The mentalization profile in patients with eating disorders: a systematic review and meta-analysis
Bibliographic record
Abstract
Context: Patients with eating disorders (EDs) may have a lower mentalization ability. To the best of our knowledge, no meta-analysis has so far addressed the multidimensional mentalization profile within these patients. Objective: To summarize the existing evidence of the mentalization profile and its association with EDs. Data sources: We searched for articles in PsychINFO, Embase and PubMed using the search terms mentalization, reflective function, adult attachment interview, alexithymia, Toronto Alexithymia Scale, eye test, Reading the Mind in the Eyes Test, Theory of Mind, mind-mindedness, mind-blindness, facial expression recognition, metacognition, ED, anorexia nervosa (AN) and bulimia nervosa (BN). Studies included: Quantitative studies including diagnosed patients with an ED, healthy controls (HCs) and relevant test methods. Data synthesis: Forty-four studies were included. Nine studies were eligible for the meta-analysis. Significantly lower mentalization ability about oneself was found in patients with an ED when compared to HCs. Groups were more comparable when dealing with mentalization ability of others. Non-significant but clinically relevant results include a tendency for a lower mentalization ability in patients with AN compared to patients with BN. Conclusion: The mentalization profile is complex and varies across dimensions of mentalization in patients with an ED. Different degrees of mentalization between various EDs were found, implying the necessity for further research on mentalization profiles in different ED diagnoses. The sparse existing literature was a limitation for this meta-analysis, emphasizing that further research on the mentalization profile in patients with EDs is needed.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.025 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".