Chronic PainNCT05754190
Assessing Symptom and Mood Dynamics in Pain Using the Smartphone Application SOMA
An observational study of Chronic Pain and Acute Pain, run by Brown University at 1 site in United States.
Trial 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… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Chronic Pain, Acute Pain, Post Operative Pain
- What is being tested?
- SOMA pain manager smartphone application
- Type of treatment
- Medical device
- How many people
- 800 participants
- Where
- 1 siteUnited States
- Study dates
- 20 Jun 2023to 30 May 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
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.
Who may be able to join
- 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
Show all 31Show fewer
- 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
Who cannot join
- 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:
Show all 27Show fewer
- 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
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
Brown University
Providence, Rhode Island, 02912
Frederike H Petzschner, PhD, 401-863-6272, frederike_petzschner@brown.edu
Chloe S Zimmerman, MD/PhD Student, 401-863-6272, chloe_zimmerman@brown.edu
About this study
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.
Read the 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.
- Conditions
- Chronic Pain, Acute Pain, Post Operative Pain, Fibromyalgia, Primary, Fibromyalgia, Secondary, Fibromyalgia
- Being tested
- SOMA pain manager smartphone application
- Keywords
- digital health, e-health, smartphone application, chronic pain, acute pain, symptom tracking, experience sampling methodology, ecological momentary assessment, pain self-management
- Medical subject headings
- Chronic Pain, Acute Pain, Pain, Postoperative, Fibromyalgia, Irritable Bowel Syndrome, Temporomandibular Joint Disorders, Arthritis, Failed Back Surgery Syndrome
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
SOMA pain manager smartphone applicationDevice
SOMA is a smartphone application developed for acute and chronic pain patients to track daily mood and pain symptoms and overall activity.
| Study group | Role | What they receive |
|---|---|---|
| Healthy Controls | [general study + sub study] No history of chronic pain Receives: Device: SOMA pain manager smartphone application | |
| Acute pain | [general study] Pain duration < 3 months Receives: Device: SOMA pain manager smartphone application | |
| Chronic pain | [general study] Pain duration > 6 months
[sub-study] diagnosis of chronic low back pain, failed back surgery syndrome, or fibromyalgia Receives: Device: SOMA pain manager smartphone application |
What is being measured
The primary outcome is the main question the study is designed to answer.
[General Study] Acute-Chronic Pain Transition Probability
Test whether daily affect (incl. mood), pain, activities, and other factors measured by the SOMA app can predict transition from acute to chronic pain, pain recovery, or pain maintenance using mixed effects linear regression model-based analyses to predict long- term pain scores such as pain intensity, unpleasantness, and/or interference
Measured: T1 [4 months of daily app use]
Secondary outcomes (14)
[General Study] Feasibility of long-term app use
Percentage of Soma users in acute and chronic pain groups who engage with the app for 4 months
Measured: T1 [4 months of daily app use]
[General Study] App Engagement
Evaluate user engagement based on number of completed daily ESM assessments per person in the acute and chronic pain groups over the 4 months of app use
Measured: T1 [4 months of daily app use]
[General Study] Pain Dynamics
Test whether variability in daily pain location, intensity, unpleasantness, and interference, and daily pain expectations and prediction errors in the SOMA app can predict long-term pain scores in cross sectional between-group and longitudinal within-subject model-based analyses
Measured: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Activity Dynamics
Test whether types or number of daily activities, the effect of activities on pain, and activity expectations for the next day can predict long-term pain scores in cross sectional and longitudinal model-based analyses.
Measured: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Pain Beliefs
Test whether questionnaire scores related to pain beliefs and personal/health history at T0 can predict long-term pain scores in cross sectional between-group and longitudinal within-subject model-based analyses
Measured: T0 [Baseline], T2 [4 months], T3 [8 months], T4 [12 months]
[General study] Mood Dynamics
Test whether variability in daily mood ratings and mood prediction errors can predict long-term pain scores in cross sectional between-group and longitudinal within-subject model-based analyses.
Measured: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Association between mood, pain, and activity
Assess the effect of mood, pain, pain prediction errors and mood prediction errors on future activities in cross sectional between-group and longitudinal within-subject model based analyses.
Measured: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Mood homeostasis as measured by SOMA app mood screens
Assess mood homeostasis using SOMA mood screens in cross sectional between-group and longitudinal within-subject model based analyses.
Measured: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Effect of Treatments on pain and mood as measured by SOMA app screens
Assess the effect of pain treatments on mood, pain and activities using the dedicated SOMA screens for these measures in cross sectional between-group and longitudinal within-subject model based analyses.
Measured: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Avoidance Learning task-computer game
Test harm avoidance learning and generalization differences between pain patients and healthy controls using a computerized reinforcement learning game.
Measured: T0 [Baseline], T2 [4 months]
[Sub-Study] Avoidance Learning Task-EEG
Test whether EEG frontal theta band power is increased during prediction error processing and harm avoidance contexts in a reinforcement learning task in cross-sectional between-group analyses.
Measured: T0 [Baseline]
[Sub-Study] Cardiac Interoceptive Attention Task-EEG
Test whether cross-sectional differences in EEG-measured Heartbeat-evoked potential (HEP) amplitude when attending to interoceptive vs exteroceptive stimuli differ between pain patients and healthy controls and test relationship to questionnaire measures at baseline and follow-up.
Measured: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[Sub-study] Resting state- EEG
Test cross-sectional differences in EEG-measured Resting State Activity between pain groups and healthy controls and test relationships between resting EEG measures and questionnaire results at baseline and follow-up
Measured: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[Sub-study] Treatment outcome prediction in chronic low back pain and failed back surgery syndrome patients
Test whether baseline EEG HEP and questionnaire measures predict pain scores at T3 following invasive back treatments (eg back surgery, spinal cord stimulation, radio-frequency ablation) that occur during T1.
