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Record W2982526530

"Eating Me Up from Inside": A Pilot Study of Mentalization of Self and Others and Emotion Regulation Strategies among Young Women with Eating Disorders.

2018· article· en· W2982526530 on OpenAlexaboutno aff
Lily Rothschild‐Yakar, Merav Peled, Adi Enoch‐Levy, Eitan Gur, Dan J. Stein

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaMentalizationPsychologyNeurocognitiveClinical psychologyCognitionEating disordersToronto Alexithymia ScaleComorbidityNegative affectivityBorderline personality disorderPsychiatryDevelopmental psychologyAnxiety
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: We examined the relationship between general ability of mentalization, the specific aspect of affective mentalizing of self and others, emotion regulation strategies, and eating disorder (ED) symptoms. METHOD: Twenty-five female adolescent and young adult inpatients with EDs, and 22 healthy subjects, were administered a semi-structured interview - the Reflective Function (RF) scale, self-rating scales assessing alexithymia, emotion regulation, depression and ED symptomatology, and a neurocognitive measure assessing Theory of Mind. RESULTS: Participants with EDs presented lower levels of RF regarding the self and higher levels of alexithymia, using more emotional suppression and less cognitive reappraisal than controls. Elevated levels of general RF and self RF and attenuated alexithymia, along with elevated cognitive reappraisal and attenuated emotional suppression, were correlated with attenuated ED symptoms. Comorbidity with depressive symptoms predicted greater ED symptomatology. CONCLUSIONS: High mentalization may serve as a coping mechanism to attenuate ED symptoms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.020
GPT teacher head0.255
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2018
Admission routes1
Has abstractyes

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Same venuePubMed→Same topicEating Disorders and Behaviors→French-language works237,207→