Currently submitted to: JMIR Research Protocols
Date Submitted: Jul 29, 2026
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Linking consumer health measures from smartphones and wearables with UK national data assets: Protocol for Physical Activity Patterns after Knee Arthroplasty (PAPrKA), a retrospective cohort study
ABSTRACT
Background:
Knee replacement surgery is performed for people with end-stage knee osteoarthritis to reduce pain and improve activity participation. However, patients have limited evidence on how quickly they can expect to return to normal physical activity after surgery, and how much better their activity will get. Smartphones and consumer-grade wearables capture step count data on individuals' devices. Linked with detailed surgical information, these data could provide a unique opportunity to address this question. However, linking consumer data with national health data, which are currently held separately, is uncharted territory and comes with operational challenges.
Objective:
This study has two objectives. The first is to describe physical activity patterns after knee replacement surgery in people with knee osteoarthritis, and the second is to understand how researchers can successfully conduct retrospective cohort studies that link consumer activity data collected through smartphones and consumer wearables with national health datasets through this worked example.
Methods:
We aim to recruit up to 1,000 people aged 18 or older who had knee osteoarthritis and a knee replacement in England, Wales, Northern Ireland, Isle of Man, or Guernsey between 1st January 2017 to 31st December 2023. Participants are eligible if they used Fitbit, Apple (iPhone or Apple Watch), or Oura Ring devices to track physical activity in the six months before and one year after surgery. Study participants will have to complete three tasks: answer questions about their surgery, provide identifiers for linkage, and provide access to physical activity information from their devices. Physical activity data will be linked to an extract of data from their surgical health record in the National Joint Registry. The primary outcome for the first objective will be post-operative relative daily step count, calculated by dividing post-operative daily step count by a pre-operative baseline level. We will assess the extent to which step count increases post-surgery using linear mixed-effects models and explore trajectory groupings using latent class mixed models. For the second objective, we will summarise sources of referral to the study and their corresponding conversion rate, cumulative recruitment numbers, website engagement, representativeness, and completeness of physical activity data.
Results:
The study started recruitment in November 2025, with 132 participants onboarded as of 24 June 2026. We will complete recruitment on 31 July 2026 and aim to publish results by December 2026.
Conclusions:
Understanding how physical activity changes after knee replacement surgery could help patients and clinicians make more informed decisions based on anticipated future physical activity levels and recovery patterns. Through this worked example, we will generate learning about how to conduct retrospective cohort studies linking consumer health measures to national healthcare datasets, particularly regarding recruitment and study onboarding. Clinical Trial: ISRCTN41610298
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