The efficacy of hypnotherapy on reducing burnout and related psychopathologies: A protocol of the systematic review and meta-analysis (Preprint)
Bibliographic record
Abstract
Background: Hypnosis is a focused state of consciousness that enhances concentration, attention, and responsiveness to suggestion. It has shown efficacy in treating psychiatric disorders such as depression, anxiety, and posttraumatic stress disorder (PTSD). However, its potential for addressing burnout and related symptoms remains underexplored. This systematic review and meta-analysis aims to assess the effectiveness of hypnotherapy in alleviating symptoms of burnout and associated conditions, including depression, anxiety, and PTSD. Objective: This study aims to evaluate the efficacy of hypnotherapy in treating burnout and its related psychopathologies, including depression, anxiety, and PTSD. Methods: A comprehensive search was conducted across PubMed, Scopus, and PsycINFO for peer-reviewed, English-language observational and experimental studies published up to February 2024. Only studies with adults (>18 y) who received hypnotherapy for psychiatric symptoms will be included. Data extraction will focus on treatment effects related to burnout and associated psychiatric conditions. Statistical analysis will be performed using Comprehensive Meta-Analysis (version 4.0). A random-effects model will be used to account for heterogeneity, with Cochran Q and I² statistics used to assess variability. Subgroup analyses will explore moderators such as sociodemographic factors, country, and study quality. Sensitivity analyses will identify influential studies, and publication bias will be assessed using funnel plots and the Egger test. All analyses will be 2-sided (P<.05), and the results will be presented in forest plots. Results: The search strategy underwent a PRESS (Peer Review of Electronic Search Strategies) review in December 2023 and was registered in PROSPERO (International Prospective Register of Systematic Reviews) in January 2024. Database searches were completed between February and April 2024, followed by title and abstract screening from May to November 2024. Full-text screening began in December 2024, with data extraction conducted from January through April 2025. A preliminary narrative synthesis was completed between May and August 2025. Quantitative analysis began in September 2025 and is ongoing, with completion anticipated in early summer 2026. The final findings are expected to be submitted for publication by fall 2026. Conclusions: This review aims to synthesize existing evidence on the potential role of hypnotherapy for burnout and related psychiatric symptoms. This systematic review will provide an updated synthesis of evidence on hypnotherapy for burnout and associated psychological outcomes. Limitations include variability in study designs and measurement tools. The results will be disseminated through peer-reviewed journals and scientific meetings to guide future clinical and research applications.
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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 | 0.093 | 0.171 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.014 | 0.026 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.032 | 0.004 |
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".