Wearable Respiratory Monitoring and Feedback for Chronic Pain in Adult Survivors of Childhood Cancer: A Feasibility Randomized Controlled Trial From the Childhood Cancer Survivor Study
Bibliographic record
Abstract
PURPOSE: Approximately 40% of childhood cancer survivors experience chronic pain, with many also reporting pain-related disability. Given associations established in the general population among respiration, anxiety, and pain, continuous tracking and feedback of respiration may help survivors manage pain. METHODS: A feasibility, nonblinded, randomized controlled trial (RCT) comparing wearable respiratory monitoring with a control group examined feasibility, acceptability, and preliminary efficacy among survivors of childhood cancer with chronic pain who were ≥ 18 years of age, able to speak and read English, lived in the United States, and had access to a smartphone and the Internet. The primary outcomes were pain interference, pain severity, anxiety, negative affect, and perceived stress. The intervention group (n = 32) received a wearable respiratory monitor, used the device, and completed an in-application breathing exercise daily for 30 days. The control group (n = 33) received psychoeducation after completion of the study. RESULTS: = 0.59; 95% CI, 0.09 to 1.10) was significantly greater in the intervention group compared with the control group. A follow-up study (n = 24) examined acceptability and feasibility of a second-generation device among those who completed the RCT. Most survivors (81.0%) wore the device daily during the trial and 85.7% reported satisfaction with the device and the application. CONCLUSION: The results of this pilot study support the acceptability and feasibility of wearable respiratory monitoring among survivors of childhood cancer. Larger randomized trials are needed to assess efficacy and maintenance of this intervention for chronic pain.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".