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Record W2100180642 · doi:10.1002/eat.20132

Emotion-processing deficits in eating disorders

2005· article· en· W2100180642 on OpenAlexaboutno aff
Sarah Bydlowski, Maurice Corcos, Philippe Jeammet, Sabrina Paterniti, Sylvie Berthoz, Catherine Laurier, Jean Chambry, Silla M. Consoli

Bibliographic record

VenueInternational Journal of Eating Disorders · 2005
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaToronto Alexithymia ScalePsychologyBeck Depression InventoryAnxietyDepression (economics)Clinical psychologyConfoundingEating disordersPsychiatryMedicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: First, we measured both emotional awareness and alexithymia to understand better emotion-processing deficits in eating disorder patients (EDs). Second, we increased the reliability of the measures by limiting the influence of confounding factors (negative affects). METHOD: Seventy females with eating disorders were compared with 70 female controls. Participants completed the Beck Depression Inventory (BDI; depression), the Hospital and Anxiety Depression Scale (HADS; anxiety), the Toronto Alexithymia Scale (TAS; alexithymia), and the Level of Emotional Awareness Scale (LEAS). RESULTS: EDs exhibited higher alexithymia scores and lower LEAS scores, with an inability to identify and describe their own emotions, as well as an impairment in mentalizing others' emotional experience. Whereas alexithymia scores were related to depression scores, LEAS scores were not. After controlling for depression, alexithymia scores were similar in EDs and controls. DISCUSSION: The marked impairment in emotion processing found in EDs is independent of affective disorders. Thus, the joint use of TAS and LEAS suggests a global emotion-processing deficit in EDs.

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)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.332
Teacher spread0.316 · 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

Citations356
Published2005
Admission routes1
Has abstractyes

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