Systematic Review of Massage Intervention for Adult Patients With Cancer
Bibliographic record
Abstract
In Brief Findings from studies of massage, one of the most commonly used nonpharmacological nursing interventions for managing cancer pain, are inconsistent. The purpose of this article was to elucidate the methodological underpinnings of these inconsistencies with a systematic review of study design, methods, and massage efficacy in adult patients with cancer. A total of 15 studies published in English between 1986 and 2006 were identified by searching in 6 electronic databases. An author-developed tool and an adapted assessment tool were used to extract information from each study and examine the quality of reviewed studies. Methodological issues that potentially account for discrepancies across studies included less rigorous inclusion criteria, failure to consider potential confounding variables, less than rigorous research designs, inconsistent massage doses and protocols, measurement errors related to sensitivity of instruments and timing of measurements, and inadequate statistical power. Areas for future study include determination of appropriate cutoff values of selected outcome measures, delivery of equal doses along with standardized massage protocols, examination of length of massage effects over time, and use of single-blinding randomized clinical trials with large sample sizes. Findings from studies of massage, one of the most commonly used nonpharmacological nursing interventions for managing cancer pain, are inconsistent. The purpose of this article was to elucidate the methodological underpinnings of these inconsistencies with a systematic review of study design, methods, and massage efficacy in adult patients with cancer. A total of 15 studies published in English between 1986 and 2006 were identified by searching in 6 electronic databases. An author-developed tool and an adapted assessment tool were used to extract information from each study and examine the quality of reviewed studies. Methodological issues that potentially account for discrepancies across studies included less rigorous inclusion criteria, failure to consider potential confounding variables, less than rigorous research designs, inconsistent massage doses and protocols, measurement errors related to sensitivity of instruments and timing of measurements, and inadequate statistical power. Areas for future study include determination of appropriate cutoff values of selected outcome measures, delivery of equal doses along with standardized massage protocols, examination of length of massage effects over time, and use of single-blinding randomized clinical trials with large sample sizes.
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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 | 0.019 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".