Foot Reflexology and Pain Intensity Among Patients with Advanced Cancer: A Systematic Literature Review
Bibliographic record
Abstract
Managing pain for cancer patients is a critical issue that requires investigations of complementary interventions to achieve comprehensive pain management. This study investigates whether foot reflexology, as a complementary intervention, has an effect on pain intensity management amongst patients with advanced cancer. A systematic literature review focusing on articles published during the period 2019 to 2024, include adult patients with advanced cancer, and implemented foot reflexology for cancer-related pain management was undertaken using different databases. The studies were screened, and eleven studies, including (2396 patients), were eligible for this review published in PubMed, Google Scholar, PsycINFO, and Cochrane Library databases. Critical appraisal of the studies was conducted using JBI Critical Appraisal Checklist and the risk assessment was undertaken based on RoB 2, ROBIS, and adapted ROBINS-I tools. Feasibility studies showed that patients generally accept foot reflexology to help with cancer-related pain. Also, foot reflexology is reported to be effective and has significant effects on reducing cancer-related pain for patients with cancer. The results also indicated that the selection of pain assessment tools should consider the specific clinical context and assessment objectives. In addition, there are some discrepancies in the foot reflexology procedures followed by different researchers; nonetheless, the effectiveness of foot reflexology was demonstrated in all the studies. Foot reflexology is appropriate and can be incorporated to complement cancer patients’ pain management plans. Existing evidence is limited by study designs and implementation procedures. Further research should address these limitations through specific implementation procedures, incorporating diverse populations.
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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 | 0.006 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".