Enhancing Exposure Treatment for Youths With Chronic Pain: Co-design and Qualitative Approach
Bibliographic record
Abstract
BACKGROUND: Increasing the access to and improving the impact of pain treatments is of utmost importance, especially among youths with chronic pain. The engagement of patients as research partners (in contrast to research participants) provides valuable expertise to collaboratively improve treatment delivery. OBJECTIVE: This study looked at a multidisciplinary exposure treatment for youths with chronic pain through the lens of patients and caregivers with the aim to explore and validate treatment change processes, prioritize and develop ideas for improvement, and identify particularly helpful treatment elements. METHODS: Qualitative exit interviews were conducted with patients and caregivers at their discharge from 2 clinical trials (ClinicalTrials.gov NCT01974791 and NCT03699007). Six independent co-design meetings were held with patients and caregivers as research partners to establish a consensus within and between groups. The results were validated in a wrap-up meeting. RESULTS: Patients and caregivers described that exposure treatment helped them better process pain-related emotions, feel empowered, and improve their relationship with each other. The research partners developed and agreed upon 12 ideas for improvement. Major recommendations include that pain exposure treatment should be disseminated more not only among patients and caregivers but also among primary care providers and the general public to facilitate an early referral for treatment. Exposure treatment should allow flexibility in terms of duration, frequency, and delivery mode. The research partners prioritized 13 helpful treatment elements. Most of the research partners agreed that future exposure treatments should continue to empower patients to choose meaningful exposure activities, break long-term goals into smaller steps, and discuss realistic expectations at discharge. CONCLUSIONS: The results of this study have the potential to contribute to the refinement of pain treatments more broadly. At their core, they suggest that pain treatments should be disseminated more, flexible, and transparent.
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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 | 0.065 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".