Impact of the COVID-19 pandemic on Canadian Armed Forces Veterans who live with chronic pain
Bibliographic record
Abstract
LAY SUMMARY Chronic pain is more frequent in military Veterans than in the general population. The objective of this study was to assess whether the COVID-19 pandemic has had a greater impact on Canadian Armed Forces (CAF) Veterans who live with chronic pain compared to non-Veterans. An online survey of Canadian adults with chronic pain was conducted between April and May 2020; 76 respondents reported having formerly served in the CAF and were compared with 76 similar non-Veterans. About two thirds of the Veterans had been living with chronic pain for longer than 10 years. Two thirds reported worsened pain since the pandemic began. Nearly half experienced moderate to severe psychological distress. These changes were similar to those in non-Veterans with chronic pain. A significant number of Veterans and non-Veterans changed their pain treatments due to the pandemic. In summary, the COVID-19 pandemic and associated restriction measures did not have a greater impact in CAF Veterans with chronic pain compared with non-Veterans. However, changes in chronic pain supports are needed to be better prepared for COVID-19 waves to come and future health crises.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".