Development of a Novel Web-Based Intervention Targeting Pain-Related Outcomes in Individuals With Chronic Orofacial Pain: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Chronic orofacial pain (COP) is common, costly, and associated with substantial pain interference and emotional distress. Psychosocial treatments for COP are scarce and limited (eg, rely on talking, which is often painful for this population; require intensive resources, limiting scalability). Here, we describe the study protocol for developing Face-Forward-Web, a "talk-free" web-based mind-body intervention for patients with COP. OBJECTIVE: We aim to (1) develop Face-Forward-Web with the aid of live-video focus groups with adults with COP and (2) optimize Face-Forward-Web and our study protocol through beta testing followed by an open feasibility trial. METHODS: We will accomplish these aims in 2 phases, incorporating user-centered design principles. For phase 1, we conducted semistructured focus groups (n=4 groups, 22 participants) with individuals with COP. We are using rapid data analysis followed by thematic analysis to gauge treatment needs, preferences, and perceptions of the proposed platform and skills. This information will inform session structure and content as well as development of a wireframe followed by a prototype. For phase 2, we will conduct beta testing (up to n=10) followed by a feasibility trial (up to n=20) with exit interviews to gather feedback. The primary outcomes are feasibility benchmarks such as recruitment (≥70% of the eligible participants will participate), acceptability (≥70% of the participants complete ≥4 or 5 sessions), credibility, expectancy (≥70% above the Credibility and Expectancy scale's midpoint), and satisfaction (≥70% above the User Experience Questionnaire's midpoint). RESULTS: Recruitment for phase 1 began in October 2024 and concluded in January 2025. Data analysis for phase 1 will conclude in fall 2025 and for phase 2 in 2026. Results will iteratively guide the development of the intervention. CONCLUSIONS: Face-Forward-Web will be the first talk-free web-based intervention tailored to the needs of adults with COP. Results will inform a future efficacy trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT06754917; https://clinicaltrials.gov/study/NCT06754917. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/71839.
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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 | 0.044 | 0.036 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.065 | 0.010 |
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".