Developing a Music Listening mHealth Intervention for Stress Reduction in Early Recovery
CalmiFy
2 other identifiers
observational
30
1 country
1
Brief Summary
The overarching goal of this study is to develop and examine the feasibility of a music-listening intervention that can be deployed in "real time" to regulate emotions and reduce momentary stress among young adults within the first 12 months of recovery from alcohol use disorder. We design the study with two phases to address three aims: Phase I includes the first two aims. For Aim 1, we will conduct formative research with a sample of young adults (N = 30) who have are within 12 months of recovery to identify features of music selections that are most effective in reducing momentary stress in real-world, ambulatory settings. For Aim 2, we will focus on developing mobile health technology that uses passive sensing and machine learning to automatically predict moments of heightened stress in real-time and suggest specific musical selections when stress is detected. During Phase II (Aim 3), we will test the feasibility of a novel music-listening intervention among a second unique sample of young adults who are within 12 months of recovery from AUD (N = 30). This protocol refers only to Phase I of the larger study, which focuses on observing music listening preferences and physiological and mental stress among people in early recovery from alcohol use disorder.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for all trials
Started May 2025
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
May 19, 2025
CompletedFirst Submitted
Initial submission to the registry
June 26, 2025
CompletedFirst Posted
Study publicly available on registry
July 4, 2025
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 30, 2026
ExpectedStudy Completion
Last participant's last visit for all outcomes
June 30, 2026
July 23, 2025
July 1, 2025
1.1 years
June 26, 2025
July 18, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (5)
Electrodermal Activity (EDA)
EDA will be assessed via a research-level wearable sensor (Empatica EmbracePlus) that will collect continuous physiological data
14 days
Heart Rate Variability (HRV)
HRV will be assessed via a research-level wearable sensor (Empatica EmbracePlus) that will collect continuous physiological data
14 days
Music Listening History
Music listening history will be collected via Spotify by requesting a complete streaming history record for each participant during the study period.
14 days
Self-Reported Acute Stress
Participants will be instructed to press an "event marker" button on the EmbracePlus sensor device during moments that they feel more stressed than usual.
14 days
Self-Reported Positive and Negative Emotions
Participants will report perceptions of positive and negative emotions via the surveys, administered four times each day.
14 days
Secondary Outcomes (3)
Satisfaction with Study
Within 7 days of completing the study.
Time-line followback (TLFB) measure of alcohol use
Within 7 days of study completion.
Recollections of stressful events
Within 7 days of study completion.
Study Arms (1)
Cohort 1
Main study cohort
Eligibility Criteria
Participants will recruited from behavioral health clinics and the general Spokane, WA community.
You may qualify if:
- Subject can and has signed an Institutional Review Board (IRB) approved informed consent form (ICF).
- Age ≥18 and ≤35 years.
- In early-stage recovery for alcohol use (within 12 months)
- Own a smartphone with a data plan
- Not experiencing symptoms of severe depression
- Not experiencing thoughts of suicide
- Meets the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) diagnostic criteria for alcohol use disorder (AUD)
- Not currently taking medication treatment for opioid use disorder (OUD)
- Able to speak and read English
You may not qualify if:
- Currently experiencing symptoms of severe depression
- Currently experiencing thoughts of suicide
- Currently taking medication treatment for opioid use disorder (OUD)
- Are unable to provide voluntary informed consent.
- Cannot read or speak English.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Washington State University Research Clinic
Spokane, Washington, 99202, United States
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Michae J Cleveland, Ph.D.
Washington State University
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
June 26, 2025
First Posted
July 4, 2025
Study Start
May 19, 2025
Primary Completion (Estimated)
June 30, 2026
Study Completion (Estimated)
June 30, 2026
Last Updated
July 23, 2025
Record last verified: 2025-07
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP, ANALYTIC CODE
- Time Frame
- Sharable scientific aggregate data generated from this project will be made available as soon as possible, and no later than 3 years past the end of the funding period. The duration of preservation and sharing of the data will be a minimum of 5 years after the funding period.
- Access Criteria
- Individuals from the scientific community will be able to access the IPD and supporting information. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset
In order to advance the state of the art for the entire research community, we will make a number of our resources for the physiological data (collected via the sensor device) publicly available on our project web page. These resources include our algorithms and software for stress monitoring and predictive models. Source code for these tools will be available, together with documentation on how to use the software and sample artificially-created datasets. The process of software dissemination will be as follows. Once the software package and the supporting pedagogical materials are mature and have been tested, we will make them available via an open-source distribution on the project website, which will include link to GitHub repositories for these resources.