Right-time self-care advice for hip and knee osteoarthritis (e-cOAch)

Developing Data Driven Algorithms for Predicting The Right Advice at The Right Time in Patients With Hip and Knee OsteoArthritis: The e-cOAch Cross-over Study

This project will test whether an online program can use regular symptom and activity reports to predict and deliver the right self-care advice about physical activity, weight, or sleep for people with hip or knee osteoarthritis.

Quick facts

• Phase: Not applicable
• Study type: Interventional
• Enrollment: 600 (estimated)
• Ages: 45 Years and up
• Sex: All
• Sponsor: UMC Utrecht (Academic / other)
• Locations: 1 site (Utrecht)
• Trial ID: NCT07423858 on ClinicalTrials.gov

What this trial studies

Over one year, participants with hip or knee osteoarthritis complete online questionnaires every two weeks about pain, activity, sleep and daily functioning. At four scheduled points they are randomly assigned in a crossover design to one of three 12-week self-care programs (physical activity, weight management, or sleep) or to no program, with no program repeated. The study will use these longitudinal data to build and validate data-driven models that aim to predict symptom changes and the best timing for delivering each self-management strategy via the ArtroseCoach web app. Secondary analyses will look for subgroups, predictors of flare-ups, and links between activity, weight, pain and sleep.

Who should consider this trial

Good fit: Ideal candidates are people aged 45 or older with knee or hip pain for at least 3 months who meet the NICE clinical criteria for osteoarthritis, can read Dutch at B1 level, have a smartphone with internet and are willing to complete regular online assessments.

Not a fit: People with systemic inflammatory arthritis, those scheduled for lower-limb joint surgery within a year, those unable to use a smartphone or Dutch-language materials, or those who do not engage with the app are unlikely to benefit from the program.

Why it matters

Potential benefit: If successful, the models could help deliver personalized self-care advice at times when it is most likely to help, potentially improving symptoms and daily functioning.

How similar studies have performed: Digital self-management programs for osteoarthritis have shown modest benefits, but using high-frequency patient-reported data to predict optimal timing for interventions is a relatively new approach with limited prior evidence.

Eligibility criteria

Inclusion Criteria:

1. Have a hip or knee joint that, self-administered through a questionnaire, meets the National

   Institute for Health and Care Excellence clinical criteria for osteoarthritis:
   1. Aged 45 years or over and;
   2. Activity-related pain at the joint and;
   3. Joint morning stiffness that lasts no longer than 30 minutes or no morning stiffness at the joint;
2. History of pain at the joint for at least 3 months;
3. Have access to a smartphone with internet connection and an email address;
4. Able to give informed consent and willing to commit to all study evaluation and assessment procedures
5. Able to read and understand texts in Dutch at B1 level.

Exclusion Criteria:

1. Self-reported systemic arthritis (e.g., rheumatoid arthritis, gout) avoid confounding due to overlapping symptoms;
2. Scheduled for lower limb joint surgery within the next year or underwent lower limb joint surgery (total hip, total knee) the last year as surgical interventions could affect outcomes and confound the assessment of treatment effects.

Where this trial is running

Utrecht

• UMC Utrecht — Utrecht, Netherlands (Recruiting)

Study contacts

• Principal investigator: Martijn F. Pisters, PhD — UMC Utrecht
• Study coordinator: Femke Groen, MSc

Conditions Osteo Arthritis Knee and Hip; Stepped care; Self-management; Lifestyle behaviours; Movement behaviour; Sleep behaviour; Weight management; Hip and knee osteoarthritis