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.
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[General Study] Acute-Chronic Pain Transition Probability
Timeframe: T1 [4 months of daily app use]