App-Based Mindfulness Meditation for People of Color Who Experience Race-Related Stress: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: People of color (POC) who experience race-related stress are at risk of developing mental health problems, including high levels of stress, anxiety, and depression. Mindfulness meditation may be especially well suited to help POC cope, given its emphasis on gaining awareness and acceptance of emotions associated with discriminatory treatment. However, mindfulness meditation rarely reaches POC, and digital approaches could reduce this treatment gap by addressing traditional barriers to care. OBJECTIVE: This study will test the effectiveness of a self-directed app-based mindfulness meditation program among POC who experience elevated levels of race-related stress. Implementation outcomes such as treatment acceptability, adherence, and satisfaction will be examined. METHODS: Participants (n=80) will be recruited online by posting recruitment materials on social media and sending emails to relevant groups. In-person recruitment will consist of posting flyers in communities with significant POC representation. Eligible participants will be block randomized to either the intervention group (n=40) that will complete a self-directed 4-week mindfulness meditation program or a wait-list control condition (n=40) that will receive access to the app after study completion. All participants will complete measures at baseline, midtreatment, and posttreatment. Primary outcomes include changes in stress, anxiety, and depression, and secondary outcomes constitute changes in mindfulness, self-compassion, rumination, emotion suppression, and experiential avoidance. Exploratory analyses will examine whether changes in the secondary outcomes mediate changes in primary outcomes. Finally, treatment acceptability, adherence, and satisfaction will be examined descriptively. RESULTS: Recruitment began in October 2021. Data will be analyzed using multilevel modeling, a statistical methodology that accounts for the dependence among repeated observations. Considering attrition issues in self-directed digital interventions and their potential effects on statistical significance and treatment effect sizes, we will examine data using both intention-to-treat and per-protocol analyses. CONCLUSIONS: To our knowledge, this will be the first study to provide data on the effectiveness of a self-directed app-based mindfulness meditation program for POC recruited based on elevated race-related stress, a high-risk population. Similarly, meaningful clinical targets for POC affected by stressors related to race will be examined. Findings will provide important information regarding whether this type of intervention is an acceptable treatment among these marginalized groups. TRIAL REGISTRATION: ClinicalTrials.gov NCT05027113; https://clinicaltrials.gov/ct2/show/NCT05027113. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35196.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".