Integration of Mindfulness and Acupuncture After Spine Surgery: Protocol for a Randomized Acceptability and Feasibility Trial
Bibliographic record
Abstract
Background: Spine surgery is increasingly common in the United States, contributing substantially to spine-related health care costs. While many patients benefit, up to 25% experience chronic postsurgical pain, and the procedure is linked to high rates of opioid misuse. Key risk factors for persistent pain and opioid use include poorly controlled early postsurgical pain, high pain-sensitivity, and poor pain-coping. Clinical guidelines recommend multimodal treatment to address these risks, but such approaches are not well studied or widely implemented. Combining two safe and effective nonpharmacologic treatments, specifically mindfulness and acupuncture that target these factors, has the potential to improve postsurgical recovery and reduce the incidence of chronic pain and opioid use. Objective: This paper describes the study protocol for the Integrating Mindfulness and Acupuncture after Spine Surgery (I-MASS), which is a single-site, 2-arm randomized controlled trial that will assess the feasibility and acceptability of a novel multicomponent program integrating mindfulness delivered via a mobile app, acupuncture, and education for patients undergoing single-level spine surgery. Methods: A total of 50 participants will be randomized 1:1 to receive (1) mindfulness and acupuncture (ie, I-MASS program) plus enhanced education or (2) enhanced education alone. Mindfulness training will consist of a 4-week app-based program starting 1 week prior to surgery, and acupuncture will include up to 8 visits (1 visit prior to surgery and 7 after surgery) during the 13-week program. Enhanced education appropriate for each phase of recovery will be delivered through the mobile app. Primary outcomes are recruitment eligibility and enrollment rates, mindfulness module and acupuncture visit completion rates, questionnaire completion rates, and participant satisfaction. Secondary outcomes include physical function, fatigue, pain interference, depressive symptoms, anxiety, ability to participate in social roles and activities, sleep disturbance, fear avoidance beliefs, pain intensity, pain medication use, adverse events, hospital readmissions, and emergency department visits. Results: Trial enrollment began in August 2024. As of May 9, 2025, 35 participants have been enrolled. Data analysis has not yet been performed. Enrollment is expected to be completed in the fall of 2025. Conclusions: The I-MASS program addresses the need for mind and body treatments to improve recovery and reduce the risk of persistent pain and opioid use after spine surgery. This integrated model of care is designed to be user-friendly and scalable, enhancing its potential for implementation in real-world settings. A future pragmatic trial is planned to determine if the I-MASS program results in better outcomes compared to either treatment alone or usual care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.050 | 0.042 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.092 | 0.016 |
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 source (direct Gemma or distilled Codex), 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".