A psychometric analysis of the Ottawa self-injury inventory-f
Bibliographic record
Abstract
OBJECTIVE: This study seeks to evaluate the psychometric properties of the Ottawa Self-Injury Inventory-Functions (OSI-F) for assessing nonsuicidal self-injury (NSSI), a condition for further study in the DSM-5. PARTICIPANTS: Participants included 345 students who indicated a history of self-injury in a university counseling center over six semesters from August 2009 to May 2012. METHOD: Participants completed the OSI-F as a measure on the psychological intake for the university counseling center. RESULTS: Factor analysis, Cronbach's alpha coefficients, independent sample t tests, and correlations were examined and demonstrated adequate reliability and validity. CONCLUSIONS: A three-factor solution emerged from the restructured OSI-F relating to Affect Regulation, Exhilaration, and Release. Affect regulation dimensions were predictive of continuing to self-injure and related to depression, anxiety, and overall mental health. Additionally, women were more likely to attribute self-injuring to affect regulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".