Examining Clinical Symptoms and Personological Traits in Adolescents With Anorexia Nervosa: A Network Analysis Approach
Bibliographic record
Abstract
OBJECTIVE: Despite advancements in treatment, research indicates that fewer than half of patients with anorexia nervosa (AN) achieve full recovery by the end of their treatment. Network analysis provides a novel framework for understanding the central features of this complex psychopathology, potentially identifying critical elements that could enhance intervention strategies. While evidence suggests that personality traits play a significant role in the etiology, symptomatic expression, and maintenance of AN, no studies have yet utilized network analysis to explore the relationships among personality traits, eating disorder (ED) symptoms, and common psychiatric comorbidities in adolescents with AN. This study aims to fill this gap by applying network analysis to examine the interplay between ED symptoms, anxiety and depressive symptoms, and personality traits in a sample of 243 adolescents with AN (92.6% female), aged 12 to 17 years (M age = 14.7 ± 1.4), recruited from five University Health Centers across Quebec, Canada. METHODS: Upon admission, participants completed the Eating Disorder Inventory-3 (EDI-3), the Multidimensional Anxiety Scale for Children (MASC), the Children's Depression Inventory 2 (CDI 2), and the Millon Adolescent Clinical Inventory (MACI). All variables were incorporated into a network analysis. RESULTS: The analysis revealed that submissive, conforming, self-demeaning, and inhibited personality traits were central nodes. Among ED symptoms, drive for thinness was the most prominent, with depressive symptoms exhibiting the highest centrality among comorbid conditions. CONCLUSION: These results highlight the complex interplay between ED symptoms, psychiatric comorbidities, and personality traits in adolescents with AN. These findings suggest that interventions may benefit from focusing on emotional regulation and interpersonal dynamics, with particular attention to assertiveness training and strategies to help adolescents express and address their needs in relationships.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".