Impact of COVID-19 pandemic on chronic pain and opioid use in marginalized populations: A scoping review
Bibliographic record
Abstract
Introduction: The COVID-19 pandemic has had a variable effect on vulnerable populations, including patients with chronic pain who rely on opioid treatment or have comorbid opioid use disorder. Limited access to care due to isolation measures may lead to increased pain severity, worse mental health symptoms, and adverse opioid-related outcomes. This scoping review aimed to understand the impact of the COVID-19 pandemic on the dual epidemics of chronic pain and opioids in marginalized communities worldwide. Methods: Searches of primary databases including PubMed, Web of Science, Scopus, and PsycINFO were performed in March 2022, restricting the publication date to December 1, 2019. The search yielded 685 articles. After title and abstract screening, 526 records were screened by title and abstract, 87 through full-text review, of which 25 articles were included in the final analysis. Results: Our findings illuminate the differential distribution of pain burden across marginalized groups and how it serves to heighten existing disparities. Service disruptions due to social distancing orders and infrastructural limitations prevented patients from receiving the care they needed, resulting in adverse psychological and physical health outcomes. Efforts to adapt to COVID-19 circumstances included modifications to opioid prescribing regulations and workflows and expanded telemedicine services. Conclusion: Results have implications for the prevention and management of chronic pain and opioid use disorder, such as challenges in adopting telemedicine in low-resource settings and opportunities to strengthen public health and social care systems with a multidisciplinary and multidimensional approach.
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How this classification was reachedexpand
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".