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
Bibliographic record
Abstract
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.
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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 | 0.030 | 0.027 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.008 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.058 | 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".