Clinical trial NCT05754190: Assessing Symptom and Mood Dynamics in Pain Using the Smartphone Application SOMA
Official title: Assessing Symptom and Mood Dynamics in Pain Using the Smartphone Application SOMA
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Chronic Pain
Acute Pain
Post Operative Pain
Fibromyalgia, Primary
Fibromyalgia, Secondary
Fibromyalgia
Irritable Bowel Syndrome
Chronic Headache Disorder
Chronic Migraine
Chronic Pelvic Pain Syndrome
Temporomandibular Joint Disorders
Endometriosis-related Pain
Arthritis
Chronic Low-back Pain
Failed Back Surgery Syndrome
Post Herpetic Neuralgia
Neuropathic Pain
Painful Diabetic Neuropathy
Painful Bladder Syndrome
Trauma-related Wound
Trauma, Multiple
Chronic Pain Syndrome
Chronic Shoulder Pain
Keywords: digital health
e-health
smartphone application
chronic pain
acute pain
symptom tracking
experience sampling methodology
ecological momentary assessment
pain self-management
Lead sponsor: Brown University
Sponsor class: OTHER
First posted: 2023-03-03
Enrollment: 800
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Any person who fits the eligibility criteria for acute pain, chronic pain, or healthy control groups will be eligible to participate in the general parent study. Healthy controls or participants who have a diagnosis of chronic low back pain, failed back surgery syndrom or fibromyalgia are eligible to participate in the in-person EEG sub-study.

Participants will be recruited from around Rhode Island and surrounding regions via online ads, listserv announcements, local healthcare clinics, rehab and nursing facilities, word of mouth, social media, and targeted newspaper/magazine/public transportation advertisements. Chronic pain participants eligible for the in-person EEG testing will be recruited via these methods as well as targeted recruitment with physicians treating these patients.

Brief summary: 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.

Detailed 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.

Eligibility criteria: INCLUSION CRITERIA \[General study\]

* Chronic 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: greater than 6 months
* 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:

  * Age above 18
  * Access to a personal smartphone and a stable internet connection
  * Average pain intensity score of less than 3 in the past week
  * Average pain interference score of less than 3 in the past week
  * Average pain distress score of less than 3 in the past week
  * No surgery, injury, acute illness, or childbirth (within the past 3 months)
* In person EEG testing \[Sub-Study only\]:

  * Same as in General App Study Above and additionally:
  * Current diagnosis of Fibromyalgia, Chronic Low Back Pain or Failed Back Surgery Syndrome OR
  * No current or prior history of chronic pain
  * If participant has chronic low back pain or failed back surgery syndrome: are they planning to have either a radio-frequency ablation, back surgery, or spinal cord stimulation implant in the next few months
  * If participant has chronic low back pain or failed back surgery syndrome: have they received insurance approval for the procedure?
  * Ok with EEC/ECG measures

EXCLUSION CRITERIA \[General study\]

* Chronic pain group:

  * recent injury or surgery unrelated to the pain in the past 3 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)
  * Current primary or metastatic cancer (organic cause of pain)
* Acute pain 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)
  * Current primary or metastatic cancer (organic cause of pain)
* 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

Primary outcomes:
measure: [General Study] Acute-Chronic Pain Transition Probability
timeFrame: T1 [4 months of daily app use]
Secondary outcomes:
measure: [General Study] Feasibility of long-term app use
timeFrame: T1 [4 months of daily app use]
measure: [General Study] App Engagement
timeFrame: T1 [4 months of daily app use]
measure: [General Study] Pain Dynamics
timeFrame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
measure: [General Study] Activity Dynamics
timeFrame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
measure: [General Study] Pain Beliefs
timeFrame: T0 [Baseline], T2 [4 months], T3 [8 months], T4 [12 months]
measure: [General study] Mood Dynamics
timeFrame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
measure: [General Study] Association between mood, pain, and activity
timeFrame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
measure: [General Study] Mood homeostasis as measured by SOMA app mood screens
timeFrame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
measure: [General Study] Effect of Treatments on pain and mood as measured by SOMA app screens
timeFrame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
measure: [General Study] Avoidance Learning task-computer game
timeFrame: T0 [Baseline], T2 [4 months]
measure: [Sub-Study] Avoidance Learning Task-EEG
timeFrame: T0 [Baseline]
measure: [Sub-Study] Cardiac Interoceptive Attention Task-EEG
timeFrame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
measure: [Sub-study] Resting state- EEG
timeFrame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
measure: [Sub-study] Treatment outcome prediction in chronic low back pain and failed back surgery syndrome patients
timeFrame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
Other outcomes:
Locations:
city: Providence
country: United States
facility: Brown University
state: Rhode Island
Study officials:
affiliation: Brown University
name: Frederike H Petzschner, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Voscopoulos C, Lema M. When does acute pain become chronic? Br J Anaesth. 2010 Dec;105 Suppl 1:i69-85. doi: 10.1093/bja/aeq323.
citation: Apkarian AV, Baliki MN, Farmer MA. Predicting transition to chronic pain. Curr Opin Neurol. 2013 Aug;26(4):360-7. doi: 10.1097/WCO.0b013e32836336ad.
citation: Baliki MN, Petre B, Torbey S, Herrmann KM, Huang L, Schnitzer TJ, Fields HL, Apkarian AV. Corticostriatal functional connectivity predicts transition to chronic back pain. Nat Neurosci. 2012 Jul 1;15(8):1117-9. doi: 10.1038/nn.3153.
citation: Hashmi JA, Baliki MN, Huang L, Baria AT, Torbey S, Hermann KM, Schnitzer TJ, Apkarian AV. Shape shifting pain: chronification of back pain shifts brain representation from nociceptive to emotional circuits. Brain. 2013 Sep;136(Pt 9):2751-68. doi: 10.1093/brain/awt211.
citation: Pincus T, Burton AK, Vogel S, Field AP. A systematic review of psychological factors as predictors of chronicity/disability in prospective cohorts of low back pain. Spine (Phila Pa 1976). 2002 Mar 1;27(5):E109-20. doi: 10.1097/00007632-200203010-00017.