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Record W2148407594 · doi:10.1002/erv.481

A brief questionnaire to assess readiness to change in adolescents with eating disorders: its applications to group therapy

2002· article· en· W2148407594 on OpenAlexaff
Joanne Gusella, Gordon Butler, Laura A. Nichols, Debbie Bird

Bibliographic record

VenueEuropean Eating Disorders Review · 2002
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of New BrunswickQueen Elizabeth II Health Sciences CentreIzaak Walton Killam Health Centre
Fundersnot available
KeywordsEating disordersEating Disorder InventoryPsychologyClinical psychologyDepression (economics)PsychiatryBulimia nervosa

Abstract

fetched live from OpenAlex

Abstract There has been little attention paid to the motivation of adolescents entering treatment for an eating disorder. The present study investigates a questionnaire designed to assess readiness to change based on Prochaska and DiClemente's model. The Motivational Stages of Change for Adolescents Recovering from an Eating Disorder (MSCARED) was examined with 34 adolescent girls attending one of six eating disorder treatment groups. The assessment prior to, and at the termination of the groups, included the MSCARED; Children's Depression Inventory (CDI); Perceived Body Image Scale (PBIS); Eating Disorders Inventory (EDI‐2—pre‐only); and, the Group Evaluation Form (post‐only). The MSCARED proved to be easy for youth to complete, reliable, and demonstrated concurrent and predictive validity. While the group was beneficial to girls at each stage of change, greater gains were reported by those who started at a more advanced stage. The clinical and research implications of measuring motivation to change are discussed. Copyright © 2002 John Wiley & Sons, Ltd and Eating Disorders Association.

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)0.005
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.077
GPT teacher head0.351
Teacher spread0.274 · 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 designBench or experimental
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

Citations67
Published2002
Admission routes1
Has abstractyes

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