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Record W2057771075 · doi:10.1089/cap.2010.0104

A Brief Motivational Intervention for Preventing Medication-Associated Weight Gain Among Youth with Bipolar Disorder: Treatment Development and Case Report

2011· article· en· W2057771075 on OpenAlexaff
Tina R. Goldstein, Benjamin I. Goldstein, Michael B. Mantz, Bridget C. Bailey, Antoine Douaihy

Bibliographic record

VenueJournal of Child and Adolescent Psychopharmacology · 2011
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsSunnybrook Health Science Centre
FundersNational Institute of Mental HealthUniversity of Pittsburgh
KeywordsWeight gainMoodBipolar disorderPsychiatryOverweightIntervention (counseling)PopulationObesityMedicinePsychologyClinical psychologyBody weightInternal medicine

Abstract

fetched live from OpenAlex

Bipolar disorder (BP) in youth is an impairing psychiatric disorder associated with high rates of relapse and recurrence. High rates of psychiatric and medical co-morbidities account for additional illness burden in pediatric BP. The elevated risk of overweight and obesity in this population is of particular concern. One of the likely etiologies for weight gain in youth with BP is use of mood-stabilizing medications. Although these medications can be effective for mood stabilization, excessive weight gain is a common side effect. Obesity is associated with a host of medical problems and is also correlated with worse psychiatric outcomes in BP, rendering the prevention of weight gain in this population particularly clinically relevant. In this article, we describe the rationale and development of a brief motivational intervention for preventing weight gain among youth with BP initiating mood-stabilizing pharmacological treatment and then present a case example illustrating the principles of the intervention.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.055
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.018
GPT teacher head0.282
Teacher spread0.264 · 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.

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

Citations14
Published2011
Admission routes1
Has abstractyes

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