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Record W2022734818 · doi:10.1136/ebmh.7.3.78

Review: interactive, multisession, and targeted programmes most effective in preventing eating disorders

2004· letter· en· W2022734818 on OpenAlexaff
Donna Ciliska

Bibliographic record

VenueEvidence-Based Mental Health · 2004
Typeletter
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsMcMaster University
Fundersnot available
KeywordsWeb of scienceMeta-analysisMedicineEating disordersCINAHLPsycINFORandomized controlled trialMEDLINEInternal medicinePsychiatryPsychological interventionBiology

Abstract

fetched live from OpenAlex

Stice E, Shaw H. Eating disorder prevention programs: a meta-analytic review. Psychol Bull 2004;130:206–27.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Q What are the effects of eating disorder prevention programmes, and which features are associated with the most effective outcomes? ### ![Graphic][5]</img>Design: Systematic review with meta-analysis. ### ![Graphic][6]</img>Data sources: PsycINFO, MEDLINE, CINAHL, and Dissertation Abstracts International searched 1980 to April 2003. Hand searches of key journals and bibliographies plus contact with experts for unpublished studies. ### ![Graphic][7]</img>Study selection and analysis: Eligible studies were randomised trials comparing eating disorder prevention programmes (designed to control eating pathology risk factors and current eating pathology) with minimal intervention, assessment only, placebo, or wait list controls. Only studies quantifying change in outcomes between intervention and control groups were included. Effect sizes were calculated for outcomes included in at least 10 trials. Where data were sufficient, and heterogeneity of effect sizes was significant, the following moderators of effect sizes were examined: selective programmes … [1]: {openurl}?query=rft.jtitle%253DPsychological%2Bbulletin%26rft.stitle%253DPsychol%2BBull%26rft.aulast%253DStice%26rft.auinit1%253DE.%26rft.volume%253D130%26rft.issue%253D2%26rft.spage%253D206%26rft.epage%253D227%26rft.atitle%253DEating%2Bdisorder%2Bprevention%2Bprograms%253A%2Ba%2Bmeta-analytic%2Breview.%26rft_id%253Dinfo%253Adoi%252F10.1037%252F0033-2909.130.2.206%26rft_id%253Dinfo%253Apmid%252F14979770%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1037/0033-2909.130.2.206&link_type=DOI [3]: /lookup/external-ref?access_num=14979770&link_type=MED&atom=%2Febmental%2F7%2F3%2F78.atom [4]: /lookup/external-ref?access_num=000189106900002&link_type=ISI [5]: /embed/inline-graphic-1.gif [6]: /embed/inline-graphic-2.gif [7]: /embed/inline-graphic-3.gif

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.617
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.380
Teacher spread0.356 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreCommentary

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

Citations0
Published2004
Admission routes1
Has abstractyes

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