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Record W2006071130 · doi:10.1515/ijamh-2013-0027

Weight gain in an eating disorders day program

2013· article· en· W2006071130 on OpenAlexaboutno aff
Ama deGraft-Johnson, Martin Fisher, Lisa Rosen, Barbara Napolitano, Emma Laskin

Bibliographic record

VenueInternational Journal of Adolescent Medicine and Health · 2013
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsnot available
Fundersnot available
KeywordsWeight gainAnorexia nervosaQuarter (Canadian coin)Eating disordersBulimia nervosaMedicineBody mass indexBody weightAnorexiaPsychiatryPediatricsPsychologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Day treatment programs have increasingly become an important level of care in the medical and psychiatric management of patients with eating disorders, yet there is little in the literature describing the weight gain patterns of patients in these programs. METHODS: Weight gain accomplished by 198 patients admitted to a day program over a 2-year period was studied. Weight gain was analyzed by demographic, diagnostic and program-related variables and was compared for weekdays and weekends. RESULTS: The mean length of stay was 2.6 weeks and patients gained a mean of 2.1 pounds (0.95 kg) in the program. Approximately one-quarter of patients lost weight, one-quarter gained 0 to <2 pounds (0.9 kg), one-quarter gained 2-4 pounds (0.9-1.8 kg), and one-quarter gained more than 4 pounds (1.8 kg). Weight gain was greater in those with a diagnosis of anorexia nervosa or eating disorder not otherwise specified (compared to bulimia nervosa), a longer time in the program, and a lower body mass index on admission. Patients gained more on weekdays, while in the program, than on weekends, when they were home. CONCLUSIONS: The data showed that most patients accomplished modest weight gains during a relatively short stay in an eating disorders day program, demonstrating what can be expected for this level of care in the current healthcare environment.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.047
GPT teacher head0.425
Teacher spread0.378 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Adolescent Medicine and HealthSame topicEating Disorders and BehaviorsFrench-language works237,207