Developing a Core Outcome Set for Pediatric and Adult Acute and Chronic Pain Extended Reality Trials: Delphi Consensus-Building Process
Notice bibliographique
Résumé
BACKGROUND: Appropriate outcome assessment strategies and high-quality trials are critical to advancing care of patients with acute and chronic pain. Using extended reality (XR), namely, virtual and augmented reality, as a nonpharmacological treatment for pain has accelerated in the last decade. XR allows users to engage completely in immersive, gamified, sensorial digital experiences. Currently, no standardized approach to assessing outcomes of XR-based interventions for pain exists. OBJECTIVE: Our aim was to recommend a core set of outcomes for pediatric and adult acute and chronic pain XR intervention trials. METHODS: To identify core outcomes, we conducted a multiphase process. In phase 1, we conducted systematic reviews on XR in pediatric and adult acute and chronic pain trials to identify the most common core outcome domains assessed in existing published studies. Primary outcome domains were identified and informed the development of the survey for phase 2, a Delphi survey of clinicians and researchers who were actively researching or using XR for pain treatment. Together, results from the systematic reviews and Delphi survey responses were collated, and in phase 3, a 2-day in-person meeting was held to reach consensus on recommended outcome domains for adult and pediatric acute and chronic pain XR clinical trials. This was followed by 2 additional rounds of the Delphi survey to broaden consensus and refine the domains and definitions. Following the Outcome Measures in Rheumatology guidelines for consensus building, outcomes were organized into 3 categories: mandatory, important to consider but optional, and research agenda. RESULTS: A systematic review including XR trials for adult and pediatric acute and chronic pain was conducted in March 2023, and 90 pediatric and 104 adult studies were included. The round 1 Delphi survey, completed by 66 respondents, revealed the following commonly measured outcomes: pain intensity or quality, distraction, anxiety or fear, satisfaction, and adverse events. Respondents indicated the following domains to be of highest importance to measure in studies: safety, feasibility, and acceptability; pain intensity or quality; pain interference or functioning; emotional functioning; and user experience or immersion. By unanimous vote at the consensus conference, pain severity, adverse events, user experience, and psychological constructs were identified as mandatory domains to be assessed in all XR trials for acute and chronic pain, with the addition of pain interference for chronic pain trials. Physiological markers and physical function were deemed important-to-consider but optional domains. Additional emerging areas for future research did not obtain sufficient support in the consensus process but were noted. CONCLUSIONS: An established core outcome set will help strengthen the emerging evidence base supporting XR interventions for children and adults with pain. Future work is underway to provide recommendations for appropriate validated measures to assess each established outcome domain.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,621 | 0,621 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,004 |
| Méta-épidémiologie (sens large) | 0,007 | 0,012 |
| Bibliométrie | 0,023 | 0,011 |
| Études des sciences et des technologies | 0,007 | 0,010 |
| Communication savante | 0,010 | 0,013 |
| Science ouverte | 0,009 | 0,025 |
| Intégrité de la recherche | 0,009 | 0,013 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».