Combining Noninvasive Brain Stimulation and Physiotherapy to Improve the Management of Chronic Low Back Pain in Veterans: Protocol for a Multi-Arm Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Low back pain (LBP) is the most common chronic pain condition in veterans, but the effectiveness of standard management approaches is modest. Addressing the psychological risk factors of chronic pain that are often observed in this population (eg, anxiety, depression, stress and mood disorders) may be important to enhance outcomes. Psychologically informed physiotherapy (PiP) identifies and mitigates the negative impacts of emotional and cognitive factors alongside the biomedical aspects of chronic LBP to improve physical functioning and has shown promising results in this population. However, residual pain and disability often persist in veterans. The combination of PiP with repetitive transcranial magnetic stimulation (rTMS) to the prefrontal cortex may enhance its effectiveness by modulating cognition, emotion, and pain perception. OBJECTIVE: The aim of this study is to compare the effects of (1) combining active rTMS with PiP, (2) combining sham rTMS with PiP, and (3) usual physiotherapy (UP) on physical functioning in veterans with chronic LBP and comorbid psychological risk factors. Secondary objectives include comparing their effect on pain intensity, quality of life, depression symptoms, pain catastrophizing, movement pain-related fear, self-efficacy, medication use, and posttraumatic stress disorder symptoms. METHODS: Ninety-six veterans with chronic LBP and comorbid psychological risks factors of pain will be enrolled in this 3-arm parallel randomized controlled trial. Individuals will be allocated to receive an 8-week intervention of (1) active rTMS + PiP, (2) sham rTMS + PiP, or (3) UP. Online self-administered questionnaires will be completed at baseline, 2, 8, and 26 weeks after the first treatment session. A linear mixed model will be used to assess the treatment effects by using intention-to-treat analyses. We hypothesize that active rTMS + PiP will be more effective than sham rTMS + PiP and that active PiP + rTMS or sham rTMS will be more effective than UP. RESULTS: Ethics approval was obtained in January 2025, and participating physiotherapists completed the 2-day PiP training in May 2025. Participants have been recruited since June 2025. As of December 2025, 28 participants have been included, and recruitment is expected to continue up to June 2027, targeting the inclusion of approximately 4 new participants per month. Follow-up should be completed by December 2027, and results will be analyzed. The results of this randomized controlled trial should be published and available in June 2028. CONCLUSIONS: It is paramount to identify innovative and effective interventions for the management of chronic LBP in veterans. This study will provide new evidence on the effectiveness of two innovative interventions targeting cognitive and emotional factors of pain (ie, PiP and rTMS). If our hypothesis is confirmed, it could motivate changes in clinical practice and improve the quality of life of veterans living with chronic LBP. TRIAL REGISTRATION: ClinicalTrials.gov NCT06999772; https://clinicaltrials.gov/study/NCT06999772. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/78952.
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 | 0,030 | 0,027 |
| Méta-épidémiologie (sens strict) | 0,007 | 0,003 |
| Méta-épidémiologie (sens large) | 0,015 | 0,008 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,008 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,058 | 0,010 |
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 ».