Acceptability and Feasibility of a Patient-Oriented Music Intervention to Reduce Pain in the Intensive Care Unit: Protocol for a Crossover Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Many patients experience pain in the intensive care unit (ICU) despite receiving pain medication. Research has shown that music can help reduce pain. Music interventions studied so far have not used music streaming to generate playlists based on patient preferences while incorporating recommended tempo and duration. Previous research has focused on postoperative ICU patients able to self-report, which is underrepresentative of the ICU population that might benefit from a music intervention for pain management. We developed a new patient-oriented music intervention (POMI) that incorporates features based on theoretical, empirical, and experiential data intended to be used in the ICU. Such a music intervention should consider the expertise of ICU patients, family members, and nursing staff, as well as the practicality of the intervention when used in practice. OBJECTIVE: The primary objectives of this study are to (1) evaluate the acceptability and feasibility of the POMI to reduce pain in ICU patients and (2) evaluate the feasibility of conducting a crossover pilot randomized controlled trial (RCT) for intervention testing in the ICU. A secondary objective is to examine the preliminary efficacy of the POMI to reduce pain in ICU patients. METHODS: A single-blind 2×2 crossover pilot RCT will be conducted. Patients will undergo 1 sequence of 2 interventions: the POMI which delivers music based on patients' preferences via headphones or music pillow for 20-30 minutes and the control intervention (headphones or pillow without music). The sequence of the interventions will be inverted with a 4-hour washout period. Timing of the interventions will be before a planned bed turning procedure. Each patient will undergo 1 session of music. Twenty-four patients will be recruited. Patients able to self-report (n=12), family members of patients unable to self-report (n=12), and nursing staff (n=12) involved in the bed turning procedure will be invited to complete a short questionnaire on the POMI acceptability. Data will be collected on the feasibility of the intervention delivery (ie, time spent creating a playlist, any issue related to headphones/pillow or music delivery, environmental noises, and intervention interruptions) and research methods (ie, number of patients screened, recruited, randomized, and included in the analysis). Pain scores will be obtained before and after intervention delivery. RESULTS: Recruitment and data collection began in March 2022. As of July 5, 2022, in total, 22 patients, 12 family members, and 11 nurses were recruited. CONCLUSIONS: Methodological limitations and strengths are discussed. Study limitations include the lack of blinding for patients able to self-report. Strengths include collecting data from various sources, getting a comprehensive evaluation of the intervention, and using a crossover pilot RCT design, where participants act as their own control, thus reducing confounding factors. TRIAL REGISTRATION: ClinicalTrials.gov NCT05320224; https://clinicaltrials.gov/ct2/show/NCT05320224. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/40760.
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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 | 0.041 | 0.040 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.052 | 0.008 |
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".