Biofield Therapies Clinical Research Landscape: A Scoping Review and Interactive Evidence Map
Bibliographic record
Abstract
Background: Biofield Therapies, with a historical lineage spanning millennia and continuing relevance in contemporary practices, have been used to address various health conditions and promote wellbeing. The scientific study and adoption of these therapies have been hindered by cultural challenges and institutional barriers. In addition, the current research landscape for Biofield Therapies is insufficiently documented. Objectives: This scoping review aims to comprehensively document the peer-reviewed research landscape of Biofield Therapies. Furthermore, an online searchable and dynamic Evidence Map was created to serve as a publicly accessible tool for querying the evidence base, pinpointing research gaps, and identifying areas requiring further exploration. Methods: A systematic search of PubMed, Embase, CINAHL, and PsycInfo databases was conducted from inception through January 2024. Peer-reviewed interventional studies in English involving human participants receiving Biofield Therapy were included. Data on study design, population, intervention, comparator, outcomes, citation details, and direction of results reported were extracted and synthesized into two summary tables and three data tables. Results: In total, 353 studies in 352 published reports were included: 255 randomized controlled trials, 36 controlled clinical trials, and 62 pre-post study designs. Named biofield interventions included Reiki ( n = 88), Therapeutic Touch ( n = 71), Healing Touch ( n = 31), intercessory prayer ( n = 21), External Qigong ( n = 16), Spiritual Healing/Spiritual Passé/Laying-on-of-hands ( n = 14), “distant or remote healing” ( n = 10), and Gentle Human Touch/Yakson Therapeutic Touch ( n = 9). Also included were 56 studies in 55 reports involving bespoke, unknown, or other interventions, 20 studies involving multimodal interventions, and 17 studies involving multiple biofield interventions. Studies encompassed a wide variety of populations, most commonly healthy volunteers ( n = 67), pain ( n = 55), and cancer ( n = 46). As reported in the Abstracts, nearly half of the studies ( n = 172) reported positive results in favor of the Biofield Therapy for all outcomes being investigated, 95 reported mixed results, 71 reported nonsignificant results, 3 reported negative results, and 12 studies did not report the direction of results. Conclusions: Despite rising interest in Biofield Therapies among researchers, practitioners, and patients, the integration of these interventions into allopathic medical systems is hindered by challenges in researching these therapies and inconsistent reporting. These issues contribute to inconclusive findings, which limit our understanding of the efficacy of Biofield Therapies for specific conditions. The resulting scoping review and interactive Evidence Map aim to empower stakeholders to overcome these obstacles, thereby strengthening the evidence for the potential adoption of Biofield Therapies as future integrative care options in allopathic medicine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".