Trajectories of nonsuicidal self‐injury during adolescence
Bibliographic record
Abstract
OBJECTIVE: Although nonsuicidal self-injury is a public health concern, there is little information on how it changes across adolescence or what contributes to stability or change. We aimed to identify trajectories of stability and change in self-injury from ages 13 to 17 years, and to identify interpersonal and intrapersonal correlates that differentiate between trajectories of stability and change. METHOD: We used five annual waves of cohort-sequential data, targeting 7th and 8th graders attending all public schools in three municipalities in central Sweden. The data were gathered via questionnaires, using a multi-item measure of non-suicidal self-injury and assessing negative experiences at home, in school, with peers, and in romantic settings, as well as intrapersonal issues (internalizing symptoms and difficulties with emotional, and behavioral regulation). The analytic sample was 3195 adolescents (51.7% boys, 48.3% girls; ages 12-16 years at T1, M = 13.61; SD = 0.66), most of whom were born in Sweden (88.6%) to at least one parent of Swedish origin (77.4%). RESULTS: Latent growth curve modeling revealed three self-injury trajectories: a stable-low, a low-increasing, and an increasing-decreasing trajectory. Adolescents in the stable-low class reported the best overall adjustment at ages 13 and 16. Comparatively, adolescents in the other two classes reported similar levels of difficulty interpersonally and intrapersonally. Where they differed, the increase-decrease class fared worse than the low-increasing class. CONCLUSIONS: This study suggests the need to frame self-injury as having multiple directions of development during adolescence and develop theory that aligns with differential patterns of self-injury development.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".