Non‐suicidal Self‐injury in Different Eating Disorder Types: Relevance of Personality Traits and Gender
Bibliographic record
Abstract
The study explored lifetime prevalence of non-suicidal self-injury (NSSI) in female and male individuals with eating disorders (ED) and compared ED symptoms, general psychopathology and personality traits across individuals with and without a history of NSSI. The incremental discriminative capacity of gender on the manifestation of lifetime NSSI was also studied. A total sample of 1649 consecutively admitted ED patients (1515 women and 134 men) participated in the current study [339 ED + NSSI (ED with NSSI) and 1310 ED - NSSI (ED without NSSI)]. Specific self-report measures were included and other clinical and psychopathological indices. The observed lifetime prevalence of NSSI was 20.6% (20.9% in women and 17.2% in men). NSSI was not associated with ED type or gender. However, ED + NSSI patients exhibited more impulsive behaviour, substance-abuse disorders and additional impulse-control disorders, were younger and had more previous treatments. Age was shown to affect the presentation of NSSI. Additionally, ED + NSSI patients exhibited more severe ED and general psychopathological symptoms and had more dysfunctional personality traits when compared with ED - NSSI. ED + NSSI was found to be positively associated with harm avoidance and self-transcendence but negatively with reward dependence, self-directedness and cooperativeness. Thus, the variables with stronger capacity to identify the presence of ED + NSSI were younger age, harm avoidance, self-directedness and self-transcendence. A lack of association between sex and ED subtype with the presence of NSSI was observed.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".