Research AppraisalRandomised Controlled Trial

Effectiveness of tele-rehabilitation using AI-guided exercise and pain neuroscience education for fibromyalgia (FIBROIA): Protocol for a randomized controlled trial

PloS oneMorales-Osorio, Marco Antonio, Ordóñez-Vega, Romualdo, Alomía Penafiel, Gustavo Adolfo et al.DOI

Clinical Snapshot

60CEBM
Evidence: ModerateRandomised Controlled Trial

PICO Framework

P — PopulationAdults meeting 2016 ACR criteria for fibromyalgia (n=50)
I — Intervention12-week tele-rehabilitation program combining AI-guided exercise (3 sessions/week via Rehbody platform) with weekly Pain Neuroscience Education modules
C — ComparatorEnhanced usual care
O — OutcomesPrimary: pain intensity (VAS) at week 13. Secondary: FIQ-R, 30-Second Sit-to-Stand test, EQ-5D-3L quality of life

Bottom Line

This protocol describes a novel approach combining AI-guided exercise with pain neuroscience education for fibromyalgia management via telerehabilitation. While the intervention addresses important accessibility barriers and combines evidence-based treatments, the protocol has significant methodological limitations including small sample size, poorly defined control group, and inability to blind participants. The study design is assessor-blinded but lacks adequate detail on randomization procedures and power calculations. If successfully completed, this trial could provide preliminary evidence for technology-enhanced fibromyalgia care, though larger, more rigorously designed studies would be needed to establish clinical efficacy. The integration of real-time biomechanical feedback with cognitive pain education represents an innovative approach that warrants investigation, particularly for underserved populations with limited access to specialized care.

Evidence: Moderate

Key Findings

  • P Value: Not available - protocol stage

  • Effect Size: Not available - protocol stage

  • Primary Outcome: Change in pain intensity (VAS) at week 13

  • Nnt Or Sensitivity: Not available - protocol stage

  • Confidence Interval: Not available - protocol stage

Clinical Application

Requires access to AI platform technology and internet connectivity; may face implementation barriers in low-resource settings Relevant to Australian telehealth initiatives and rural/remote access challenges; would need TGA approval for AI medical device components and consideration for Medicare telehealth item numbers Adults with fibromyalgia meeting 2016 ACR criteria, particularly those in underserved or resource-limited settings

Abstract

INTRODUCTION: Fibromyalgia (FM) is a chronic condition characterized by widespread pain and cognitive dysfunction, with pharmacological treatments offering limited efficacy. Although Pain Neuroscience Education (PNE) and therapeutic exercise are evidence-based interventions, accessibility and adherence remain major challenges particularly in underserved regions such as Latin America. This trial investigates the effectiveness of a 12-week tele-rehabilitation program (FIBROIA) that integrates Artificial Intelligence (AI)-guided exercise with PNE to enhance access to comprehensive multimodal care. METHODS AND ANALYSIS: This multicentre, randomized, assessor-blinded, parallel-group controlled trial will enroll fifty adults meeting the 2016 ACR criteria for FM. Participants will be randomly assigned (1:1) to either the intervention group or enhanced usual care. The intervention consists of three personalized exercise sessions per week delivered through the Rehbody AI platform, which provides real-time biomechanical feedback, along with a weekly PNE module designed to reconceptualize pain. The primary outcome is the change in pain intensity, measured using the Visual Analogue Scale (VAS), at week 13 (±7 days), immediately following completion of the 12-week program. Secondary outcomes include the Fibromyalgia Impact Questionnaire-Revised (FIQ-R), lower-limb strength assessed by the 30-Second Sit-to-Stand test, and health-related quality of life measured with the EQ-5D-3L. Statistical analyses will follow an intention-to-treat (ITT) framework. DISCUSSION: The FIBROIA protocol addresses the urgent need for scalable, evidence-based interventions in resource-limited settings. By combining AI-driven biomechanical feedback with cognitive reappraisal through PNE, this study seeks to reduce fear-avoidance behaviors and improve exercise adherence. This integrative approach aims to overcome the limitations of passive tele-rehabilitation by simulating asynchronous professional supervision, thereby ensuring both safety and technical precision in movement execution. CONCLUSIONS: If effective, this protocol will offer a robust, technology-enabled framework for remote FM management. The results could help establish a new clinical standard for accessible, patient-centered rehabilitation, bridging the gap between high-level evidence and real-world practice across diverse socioeconomic contexts. TRIAL REGISTRATION: ClinicalTrials.gov NCT06672419.

References

  1. 1.Morales-Osorio, M. A., Ordóñez-Vega, R., Alomía Penafiel, G. A., & Ordoñez-Mora, L. T. (2026). Effectiveness of tele-rehabilitation using AI-guided exercise and pain neuroscience education for fibromyalgia (FIBROIA): Protocol for a randomized controlled trial. PLoS One. https://doi.org/10.1371/journal.pone.0349017
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