Massage therapy for paediatric procedural pain: A rapid review
Bibliographic record
Abstract
BACKGROUND: Pain is a common paediatric problem, and procedural pain, in particular, can be difficult to manage. Complementary therapies are often sought for pain management, including massage therapy (MT). We assessed the evidence for use of MT for acute procedural pain management in children. METHODS: We searched five main databases for (i) primary studies in English, (ii) included children 0 to 18 years of age, (iii) compared MT for procedural pain management to standard care alone or placebo, and (iv) measured pain as the primary or secondary outcome. The data were extracted by one author and verified by a second author. Randomized controlled trials were evaluated using the Cochrane Risk of Bias tool. RESULTS: Eleven paediatric trials of procedural pain in neonatal, burn, and oncology populations, a total of 771 participants, were identified. Eight reported statistically significant reductions in pain after MT compared to standard care. Pain was measured using validated pain scales, or physiologic indicators. The studies were heterogeneous in population, techniques, and outcome measures used. No adverse events associated with MT were identified. CONCLUSION: MT may be an effective nonpharmacologic adjunct for management of procedural pain in children.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".