A Systematic Review of the Therapeutic Effects of Reiki
Bibliographic record
Abstract
INTRODUCTION: Reiki is an ancient form of Japanese healing. While this healing method is widely used for a variety of psychologic and physical symptoms, evidence of its effectiveness is scarce and conflicting. The purpose of this systematic review was to try to evaluate whether Reiki produces a significant treatment effect. METHODS: Studies were identified using an electronic search of Medline, EMBASE, Cochrane Library, and Google Scholar. Quality of reporting was evaluated using a modified CONSORT Criteria for Herbal Interventions, while methodological quality was assessed using the Jadad Quality score. DATA EXTRACTION: Two (2) researchers selected articles based on the following features: placebo or other adequate control, clinical investigation on humans, intervention using a Reiki practitioner, and published in English. They independently extracted data on study design, inclusion criteria, type of control, sample size, result, and nature of outcome measures. RESULTS: The modified CONSORT Criteria indicated that all 12 trials meeting the inclusion criteria were lacking in at least one of the three key areas of randomization, blinding, and accountability of all patients, indicating a low quality of reporting. Nine (9) of the 12 trials detected a significant therapeutic effect of the Reiki intervention; however, using the Jadad Quality score, 11 of the 12 studies ranked "poor." CONCLUSIONS: The serious methodological and reporting limitations of limited existing Reiki studies preclude a definitive conclusion on its effectiveness. High-quality randomized controlled trials are needed to address the effectiveness of Reiki over placebo.
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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 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| 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".