Pediatrics massage evidence map
Bibliographic record
Abstract
BACKGROUND: This evidence map describes Pediatrics Massage intervention research reporting health outcomes. Massage is a complementary therapy and can be defined as any form of systematic tactile stimulation by human hands, the type of massage typically used in pediatrics care is a gentle, slow stroking of each part of the body in turn. METHODS: The evidence map is based on the 3iE evidence gap map methodology. We searched four electronic databases from inception to November 2019 and included systematic reviews and non-systematic reviews. Systematic reviews were analyzed based on AMSTAR 2. We used tableau to graphically display confidence level, number of reviews, outcomes and a broad estimate of effectiveness. RESULTS: The map is based on 38 reviews. Most of the reviews were published in the last ten years. The Pediatrics Massage was the most researched intervention. Massage was evaluated as an intervention in several health outcomes, resulting in the following confidence levels: 11 high, 13 moderate and 14 low. Every outcome effect was classified: 6 as no effect; 1 mixed and 28 as positive. The outcomes were divided into four major groups: physical and metabolic effects; vitality, well-being and quality of life, mental health; and management. High quality studies presented no effect and positive effects, highlighting outcomes related to neuro-motor development (Badr et al., 2015; Bennett et al., 2013; Vickers et al., 2015), growth (Badr et al., 2015; Bennett et al., 2013; Vickers et al., 2015) and stress disorders (Bennett et al., 2013; Vickers et al., 2015). CONCLUSIONS: Pediatrics massage has been applied in different areas and these Evidence Gap Map provides an easy visualization of valuable information for patients, health practitioners and managers, in order to promote evidence-based complementary therapies.
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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 | 0.014 | 0.104 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.037 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.058 | 0.010 |
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".