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Record W43044599

The effect of multiple family therapy on weight gain in adolescents with anorexia nervosa: pilot data.

2014· article· en· W43044599 on OpenAlexaff
Kevin Gabel, Leora Pinhas, Ivan Eisler, Debra K. Katzman, Margus Heinmaa

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsHospital for Sick ChildrenOntario Shores Centre for Mental Health SciencesSickKids FoundationNorth York General Hospital
Fundersnot available
KeywordsAnorexia nervosaMedicineEating disordersBehavioral therapyGynecologyPsychologyPsychiatryClinical psychology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: Preliminary research suggests that multiple family therapy (MFT) may be an effective intervention for adolescent anorexia nervosa (AN). This study compared the extent of weight restoration for patients enrolled in one year of MFT compared to a matched control group receiving treatment as usual (TAU). METHOD: A retrospective chart review was performed using data from 25 MFT cases matched to 25 controls on age, diagnosis and year of entry to the eating disorder program. RESULTS: Both cases and controls experienced significant weight restoration, however patients enrolled in MFT were restored to a higher mean percent ideal body weight than the TAU group (99.6% (±7.27%) vs. 95.4 (±6.88); p<0.05). CONCLUSIONS: MFT may be more effective than TAU in restoring weight in adolescents with AN.

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)0.002
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.034
GPT teacher head0.275
Teacher spread0.242 · 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

Citations32
Published2014
Admission routes1
Has abstractyes

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