Disordered eating,<scp>self‐esteem</scp>, and depression symptoms in Iranian adolescents and young adults: A network analysis
Bibliographic record
Abstract
OBJECTIVE: The network theory of psychopathology examines networks of interconnections across symptoms. Several network studies of disordered eating have identified central and bridge symptoms in Western samples, yet network models of disordered eating have not been tested in non-Western samples. The current study tested a network model of disordered eating in Iranian adolescents and college students, as well as models of co-occurring depression and self-esteem. METHOD: Participants were Iranian college students (n= 637) and adolescents (n = 1,111) who completed the Eating Disorder Examination-Questionnaire (EDE-Q), Rosenberg Self-Esteem Scale (RSES) and Beck Depression Inventory, Second Edition (BDI-II). We computed six Glasso networks and identified central and bridge symptoms. RESULTS: Central disordered eating nodes in most models were a desire to lose weight and discomfort when seeing one's own body. Central self-esteem and depression nodes were feeling useless and self-dislike, respectively. Feeling like a failure was the most common bridge symptom between disordered eating and depression symptoms. With exception of a few differences in some edges, networks did not significantly differ in structure. DISCUSSION: Desire to lose weight was the most central node in the networks, which is consistent with sociocultural theories of disordered eating development, as well as prior network models from Western-culture samples. Feeling like a failure was the most central bridge symptom between depression and disordered eating, suggesting that very low self-esteem may be a shared correlate or risk factor for disordered eating and depression in Iranian adolescents and young adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".