Effectiveness of AI-Guided Exercise and Pain Neuroscience Education for Fibromyalgia (FIBROIA)
- Conditions
- FibromyalgiaFibromyalgia Syndrome
- Registration Number
- NCT06672419
- Lead Sponsor
- Marco Antonio Morales Osorio
- Brief Summary
This randomized controlled trial will investigate a 12-week tele-rehabilitation program for individuals with fibromyalgia (FM), combining AI-guided exercise with pain neuroscience education. Fifty participants will be randomized to either the intervention program or standard care. The primary outcome is reduction in pain intensity, with secondary outcomes including physical function and quality of life. Participants and investigators will remain blinded to group allocation, and outcome assessors and statisticians will remain blinded until data lock.
- Detailed Description
This randomized controlled trial aims to evaluate the effectiveness of a 12-week tele-rehabilitation program that integrates artificial intelligence (AI)-guided exercise, computer vision, and pain neuroscience education (PNE) for individuals with fibromyalgia (FM). The study seeks to determine whether this technology-driven approach can reduce pain intensity, improve physical function, and enhance quality of life in a population that frequently experiences limited benefit from conventional treatment strategies.
Intervention
Participants in the intervention group will use a tele-rehabilitation platform that applies AI and computer vision to deliver personalized exercise programs. The AI system monitors performance in real time and adapts exercises to individual capacities and progress. In parallel, participants will attend weekly sessions of pain neuroscience education, designed to improve their understanding of pain processing within the nervous system and to promote more effective self-management through cognitive and behavioral strategies.
The control group will receive standard care for fibromyalgia, which typically includes pharmacological management (e.g., analgesics, antidepressants, anticonvulsants) alongside general recommendations for physical activity and self-care. Comparison between the groups will allow assessment of the added value of combining AI-guided tele-rehabilitation with PNE.
Study Design Participants will be randomly assigned (1:1) to intervention or control group. The intervention will last 12 weeks, during which participants in the intervention group will complete three exercise sessions per week and one educational session weekly. All sessions will be conducted remotely through a user-friendly platform accessible via smartphones or computers. Outcome assessments will be conducted at baseline and immediately after completion of the 12-week program.
Masking: Participants and investigators will remain blinded to group allocation. Outcome assessors and statisticians will also remain blinded until data lock.
Objectives
The primary objective is to determine whether the AI-guided exercise and PNE program reduces pain intensity and improves physical function compared with standard care. Secondary objectives include evaluating changes in quality of life, psychological well-being, and treatment adherence. Findings will provide evidence on whether technology-enabled rehabilitation can serve as an accessible, effective alternative for fibromyalgia management.
Rationale
Conventional therapies for fibromyalgia, such as pharmacological treatment and standard physical therapy, often provide suboptimal relief. Tele-rehabilitation represents a promising strategy to deliver personalized, supervised exercise at scale, particularly for patients in underserved or remote areas. When combined with pain neuroscience education, this approach addresses both physical and cognitive aspects of pain, with the potential to improve outcomes beyond current standards of care.
This study aligns with broader public health goals to improve access to effective interventions for chronic pain. Its results may inform future clinical guidelines and support the integration of AI-driven tele-rehabilitation into routine practice for fibromyalgia and related chronic pain conditions.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 50
- Clinical diagnosis of fibromyalgia according to the American College of Rheumatology criteria.
- Age between 18 and 65 years.
- Access to an internet-connected device (smartphone or computer).
- Ability to participate in a tele-rehabilitation program.
- Participation in another clinical trial in the last 3 months.
- Pregnancy or breastfeeding.
- Uncontrolled severe medical conditions that could interfere with the intervention (e.g., cardiac or pulmonary diseases).
- Physical or cognitive impairments that prevent following the exercise program.
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- PARALLEL
- Primary Outcome Measures
Name Time Method Change in Pain Intensity Measured by Visual Analog Scale (VAS) 12 weeks Pain intensity will be measured using the Visual Analog Scale (VAS), which ranges from 0 (no pain) to 10 (worst pain imaginable). Participants will rate their pain at baseline and after 12 weeks of intervention. Higher scores indicate a worse outcome (greater pain intensity). The primary outcome focuses on changes in pain intensity from baseline to the end of the 12-week period.
- Secondary Outcome Measures
Name Time Method Change in the Impact of Fibromyalgia on Daily Life Measured by the Revised Fibromyalgia Impact Questionnaire (FIQ-R) 12 weeks The impact of fibromyalgia on daily life will be assessed using the Revised Fibromyalgia Impact Questionnaire (FIQ-R), a tool that measures the overall burden of fibromyalgia on patients through three key domains: overall impact on daily life, severity of specific symptoms, and functional ability in daily tasks. The FIQ-R provides a comprehensive score ranging from 0 to 100, where higher scores reflect a worse outcome (indicating a greater negative impact of fibromyalgia on daily life). This primary outcome measure will evaluate changes in the total FIQ-R score from baseline to the end of a 12-week intervention period.
Lower Limb Strength and Endurance Measured by the 30-Second Sit-to-Stand Test 12 weeks The 30-second sit-to-stand test measures lower limb strength and endurance by counting the number of times a participant can stand up from a seated position and sit back down within 30 seconds. Higher scores indicate a better outcome (greater strength and endurance). This test serves as a reliable indicator of overall physical function and has been validated for remote use (Bowman et al., 2023). The test will be conducted at baseline and after 12 weeks of intervention.
Change in Quality of Life Measured by EQ-5D 12 weeks Quality of life will be assessed using the EQ-5D (EuroQol-5 Dimension), a standardized measure to evaluate health-related quality of life. The EQ-5D examines five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Scores range from -0.59 to 1, where higher scores indicate a better quality of life. Scores will be compared from baseline to the end of the 12-week intervention.
Change in Psychological Well-being Measured by the Numeric Rating Scale for Anxiety (NRS-A) 12 weeks The NRS-A is a simple, validated tool that allows patients to rate their level of anxiety on a scale of 0 to 10, where 0 indicates 'no anxiety' and 10 represents 'the worst imaginable anxiety.' Anxiety levels will be measured at baseline and after 12 weeks of intervention.
Perceived Barriers to Treatment Adherence Measured by the Treatment Adherence Barriers Questionnaire 12 weeks The Treatment Adherence Barriers Questionnaire identifies perceived barriers that patients face in adhering to treatment recommendations. This measure provides valuable insights into factors affecting adherence and will be evaluated at baseline and after 12 weeks.
Trial Locations
- Locations (1)
Universidad San Sebastián
🇨🇱Concepción, Región del Biobío, Chile
Universidad San Sebastián🇨🇱Concepción, Región del Biobío, ChileMarco Morales-Osorio, PhDPrincipal InvestigatorRomualdo Ordoñez, MscContact+56 9 8225 6426kine.ordonez@gmail.comRobinson Ramirez-Velez, PhDSub InvestigatorTatiana Ordoñe-Mora, PhDSub Investigator