Measured: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Mar 2023
- Study start20 Jun 2023
- Primary completion30 May 2026 (estimated)
- Study completion30 May 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for Chronic PainStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 800 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Brown University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Frederike Petzschner, Brown University
- Investigators
- Frederike H Petzschner, PhD, Principal investigator, Brown University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05754190
- Sponsor's protocol ID
- 2022003301
- Status last verified
- Sep 2025
- First submitted
- 8 Feb 2023
- Last updated
- 19 Sep 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Anyone interested in IPD should reach out to the Principal Investigator
Publications
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.
PubMed 21148657Apkarian AV, Baliki MN, Farmer MA. Predicting transition to chronic pain. Curr Opin Neurol. 2013 Aug;26(4):360-7. doi: 10.1097/WCO.0b013e32836336ad.
PubMed 23823463Baliki 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.
PubMed 22751038Hashmi 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.
PubMed 23983029Pincus 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.
PubMed 11880847
Study at a glance
From the registry record, last updated by the sponsor on 19 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Assessing Symptom and Mood Dynamics in Pain Using the Smartphone Application SOMA
- ClinicalTrials.gov ID
- NCT05754190
- Acronym / sponsor ID
- 2022003301
- Conditions
- Chronic Pain, Acute Pain, Post Operative Pain, Fibromyalgia, Primary, Fibromyalgia, Secondary, Fibromyalgia
- Keywords
- digital health, e-health, smartphone application, chronic pain, acute pain, symptom tracking, experience sampling methodology, ecological momentary assessment
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 800 participants (estimated)
- Lead sponsor
- Brown UniversityUniversity, hospital or other
- Study start
- 20 Jun 2023 (actual)
- Primary completion
- 30 May 2026 (estimated)
- Study completion
- 30 May 2026 (estimated)
- First posted
- 3 Mar 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Healthy Controls | – | Device: SOMA pain manager smartphone application[general study + sub study] No history of chronic pain |
| Acute pain | – | Device: SOMA pain manager smartphone application[general study] Pain duration < 3 months |
| Chronic pain | – | Device: SOMA pain manager smartphone application[general study] Pain duration > 6 months [sub-study] diagnosis of chronic low back pain, failed back surgery syndrome, or fibromyalgia |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (31 listed)
- Chronic pain group:
- Acute pain group:
- ○ or
- ○ or
- Healthy control group:
Key exclusion criteria (27 listed)
- 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);
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| SOMA pain manager smartphone applicationSOMA is a smartphone application developed for acute and chronic pain patients to track daily mood and pain symptoms and overall activity. | Device | Acute pain, Chronic pain, Healthy Controls |
Primary outcome
[General Study] Acute-Chronic Pain Transition Probability
Time frame: T1 [4 months of daily app use]
Test whether daily affect (incl. mood), pain, activities, and other factors measured by the SOMA app can predict transition from acute to chronic pain, pain recovery, or pain maintenance using mixed effects linear regression model-based analyses to predict long- term pain scores such as pain intensity, unpleasantness, and/or interference
14 secondary outcomes
[General Study] Feasibility of long-term app use
Time frame: T1 [4 months of daily app use]
[General Study] App Engagement
Time frame: T1 [4 months of daily app use]
[General Study] Pain Dynamics
Time frame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Activity Dynamics
Time frame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Pain Beliefs
Time frame: T0 [Baseline], T2 [4 months], T3 [8 months], T4 [12 months]
[General study] Mood Dynamics
Time frame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Association between mood, pain, and activity
Time frame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Mood homeostasis as measured by SOMA app mood screens
Time frame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Effect of Treatments on pain and mood as measured by SOMA app screens
Time frame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[General Study] Avoidance Learning task-computer game
Time frame: T0 [Baseline], T2 [4 months]
[Sub-Study] Avoidance Learning Task-EEG
Time frame: T0 [Baseline]
[Sub-Study] Cardiac Interoceptive Attention Task-EEG
Time frame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[Sub-study] Resting state- EEG
Time frame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
[Sub-study] Treatment outcome prediction in chronic low back pain and failed back surgery syndrome patients
Time frame: T0 [Baseline], T1 [4 months of daily app use], T2 [4 months], T3 [8 months], T4 [12 months]
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Sep 2025.
- Background: PubMed 21148657Voscopoulos C, Lema M. When does acute pain become chronic? Br J Anaesth. 2010 Dec;105 Suppl 1:i69-85. doi: 10.1093/bja/aeq323.
- Background: PubMed 23823463Apkarian AV, Baliki MN, Farmer MA. Predicting transition to chronic pain. Curr Opin Neurol. 2013 Aug;26(4):360-7. doi: 10.1097/WCO.0b013e32836336ad.
- Background: PubMed 22751038Baliki 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.
- Background: PubMed 23983029Hashmi 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.
- Background: PubMed 11880847Pincus 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.
- To find out more about how to download and use the SOMA Pain Manager appLink provided by the sponsor.
- Individual participant dataSharing planned: No. Anyone interested in IPD should reach out to the Principal Investigator
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Frederike H Petzschner, PhD principal investigator
Brown University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Chronic Pain and Acute Pain, run by Brown University at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 31 inclusion and 27 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 19 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Frederike H Petzschner, PhD (401-863-6272, frederike_petzschner@brown.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
[General Study] Acute-Chronic Pain Transition Probability (time frame: T1 [4 months of daily app use]). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05754190, which also lists 5 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Sep 2025.