Mentalisation-based therapy for eating disorder treatment: protocol for a systematic review
Bibliographic record
Abstract
INTRODUCTION: Eating disorders (EDs) are complex psychological and physiological disorders that often co-occur in the presence of other mental health difficulties. Mentalisation-based therapy (MBT) offers a promising therapeutic approach for treating comorbid difficulties by fostering individuals' capacity to understand their own and others' mental states. More specifically, MBT is a novel approach for treating EDs that recognises the intricate interplay between psychological factors and disordered eating behaviours, targeting the underlying cognitive and emotional processes implicated in ED pathology. The possible value of MBT in treating EDs has been proposed, but the existing research on the topic has not yet been synthesised. This review aims to examine the effectiveness of MBT across diverse ED presentations through analysis of the peer-reviewed literature. METHODS AND ANALYSIS: This systematic review protocol adheres to the Preferred Reporting Items for Systematic reviews and Meta-Analyses for Protocols checklist. The review will include peer-reviewed studies on MBT for EDs without geographical restrictions. A systematic search for the published literature will be conducted using the following databases: Medline, Embase, PsycInfo and Cochrane Central Register of Controlled Trials. For articles to be included, documents must describe and evaluate MBT for EDs and be a quantitative study. There will be no restrictions on publication date. The two authors will independently screen titles, abstracts and full-text articles. A meta-analysis will be conducted for data synthesis if at least three studies with comparable designs, populations and outcomes are identified. If studies are too heterogeneous, a narrative synthesis will summarise the results. The findings may contribute to a more nuanced understanding of MBT's role in ED treatment, with potential implications for clinical practice, policy development and future research endeavours. ETHICS AND DISSEMINATION: Ethical approval is not required as all data are available from public sources. The results of this systematic review will be disseminated through peer-reviewed publications and conference presentations. PROSPERO REGISTRATION NUMBER: CRD42024421136.
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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 | 0.080 | 0.084 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.017 | 0.021 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.082 | 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".