Self-Reported Pain Treatment Practices Among U.S. and Canadian Adults: Findings From a Population Survey
Bibliographic record
Abstract
Background and Objectives: Pain treatments and their efficacy have been studied extensively. Yet surprisingly little is known about the types of treatments, and combinations of treatments, that community-dwelling adults use to manage pain, as well as how treatment types are associated with individual characteristics and national-level context. To fill this gap, we evaluated self-reported pain treatment types among community-dwelling adults in the United States and Canada. We also assessed how treatment types correlate with individuals' pain levels, sociodemographic characteristics, and country of residence, and identified unique clusters of adults in terms of treatment combinations. Research Design and Methods: We used the 2020 "Recovery and Resilience" United States-Canada general online survey with 2 041 U.S. and 2 072 Canadian community-dwelling adults. Respondents selected up to 10 pain treatment options including medication, physical therapy, exercise, etc., and an open-ended item was available for self-report of any additional treatments. Data were analyzed using descriptive, regression-based, and latent class analyses. Results: Over-the-counter (OTC) medication was reported most frequently (by 55% of respondents, 95% CI 53%-56%), followed by "just living with pain" (41%, 95% CI 40%-43%) and exercise (40%, 95% CI 38%-41%). The modal response (29%) to the open-ended item was cannabis use. Pain was the most salient correlate, predicting a greater frequency of all pain treatments. Country differences were generally small; a notable exception was alcohol use, which was reported twice as often among U.S. versus Canadian adults. Individuals were grouped into 5 distinct clusters: 2 groups relied predominantly on medication (prescription or OTC), another favored exercise and other self-care approaches, one included adults "just living with" pain, and the cluster with the highest pain levels employed all modalities heavily. Discussion and Implications: Our findings provide new insights into recent pain treatment strategies among North American adults and identify population subgroups with potentially unmet need for more adaptive and effective pain management.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".