Clarifying the association of eating disorder features to suicide ideation and attempts
Bibliographic record
Abstract
OBJECTIVE: We examine the relationships of eight eating disorder (ED) features to histories of suicide ideation and suicide attempts. METHOD: Participants were 387 adults (62% female, mean age = 36 years) recruited via an online platform, and oversampled for the presence of ED features, who completed standardized self-report measures of study variables. RESULTS: Different ED features predicted suicide ideation versus attempts. Specifically, Restrictive Eating (d = 0.44), Purging (d = 0.30), and Body Dissatisfaction (d = 0.27) were higher among ideators compared to nonsuicidal participants. In contrast, Muscle Building (d = 0.31), Excessive Exercise (d = 0.26), Cognitive Restraint (d = 0.23), and Restrictive Eating (d = 0.20) were higher among attempters compared to ideators-however, we note that the p-values for these effects range between 0.02 and 0.04 and it is unclear if they would replicate. Independent replication is important. CONCLUSION: Findings have implications for the conceptualization of suicide risk in individuals with EDs.
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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 | 0.010 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".