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Record W2035820646 · doi:10.1002/eat.22038

Assessment of thought–shape fusion: Initial validation of a short version of the trait thought–shape fusion scale

2012· article· en· W2035820646 on OpenAlexaff
Jennifer S. Coelho, Céline Baeyens, Christine Purdon, Roz Shafran, Jean‐Luc Roulin, Martine Bouvard

Bibliographic record

VenueInternational Journal of Eating Disorders · 2012
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPsychologyPsychopathologyEating disordersScale (ratio)TraitClinical psychologyCognitionConvergent validityInternal consistencyPsychometricsDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: Thought-shape fusion (TSF) is a cognitive distortion that has been linked to eating pathology. Two studies were conducted to further explore this phenomenon and to establish the psychometric properties of a French short version of the TSF scale. METHOD: In Study 1, students (n = 284) completed questionnaires assessing TSF and related psychopathology. In Study 2, the responses of women with eating disorders (n = 22) and women with no history of an eating disorder (n = 23) were compared. RESULTS: The French short version of the TSF scale has a unifactorial structure, with convergent validity with measures of eating pathology, and good internal consistency. Depression, eating pathology, body dissatisfaction, and thought-action fusion emerged as predictors of TSF. Individuals with eating disorders have higher TSF, and more clinically relevant food-related thoughts than do women with no history of an eating disorder. DISCUSSION: This research suggests that the shortened TSF scale can suitably measure this construct, and provides support for the notion that TSF is associated with eating pathology.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.363
Teacher spread0.337 · 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

Citations24
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Eating DisordersSame topicEating Disorders and BehaviorsFrench-language works237,207