JMIR Publications

ABSTRACT

Background:

Pain fluctuations are common in chronic musculoskeletal conditions, with periods of increased pain severity, known as pain flares, often occurring alongside worsening disease activity. These painful episodes can lead to significant impacts, including functional disability, emotional distress, and a lower quality of life. Advances in digital technologies, such as smartphones and wearable devices, can now capture individual time-vary information and provide insights into pain patterns and associated factors.

Objective:

To characterise pain flares and identify associated factors in rheumatoid arthritis by 1) describing the frequency and duration of pain flares using progressively stringent definitions based on pain severity, and 2) exploring associations between pain flares and temporal changes in symptoms across emotional, cognitive and behavioural domains.

Methods:

Our 30-day mHealth study collected daily pain severity and related symptoms (score 1-5, higher are worse) via a smartphone app and passively recorded sleep and physical activity via a wrist-worn accelerometer. Pain flares were defined using a 5-point scale, including 1) above average: pain severity > personal median, 2) above threshold: pain severity > 3, and 3) move above threshold: pain severity moves from 1, 2, 3 to 4 or 5. A case-crossover analysis compared within-person variations of daily symptoms across hazard (three days before a pain flare) and control (three days which did not precede a pain flare) periods using mean and intraindividual standard deviation. Conditional logistic regression estimated the odds ratio (OR) for pain flare occurrence.

Results:

A total of 195 participants (82.1% females; mean age: 57.2; average years with RA: 11.3) contributed 5290 days of data. Of these, 88.7% experienced at least one above average flare (median monthly rate: 4, IQR 2.1-5). Nearly half experienced at least one above threshold or move above threshold flare (median monthly rate: 2, IQR 1-4). These pain flares lasted two days (IQR 2-3) on average across definitions, with some extending up to 12 days. Worsening mood over three days was associated with a twofold increase in the likelihood of above threshold flares the following day (OR 2.04, IQR 1.06-3.94). Greater variability in anxiety, sleepiness and fatigue over three days also increased the likelihood of above threshold or move above threshold flares. Sedentary time (hr) consistently showed almost no influence across all definitions. Similarly, the simplest definition of above average demonstrated no significant associations across all symptoms.

Conclusions:

Pain flares, as defined by pain severity, were commonly observed in rheumatoid arthritis. Changes in sleep patterns and emotional distress were associated with the occurrence of pain flares. This analysis demonstrates the potential to identify pain flares using daily data, opening opportunities for timely monitoring and personalised management.