Understanding the use of over-the-counter pain treatments in adolescents with chronic pain
Bibliographic record
Abstract
Background: The prevalence of chronic pain in children and adolescents is well established. What is not well understood is how over-the-counter (OTC) oral and topical pain treatments are being used by adolescents with chronic pain, their decision making around use of these products, and how they communicate with their health care providers about their use.Aims: The aim of this study was to explore the use, decision-making process, and communication about the use of OTC pain medications with health care professionals among adolescents living with chronic pain and their primary caregiver.Methods: A qualitative descriptive design with semistructured, audiotaped individual interviews was undertaken with adolescents with chronic pain (n = 15, aged 12–18 years, mean age = 16, SD = 1.79) and their caregivers (n = 16). A convenience sample of patient–caregiver dyads was recruited from a tertiary care pediatric chronic pain clinic in Ontario.Results: Interview questions focused on four topics: (1) experience with chronic pain and medication; (2) perceptions of medications and concerns with long-term consumption; (3) decision making for use of OTC medications guided mainly by a trusted source or health care professional; and (4) topical OTC medications perceived as harmless. Content analysis within these four topics uncovered two to four subthemes, which are described in detail.Conclusions: An improved understanding of the prevalence of use, decision-making process around use, and how patients and their families communicate about the use of OTC pain medications with health care providers can help clinicians better personalize treatments and help adolescents with chronic pain to make sound self-care decisions.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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, 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".