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Record W2107191382 · doi:10.4172/1522-4821.1000145

Affect-Group Intervention for Alexithymia in Eating Disorders

2015· article· en· W2107191382 on OpenAlexaboutno aff
Suzanna Lundblad, Bertil Hansson, Trevor Archer

Bibliographic record

VenueChalmers Publication Library (Chalmers University of Technology) · 2015
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaAnorexia nervosaToronto Alexithymia ScaleBulimia nervosaFeelingIntervention (counseling)Clinical psychologyPsychologyEating disordersCoachingAffect (linguistics)PsychiatryPsychotherapistMedicineSocial psychology

Abstract

fetched live from OpenAlex

The purpose of this study is to describe a treatment intervention to alleviate eating disturbance and alexithymia symptoms in thirty patients diagnosed with anorexia nervosa and/or bulimia nervosa. The method consists of teaching and coaching about the emotional/affective status of individuals and incorporates both written and oral sessions. The treatment is presented within groups on one occasion (90 min) each week over eight-week periods. The results indicated that the intervention treatment reduced significantly the extent of alexithymia, as measured using the Toronto Alexithymia Scale, expressed by the patients. This implies that the teaching-coaching episodes affected their ability to cope with feelings thereby expressing improved insights concerning self-awareness and an understanding of themselves and others.

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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.245
Teacher spread0.228 · 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 designNon-randomized trial
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

Citations12
Published2015
Admission routes1
Has abstractyes

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