Effects of two years of COVID-19 pandemic on individuals with fibromyalgia
Bibliographic record
Abstract
OBJECTIVES: The COVID-19 pandemic has caused prolonged stress, potentially exacerbating fibromyalgia (FM) symptoms. This study aimed to compare the health status of FM patients and healthy controls (HC) before and 2.5 years into the pandemic. METHODS: A cohort of FM patients and HC with pre-pandemic data completed an online survey in August 2022. The survey collected demographic information, symptom severity, and health perception using the Fibromyalgia Impact Questionnaire (FIQ), Brief Pain Inventory (BPI), Perceived Stress Scale (PSS), and other quality of life and physical activity questionnaires. RESULTS: The study included 32 FM patients and 21 HC, all female and predominantly white, with FM patients having higher BMI. Emotional responses to the pandemic were similar across both groups. Clinical measures in FM showed stability or improvement in 84% for FM severity scores, 66% for FIQ (quality of life), and 50% for pain intensity. Physical activity related to sports decreased in both FM and HC, while leisure activity increased in FM but decreased in HC. In FM insomnia correlated with pain intensity, clinical measures were associated with function and affective status, and changes in leisure activity inversely correlated with pain interference. CONCLUSIONS: Contrary to expectations, FM patients' health remained stable or improved during the pandemic. This study is unique due to its pre-pandemic data and comparison to a control group, reducing potential bias. Findings suggest that FM patients may have developed resilience, or benefited from pandemic-related lifestyle changes, such as a slower pace of life. Alternatively, the observed trends could reflect a regression to the mean.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".