Examining the components and stability of negative affect in disordered eating frequency
Bibliographic record
Abstract
OBJECTIVE: There is a limited understanding of the unique components of negative affect that are most important to disordered eating. Our study tested the contributions and stabilities of unique components of negative affect in the frequency of both binge eating and restricted eating. We examined if: (1) symptoms of depression, anxiety and stress share unique, concurrent associations with binge eating and restricted eating, respectively, and if (2) instability of depression, anxiety, and stress predict binge eating and restricted eating, respectively. METHOD: 627 first year undergraduate students completed 7 assessments of these constructs across their first academic year. Generalised multilevel modelling was employed. RESULTS: Higher than average anxiety, but not depression or stress, was concurrently associated with restricted eating. No concurrent associations between negative affect and binge eating were found. Instability of depression, but not anxiety or stress, predicted both binge and restricted eating. CONCLUSION: Anxiety may be a more salient predictor of restricted eating than depression or stress. However, larger monthly changes in depression may confer risk for more frequent binge eating and restricted eating.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".