Determinants of Qigong, Tai Chi, and Yoga Use for Health Conditions: A Systematic Review Protocol
Bibliographic record
Abstract
ABSTRACT INTRODUCTION Mind-body movement interventions such as qi gong, tai chi, and yoga are recommended in clinical practice guidelines to improve outcomes for several health conditions. However, use of these interventions for health conditions, or the integration of these interventions within healthcare settings, is low. A systematic synthesis of implementation determinants (i.e., barriers and facilitators) is needed to increase adoption. Similarly, determinants may influence other implementation outcomes, such as scalability or sustainability of these interventions in a healthcare system or community organization. Thus, in conducting this review we aim to identify determinants of qi gong, tai chi, and yoga use for health conditions. The secondary aim is to evaluate whether barriers and facilitators differ by intervention type, health condition, implementation setting, or implementation outcome. METHODS AND ANALYSIS We conducted a comprehensive search of electronic databases (MEDLINE, EMBASE, Web of Science, CINAHL, PsycInfo) through May 2024 and a grey literature search (Google Scholar, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov , the WHO Clinical Trials database) through March 2025. We will include original research articles in English that identify barriers and facilitators to adoption of qi gong, tai chi, and yoga by adults with health conditions. Study quality will be assessed using the Mixed Methods Appraisal Tool. We will code each article using a codebook informed by the Consolidated Framework for Implementation Research (CFIR), a comprehensive taxonomy of implementation determinants. Findings will be presented as a narrative synthesis. We will report on how barriers and facilitators may relate to intervention type (qi gong, tai chi, yoga), health condition (e.g., low back pain, fall prevention), implementation settings (e.g., primary care clinic, community organization) or implementation outcome (e.g., adoption, sustainability). ETHICS AND DISSEMINATION Ethics approval will not be obtained for this review of published, publicly accessible data. The results from this systematic review will be disseminated through conference presentations and journal publications. STRENGTHS AND LIMITATIONS OF THIS STUDY There are no prior comprehensive reviews of the determinants (i.e., barriers and facilitators) of qi gong, tai chi and yoga use. This review will examine whether barriers and/or facilitators vary by type of mind-body movement intervention, health condition, implementation setting, or implementation outcome. Our search has been guided by librarians with expertise in systematic review methodology and informed by the PEER Review of Electronic Search Strategies (PRESS) guidelines. Reporting of results will be informed by the PRISMA-P checklist for systematic reviews. We will use the updated version of the Consolidated Framework for Implementation Research (CFIR, version 2.0) to report implementation factors using consistent concepts to facilitate use of the review by researchers, healthcare systems, and community organizations. Our findings will support the development of implementation strategies to increase the adoption of qi gong, tai chi, and yoga for health conditions. Due to the complex nature of describing implementation determinants and characterizing them within the Consolidated Framework for Implementation Research, our review is limited to papers written in English which may restrict the generalizability of our implementation findings to predominantly English-speaking healthcare settings.
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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 | 0.094 | 0.087 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.019 | 0.017 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.079 | 0.011 |
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".