Development and Validation of the Self‐Harm Reasons Questionnaire
Bibliographic record
Abstract
Understanding the reasons for self-harm (SH) may be paramount for the identification and treatment of SH behavior. Presently, the psychometric properties for SH reason questionnaires are generally unknown or tested only in non-inpatient samples. Existing inpatient measures may have limited generalizability and do not examine SH apart from an explicit intent to die. The present study examined a newly developed, self-report measure of reason for self-harm. The Self-Harm Reasons Questionnaire (SHRQ) was administered to 143 undergraduate students. Results indicated that SH reasons covaried in meaningful and internally consistent ways, with subgroups of SH reasons correlating with hypothesized concomitants of SH, such as depressive symptoms. Findings have implications for prevention and intervention and the SHRQ offers a new, albeit preliminary, means by which to examine SH reasons in a non-inpatient sample.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".