A Longitudinal Network Analysis of Emotion Regulation, Interpersonal Problems, and Eating Disorder Psychopathology in Chinese Adolescents
Bibliographic record
Abstract
OBJECTIVE: The present longitudinal study examined sex-specific, symptom-level relationships among emotion regulation (ER), interpersonal problems (IP), and eating disorder (ED) psychopathology in a large sample of Chinese adolescents. METHOD: Data were from a project with four waves of data collection (N = 1540; 710 boys and 830 girls) at 6-month intervals over 18 months. Questionnaires assessed ED psychopathology, ER, and IP at each wave of data collection. Longitudinal network analyses were conducted separately for boys and girls. Sex differences in the network structures were also examined. RESULTS: The results revealed pronounced heterogeneity in the presentation of ED psychopathology, ER, and IP across Chinese adolescent boys and girls longitudinally and intra-individually. For example, weight/shape preoccupation in ED psychopathology and awareness in ER emerged as important nodes in the temporal network for boys. However, weight/shape preoccupation and dissatisfaction in ED psychopathology were identified as the most important nodes in the temporal network for girls. Regarding bridge strength, awareness in ER emerged as the node with the highest connectivity in the temporal network for boys. At the same time, weight/shape dissatisfaction in ED psychopathology was the node with the highest connectivity for girls. DISCUSSION: The current study extended network theory to better understand the longitudinal interplay among ER, IP, and ED psychopathology in Chinese adolescents and their sex differences in the importance of symptoms. Such insights may pave the way for developing targeted prevention and treatment strategies for adolescent boys and girls in China.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".