Lack of exposure, sensitivity to blood, self-worth, and perceived stigma: Examining potential “barriers” to nonsuicidal self-injury among emerging adults in daily life
Bibliographic record
Abstract
Nonsuicidal self-injury (NSSI) is a highly prevalent mental health concern among adolescents and young adults. Understanding not only who is most at risk, but when in daily life, is necessary to prevent NSSI. To explore the role of several theoretically relevant "barriers" to NSSI (i.e., lack of exposure to NSSI, sensitivity to blood, self-worth, and perceived stigma) in NSSI urges and behaviors, daily diary sampling was used in the present study. Participants included 236 young adults (130 with recent NSSI, 106 without recent NSSI) who completed daily assessments for 14 days. Across the daily diary period, participants who engaged in NSSI reported greater exposure to NSSI, insensitivity to blood, perceived stigma toward NSSI, and lower self-worth compared to individuals without a history of NSSI. Hierarchical linear modeling revealed that within individuals, greater than typical insensitivity to blood and lower self-worth predicted same day NSSI urges and behaviors, and lower self-worth also predicted next day NSSI urges and behaviors. Greater exposure to NSSI also predicted same day NSSI urges, and next day NSSI behavior. Findings underscore that increasing self-worth and aversion to NSSI, and decreasing exposure to NSSI, may serve as important targets for NSSI prevention and intervention.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".