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This study relies on the use of a smartphone application (SOMA) that the investigators developed for tracking daily mood, pain, and activity status in acute pain, chronic pain, and healthy controls over four months.The primary goal of the study is to use fluctuations in daily self-reported symptoms to identify computational predictors of acute-chronic pain transition, pain recovery, and/or chronic pain maintenance or flareups. The general study will include anyone with current acute or chronic pain, while a smaller sub-study will use a subset of patients from the chronic pain group who have been diagnosed with chronic low back pain, failed back surgery syndrome, or fibromyalgia. These sub-study participants will first take part in one in-person EEG testing session while completing simple interoception and reinforcement learning tasks and then begin daily use of the SOMA app. Electrophysiologic and behavioral data from the EEG testing session will be used to determine predictors of treatment response in the sub-study.
Full description
The investigators aim to study the temporal dynamics of pain and links between self-reported pain, mood/emotion, and activities using the daily tracking app SOMA. The experience of pain fluctuates over time, specifically in patients who suffer from chronic pain and those who are transitioning from an acute to a chronic state. Emotions and mood directly influence the experience of pain and may contribute to its chronification. The investigators will use statistical and computational approaches to better understand the dynamics of these reported daily symptoms to identify computational predictors of transition from acute to chronic pain. Specifically, the investigators hypothesize that certain symptom clusters will co-occur in time and be linked to external life events (e.g. emotional and physical stress) and emotional states (e.g. worry). Statistical/computational analysis of pain dynamics could therefore identify indicators for change points in the transition from acute to chronic pain.
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Inclusion and exclusion criteria
INCLUSION CRITERIA [General study]
Chronic pain group:
Acute pain group:
Age above 18
Access to a personal smartphone and a stable internet connection
Average pain intensity score of greater than 3 in the past week
○ or
Average pain interference score of greater than 3 in the past week
○ or
Average pain distress score of greater than 3 in the past week
Pain duration: less than 3 months
Pain cause: Due to recent surgery, injury, acute illness, or childbirth (within the past 3 months)
Healthy control group:
In person EEG testing [Sub-Study only]:
EXCLUSION CRITERIA [General study]
Chronic pain group:
Acute pain group:
Healthy control group:
History of Chronic Pain (Pain lasting for more than 6 months)
difficulty participating for technical/logistical issues (e.g., no computer, incompatible smartphone, can't commit to 4 months study participation);
Not fluent in English (difficulty understanding questions)
-In person EEG testing [Sub-study only]: [will interfere with EEG data collection safety or quality]:
Same as in General App Study Above and additionally:
Baldness
Pregnancy
Dreadlocks
Left-handedness
Use of a wheelchair
Heart failure diagnosis
Current or prior experience with acute psychosis or mania
implanted pacemaker, neurostimulator or any other head or heart implants
require a hearing aid to hear properly
claustrophobia
metal fragments in the body
800 participants in 3 patient groups
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Central trial contact
Chloe S Zimmerman, MD/PhD student; Frederike H Petzschner, PhD
Data sourced from clinicaltrials.gov
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