Title: Using Activity Tracking and Just-In-Time Messaging to Improve Adaptive Pacing: A Pragmatic Randomised Control Trial
Funder: Department of Health and Social Care

Abstract: People with long COVID (LC) report 'push-crash' cycles, with a disproportionate worsening of symptoms in response to activity, similar to post-exertional malaise (PEM) reported by patients with chronic fatigue syndrome (CFS). These PEM-like symptoms increase the overall symptom load, reduce each individual's quality of life, and make recovery harder. Adaptive pacing has emerged as a common strategy to self-manage PEM-like symptoms. However, recent work endorsed by our LC PPI group indicates that implementing adaptive pacing is often problematic for those attempting to self-manage. Difficulties include accurately estimating concepts such as energy availability and predicted energy use and identifying and tracking a suitable threshold to limit activity. Combining these requirements to plan daily activities, often hour-by-hour, can be highly challenging, particularly when symptoms include impaired cognition. This project aims to determine if combining continuous activity tracking with a just-in-time adaptive intervention (JITAI) can address these limitations. JITAIs provide information to participants at a time and context where they can act upon it. Widely used in behaviour change research, JITAIs are yet to be applied to adaptive pacing. Using a randomised control study design, we will allocate 220 participants to receive either JITAI supported adaptive pacing or usual care. Our primary outcome is patient-reported symptoms, and secondary outcomes are frequency of PEM-like episodes and objective measures of cognitive and autonomic function. Intervention participants will wear an activity tracker to manage personalised activity thresholds, which will be linked to changes in symptom severity. A companion smartphone app will deliver real-time alerts as participants reach their activity threshold. The app also tracks self-reported symptom severity and objective measures of cognitive and autonomic function weekly. A benefit of this application is that we have already developed the required technology (messaging, activity tracking, and smartphone app), enabling rapid progression to data collection.

Lay abstract: Long-COVID symptoms change regularly, often getting worse after activity. Adaptive pacing (AP) is a way for people who experience these symptoms to better manage their day-to-day activity. AP needs people to continuously track their daily activities and balance what they plan to do with how much energy they feel they have. However, this is not always easy because the amount of activity that will cause symptoms to get worse is different for everyone. Also, individuals must keep track of their activity (perhaps for several days) which can also be challenging, particularly if poor memory is a symptom. With help from people with long-COVID, we have designed a project to make AP easier for people with long-COVID to use. We will track activity for them and send alerts if they risk doing too much. The aim is to help individuals better plan their day-to-day activities and prevent periods where symptoms become worse. We will recruit two groups; one will follow the standard AP advice, and the other will try our modified AP approach. We will ask this group to wear a Fitbit activity monitor and download a mobile phone app designed by us. We will use the information from the Fitbit to keep track of each participants activity level. We will then send alert messages if it looks like they might do too much. This way, each person has their own AP plan. The activity and messaging support will last for three months. Afterwards, we will review how effective it was by comparing them to the usual care group. If this approach works, we will see if the tracking and messages can be improved and offer this to the control group so they can also benefit. We will also look for ways to scale up the process to help more people.

Research activity codes: 7.1 INDIVIDUAL CARE NEEDS;6.7 PHYSICAL
Health categories: INFECTION