-thirds (68.9%) of individuals reported worsened pain since pandemic onset. Higher levels of perceived pandemic-related risks (adjusted odds ratio: 1.27; 95% confidence interval: 1.03-1.56) and stress (1.21; 1.05-1.41), changes in pharmacological (3.17; 2.49-4.05) and physical/psychological (2.04; 1.62-2.58) pain treatments and being employed at the beginning of the pandemic (1.42; 1.09-1.86) were associated with increased likelihood of reporting worsened pain. Job loss (34.9% of individuals were employed pre-pandemic) was associated with lower likelihood (0.67; 0.48-0.94) of reporting worsened pain. Almost half (43.2%) of individuals reported moderate/severe levels of psychological distress. Negative emotions toward the pandemic (2.14; 1.78-2.57) and overall stress (1.43; 1.36-1.50) were associated with moderate/severe psychological distress. CONCLUSIONS: Study results identified psychosocial factors to consider in addition to biomedical factors in monitoring patients' status and facilitating treatment access for chronic pain patients during a pandemic.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".