Early maladaptive schemas are associated with self-injury thoughts and behavior in adolescents
Bibliographic record
Abstract
BACKGROUND: Early maladaptive schemas (EMSs) and self-harm have been firmly linked in adults, but research on these associations in adolescents remains scarce. Additionally, the links between EMSs and functions of self-injury has not been previously studied in this age group. Thus, the aim of the present study was to investigate the associations of EMSs with self-harm thoughts and behavior, as well as with self-harm functions, among adolescents in specialized health care. METHODS: The participants were recruited from first-visit 12-22-year-old adolescent patients entering specialized mental health care or pediatric care. For 118 participants, complete data were available for the Young Schema Questionnaire Short Form 2-Extended (YSQ) when entering care and the Ottawa Self-Injury Inventory Functions scale (OSI-F) one year later. YSQ was used to measure the participants' EMSs and OSI-F their self-harm thoughts and behavior. The associations of EMSs and self-harm were investigated in three groups: no self-harm, self-harm thoughts only, and both self-harm thoughts and behavior. The associations of EMSs with self-injury behavior functions were assessed in four categories: Internal Emotional Regulation, External Emotional Regulation, Social Influence, and Sensation Seeking. Additionally, EMSs' associations with addictive features of self-injury behavior were assessed. The magnitudes of effect sizes of differences between the self-harm groups were evaluated with Cliff's Delta. The associations of EMSs with self-injury functions were analyzed with general linear modeling and with self-injury addictive features using logistic regression. RESULTS: The differences between the self-harm groups were significant for the majority of the EMSs. The stronger the EMSs were, the more severe the manifestations of self-harm. The effect sizes ranged from small to large depending on the EMS. Considering self-injury functions, Internal Emotional Regulation was associated with Self-Sacrifice EMS (p = 0.021), and External Emotional Regulation both with Abandonment (p = 0.040) and Unrelenting Standards (p = 0.012) EMSs. Being addicted to self-injury was associated with Abandonment (p = 0.043) and Dependence (p = 0.025) EMSs. CONCLUSIONS: The present study shows that significant associations between EMSs and both self-harm thoughts and behavior exist also in adolescents. Stronger EMSs are linked to more severe self-harm. Knowledge of these associations may help to improve the understanding and treatment of adolescents suffering from self-harm.
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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 | 0.001 |
| 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".