Trajectories and Personality Predictors of Eating-Pathology Development in Girls From Preadolescence to Adulthood
Bibliographic record
Abstract
Understanding eating-pathology development may enable meaningful prescriptions for its prevention. Here, we identified common trajectories of eating-pathology development and the personality factors associated with these trajectories. Participants were 760 female twins from the Minnesota Twin Family Study who reported on eating pathology at approximate ages 11, 14, 18, 20, 24, and 29. Parents reported on twins’ personality characteristics at age 11, and twins completed self-report personality questionnaires at ages 14 and 18. Latent class growth analysis identified two distinct trajectories for total eating pathology, binge eating, and weight preoccupation and three distinct trajectories for body dissatisfaction. Girls with more pathological trajectories already showed elevated eating pathology at age 11. These subgroups of high-risk girls self-reported greater proneness to anxiety, stress, and alienation, and less sociable personality styles. Prevention efforts may be enhanced by using self-reported personality traits to identify girls at high risk for eating pathology.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".