Self-Harm Reasons, Goal Achievement, and Prediction of Future Self-Harm Intent
Bibliographic record
Abstract
Self-harm may have several reasons, and these reasons may have corresponding implied goals. The current study examined reasons for self-harm and whether the a priori goals intended by these reasons were achieved. Fifty-seven individuals with a history of self-harm were recruited online and volunteered their time to complete a series of online questionnaires assessing past self-harm frequency, self-harm reasons, whether the goal associated with these reasons was achieved, and future self-harm intent. Reasons to reduce tension and dissociation associated with more past self-harm, a higher intent to self-harm again, and it was reported that the goals associated with reasons were achieved (i.e., these internal states were extinguished). Achievement of these goals (i.e., reported reductions in tension and dissociation) mediated the relation between corresponding self-harm reasons and intent to self-harm in the future. Findings support the view that self-harm is a maladaptive coping strategy and the reinforcement component of the experiential avoidance model of self-harm. Results have clinical implications and heuristic value for future research, which are discussed.
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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 | 0.002 | 0.013 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".