Assessment of Two Online Interventions for Veterans With Chronic Pain: Protocol for a Randomized Controlled Efficacy Trial
Notice bibliographique
Résumé
BACKGROUND: Chronic pain is a debilitating condition that disproportionately impacts US veterans who manage numerous negative pain-related outcomes. There is an urgent need for accessible, engaging, and innovative treatments that can help veterans with chronic pain better self-manage their pain at home and improve their daily functioning. Technology-delivered acceptance- and mindfulness-based interventions for pain have shown strong efficacy, particularly when they are engaging and tailored to specific client needs. However, more research is needed to assess the impact of such interventions, particularly in terms of pain-related functioning and quality of life. OBJECTIVE: The primary aim of this study is to test the efficacy of Veteran Acceptance and Commitment Therapy for Chronic Pain (VACT-CP), an online self-management pain program, compared to an active online control (Online Pain School) for improving pain-related functioning in a 3-site randomized controlled trial. The secondary aim is to explore psychological flexibility as a potential mediator between pain severity and pain-related functioning. METHODS: This study will use a mixed methods approach to examine the efficacy of VACT-CP in a 2-arm, multisite, randomized controlled superiority trial including 200 participants with chronic musculoskeletal pain compared to Online Pain School. Participants will be assigned to 1 of these 2 online interventions. Both interventions will include 7 modules delivered over 7 weeks, with each module lasting approximately 15 minutes. Mixed effects models will be used to analyze the primary hypothesis that participants in the VACT-CP group will have greater improvement in pain-related functioning (Brief Pain Inventory-Interference subscale) than those in the active control group (Online Pain School). The main acceptance and commitment therapy process mediator (ie, Multidimensional Psychological Flexibility Inventory), pain-related functioning outcomes (Brief Pain Inventory-Interference subscale), and quality of life (Veterans RAND 36-Item Health Survey) will be measured at baseline, end of treatment, and 3 and 6 months after treatment. In addition, qualitative exit interviews will be conducted with a random set of 30 VACT-CP users (n=10, 33% per site) to obtain intervention usability, feasibility, and acceptability information. RESULTS: The recruitment for this study began in January 2025. It is expected to continue through January 2027. Data collection is expected to be completed by June 2027, and primary data analyses are expected to be completed by early 2028. CONCLUSIONS: Online interventions such as VACT-CP and Online Pain School have the potential to expand access to behavioral interventions that improve quality of life and provide nonpharmacological pain treatment options for veterans experiencing chronic pain. However, research on their impact and underlying mechanisms of change is required to support this area of potential at-home programming. TRIAL REGISTRATION: ClinicalTrials.gov NCT06058624; https://clinicaltrials.gov/study/NCT06058624. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/70601.
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 | 0,056 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,008 | 0,005 |
| Méta-épidémiologie (sens large) | 0,015 | 0,008 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,005 | 0,003 |
| Intégrité de la recherche | 0,009 | 0,013 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,104 | 0,018 |
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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».