Intrapersonal and Interpersonal Functions of Non suicidal Self‐Injury: Associations with Emotional and Social Functioning
Bibliographic record
Abstract
Understanding the functions of nonsuicidal self-injury (NSSI) has important implications for the development and refinement of theoretical models and treatments of NSSI. Emotional and social vulnerabilities associated with five common functions of NSSI-emotion relief (ER), feeling generation (FG), self-punishment (SP), interpersonal influence (II), and interpersonal communication (IC)-were investigated to clarify why individuals use this behavior in the service of different purposes. Female participants (n = 162) with a history of NSSI completed online measures of self-injury, emotion regulation strategies and abilities, trait affectivity, social problem-solving styles, and interpersonal problems. ER functions were associated with more intense affectivity, expressive suppression, and limited access to emotion regulation strategies. FG functions were associated with a lack of emotional clarity. Similar to ER functions, SP functions were associated with greater affective intensity and expressive suppression. II functions were negatively associated with expressive suppression and positively associated with domineering/controlling and intrusive/needy interpersonal styles. IC functions were negatively associated with expressive suppression and positively associated with a vindictive or self-centered interpersonal style. These findings highlight the specific affective traits, emotional and social skill deficits, and interpersonal styles that may render a person more likely to engage in NSSI to achieve specific goals.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".