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Record W2023581874 · doi:10.3390/nu4091260

Body-Related Social Comparison and Disordered Eating among Adolescent Females with an Eating Disorder, Depressive Disorder, and Healthy Controls

2012· article· en· W2023581874 on OpenAlexafffund
Andrea Elizabeth Hamel, Shannon L. Zaitsoff, Andrew J. Taylor, Rosanne Menna, Daniel Le Grange

Bibliographic record

VenueNutrients · 2012
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of WindsorSimon Fraser University
FundersCanadian Institutes of Health Research
KeywordsDisordered eatingMajor depressive disorderPsychologyEating disordersClinical psychologyPsychiatryBody mass indexMedicineMoodInternal medicine

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate the association between body-related social comparison (BRSC) and eating disorders (EDs) by: (a) comparing the degree of BRSC in adolescents with an ED, depressive disorder (DD), and no psychiatric history; and (b) investigating whether BRSC is associated with ED symptoms after controlling for symptoms of depression and self-esteem. Participants were 75 girls, aged 12-18 (25 per diagnostic group). To assess BRSC, participants reported on a 5-point Likert scale how often they compare their body to others'. Participants also completed a diagnostic interview, Eating Disorders Inventory-2 (EDI-2), Beck Depression Inventory-II (BDI-II), and Rosenberg Self-Esteem Scale (RSE). Compared to adolescents with a DD and healthy adolescents, adolescents with an ED engaged in significantly more BRSC (p ≤ 0.001). Collapsing across groups, BRSC was significantly positively correlated with ED symptoms (p ≤ 0.01), and these associations remained even after controlling for two robust predictors of both ED symptoms and social comparison, namely BDI-II and RSE. In conclusion, BRSC seems to be strongly related to EDs. Treatment for adolescents with an ED may focus on reducing BRSC.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.330
Teacher spread0.303 · 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 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

Citations61
Published2012
Admission routes2
Has abstractyes

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