Personalized Exercise for Chronic Pelvic Pain
(WorkoutCPP Trial)
What You Need to Know Before You Apply
What is the purpose of this trial?
WorkoutCPP is a pilot study evaluating the feasibility of a personalized exercise recommendation system for individuals with chronic pelvic pain disorders (CPPDs). The study uses reinforcement learning (RL), a type of artificial intelligence that adapts recommendations over time based on each participant's reported pain levels, symptom burden, and exercise compliance. Participants receive daily exercise recommendations that alternate between standard, non-personalized guidance and personalized, RL-generated recommendations across four 2-week phases, allowing within-person comparison of outcomes under each condition. The primary hypothesis is that an RL-based adaptive recommendation system is feasible to deliver in a CPPD population.
Who Is on the Research Team?
Ipek Ensari, PhD
Principal Investigator
Icahn School of Medicine at Mount Sinai
Stefan Konigorski, PhD
Principal Investigator
Department of Computational Precision Nutrition, German Institute of Human Nutrition
Are You a Good Fit for This Trial?
This trial is for adults with chronic pelvic pain conditions, such as chronic prostatitis or endometriosis. Participants should be able to follow daily exercise routines and report their symptoms regularly.Inclusion Criteria
Exclusion Criteria
What Are the Treatments Tested in This Trial?
Interventions
- Reinforcement Learning (RL)-Based Personalized Exercise Recommendations
Trial Overview
The study compares standard exercise advice with personalized recommendations created by an AI system that adapts based on each person's pain and activity levels. Each participant tries both approaches in alternating phases.
How Is the Trial Designed?
2
Treatment groups
Experimental Treatment
Active Control
Participants will receive RL-generated personalized exercise recommendations, which are generated using the list from the initial participant intake form indicating their capacity and resources for carrying out various modalities and intensities of physical activity. The RL agent learns from the participant feedback to update the update the subsequent recommendations.
Participants will receive standardized, non-personalized exercise recommendations based on the U.S. Physical Activity Guidelines, in 2-week blocks. This comparison will serve as the "active control" arm to which the experimental RL arm will be compared. This type of control condition was selected to provide a more rigorous test of the experimental condition.
Find a Clinic Near You
Who Is Running the Clinical Trial?
Icahn School of Medicine at Mount Sinai
Lead Sponsor
Hasso Plattner Institute, Potsdam, Germany
Collaborator
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