Preprint A Digital Platform with Activity Tracking for Energy Management Support in Long COVID: A Randomised Controlled Trial, 2025, Hayes et al

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A Digital Platform with Activity Tracking for Energy Management Support in Long COVID: A Randomised Controlled Trial

Lawrence Hayes, Nilihan Sanal-Hayes, Jacqueline Mair, Antonio Dello Iacono, Joanne Ingram, Jane Ormerod, David Carless, Natlie Hilliard, Marie Mclaughlin, Rachel Meach, Nicholas Sculthorpe

Abstract
People with long COVID (LC) report worsening symptoms after activity, like post-exertional malaise (PEM) in chronic fatigue syndrome (CFS). The National Institute for Health and Care Excellence (NICE) recommends ‘energy management’ for CFS, but at the time of writing, how people with LC would respond to energy management was unknown.

In a 6-month pragmatic decentralised randomised controlled trial (RCT), we compared a just-in-time intervention to support energy management in adults with LC to standard care. Participants were randomised to receive either the ‘Pace Me’ app and a wearable activity tracker (intervention) or an app only with data entry screens (control). The intervention group received just-in-time messages on PEM management when they reached 50%, 75%, and 100% of their daily ‘activity allowance’. The primary outcome was PEM measured by the DePaul Symptom Questionnaire-Post-Exertional Malaise (DSQ-PEM).

Of 368 participants assessed for eligibility, 250 participants were randomised 1:1, but 36 control and eight intervention participants were lost to follow-up. 12 control and 24 intervention participants were excluded from analysis due to missing data. 84 intervention participants and 77 control participants were analysed. There was no time by group interaction for the DSQ-PEM. The intervention group value was 48 (95% CI 44–53) pre-intervention and 46 (95% CI 41–51) post-intervention (arbitrary units). The control group value was 47 (95% CI 42–52) pre-intervention and 44 (95% CI 39–49) post-intervention (interaction effect p = 0.614, η²p = 0.002; trivial). No individual question exhibited an interaction effect (P > 0.05).

Digitally supported energy management in people with LC had no effect on PEM compared to standard care. Although the intervention had no additional effect compared to control, the substantial recovery rate in LC may have masked intervention effects. Therefore, future studies should consider this energy management framework in conditions without such recovery rates, such as CFS.

Link | PDF (Preprint: Research Square) [Open Access]
 
The intervention used a personalised activity allowance, initially set to no more than 30 minutes of activity above 60% of their age-predicted heart rate maximum. This allowance was iteratively adjusted in response to participants’ activity and PEM reports. If participants reported PEM and had exceeded the allowance, the allowance remained unchanged (i.e. the PEM may be due to poor pacing). If participants reported PEM but had remained within their allowance for the preceding 3 days, the allowance was reduced in a stepwise fashion (i.e. activity allowance may be too large to prevent PEM). Conversely, the allowance was increased if participants did not report PEM for three consecutive weeks. For participants with unstable heart rates (e.g. autonomic issues), step counts were used to set activity allowance. These limits were not intended as targets but as a guide for energy management.
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The bolded section is literally pacing up.

If their aim was to reduce PEM - why did they encourage the participants to do more once they’ve managed to avoid PEM for a short while?
 
This is the first study of its kind to examine digital technology to support energy management in conditions with PEM. We rigorously tested guided energy management in this randomised controlled trial (RCT), the first since the landmark PACE Trial, published over a decade ago 22.
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This statement is a bit worrying..
 
A consequence of these findings is that, for most individuals (excluding a small proportion who may develop a more persistent post-viral condition), LC differs from conditions like ME/CFS, where recovery can take years or may not occur at all. Consequently, the effectiveness of this type of activity-tracking just-in-time intervention is less certain for individuals with ME/CFS, who are unlikely to experience significant recovery or symptom reduction within the timeframe of such trials.
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I don’t understand the last sentence. Would it not be beneficial if an intervention prevented worsening - which is a plausible result for some pwME/CFS if pacing properly?
 
Couple of things from a quick skim of the PDF:

Exclusion Criteria
Participants were excluded if they (1) had insufficient English language to understand messages, (2) had no smartphone access, (3) were participating in another LC intervention, (4) had impaired cognitive function which compromises comprehension of study information or messaging, (5) were receiving therapies known to cause symptom exacerbations (e.g. chemotherapy) or aimed at treating LC, (6) or (6) were receiving ongoing care for LC via primary or secondary care services.
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That suggests their participants were on the milder end of LC, because those with more severe symptoms would have been more likely to already be on a GP or specialist care pathway and so ineligible for the study?


(from Discussion)
it is possible that some control participants used their own activity tracker or app to modify and manage their activity. For example, part way through the trial a commercial app aimed at energy management was launched and some control participants may have decided to use that app
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A second limitation, although necessary, was that we provided activity trackers to the intervention group but not the control group. The reason we believed this necessary was provision of a wearable would be in itself a form of intervention. As such, it is possible that similar frequency and severity of PEM existed between the two groups despite differences in physical activity, but due to our design we cannot examine this.
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This is a flawed argument. A controlled placebo does not mean ‘no intervention’, it means to try to replicated every aspect of the intervention except for the part you want to measure the relative effect of. If the app was the thing they believed would create an effect - they could have given everyone a fitbit.
 
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The intervention integrated heart rate and step count feedback using Fitbit Charge 5, logging of PEM, logging of symptoms, and support messaging when patients exceeded their energy allowance (see supplementary information 1 for full details of the intervention).
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I can’t find this. There are only two images in the supplementary files. Including this weirdly labeled graph (image file is named days without PEM):
fcb4756781c616239040cc4c.tif

I would have put the months on the left axis and plotted the intervention with solid colours and the control with just the outline.

Edit: I would also have flipped the axes - time is usually on the x-axis.
 
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Yeah it’s weird. If the point is to avoid PEM. Try pacing strict.

If the point is to test that some softened “PEM aware” version of Graded Activity Management would work for pwLC, why did they have PEM as a primary outcome, and not something like FUNCAP. I mean you'd want something that can show improvement in the functioning. I guess they kind of removed the step data from the abstract since it didn't show any difference.

Also noting that the DePaul Symptom questionnaire they use measures something more like long lasting fatigue after exertion, than PEM.
 
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InitialConditions said:
That is deliberate. The paper is a pre-print so this will be how the journal expects the manuscript; usually they ask for figures as separate files or collated at the end of the document.
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I’m confused. Is this normal for pre-prints? It’s the first time I’ve come across it.

I can understand that they would send it to the publisher like that, but not that the published preprint wouldn’t include the figures in the correct place.

Is it just how the platform works - you can’t insert figures?
 
Utsikt said:
I’m confused. Is this normal for pre-prints? It’s the first time I’ve come across it.

I can understand that they would send it to the publisher like that, but not that the published preprint wouldn’t include the figures in the correct place.

Is it just how the platform works - you can’t insert figures?
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I don't know exactly how it works, but pre-prints are not yet typeset in the journal style, so it is common to upload the submission file and separate files for figures, but I'm sure you'd find pre-prints where the figures are inline.
 
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