The Role of Alexithymia, Borderline Personality Traits and Resilience in Suicidal and Nonsuicidal Self‐Harm Behaviours Among Adolescents With Major Depressive Disorder
Bibliographic record
Abstract
BACKGROUND: Depression is a significant health issue among adolescents, often associated with decreased academic performance, self-harm and increased suicide attempts. Suicidal and self-harm behaviours are particularly concerning and are influenced by multiple factors beyond depression. This study aims to examine the factors contributing to suicidal behaviour and nonsuicidal self-harm in adolescents diagnosed with major depressive disorder (MDD). MATERIALS AND METHODS: This prospective study included adolescent patients aged 12-18 years diagnosed with MDD according to DSM-5 criteria, referred to our Child and Adolescent Psychiatry Clinic between 1 February 2023 and 1 August 2023. Participants with intellectual disability, autism spectrum disorder, schizophrenia or other psychotic disorders were excluded. Data collection tools included the Sociodemographic Data Form, Inventory of Statements About Self-Injury, Child Depression Inventory, Borderline Personality Inventory (BPI), Toronto Alexithymia Scale and Child and Youth Resilience Measure-12 (CYRM-12). Data were analysed using SPSS25.0. RESULTS: Out of the 185 participants initially screened, 153 completed the study and were evenly divided into three groups: those who had never engaged in self-harm or attempted suicide (n = 51), those who had engaged in self-harm at least once but had not attempted suicide (n = 51) and those who had both engaged in self-harm and attempted suicide (n = 51). There were no significant differences in sociodemographic variables among the groups. Cutting was identified as the most common method of self-harm (84.3%), followed by scratching (72.5%). In terms of resilience, measured by the CYRM-12, the group with no history of self-harm or suicide attempts had significantly higher scores (M = 36.55) than the self-harm only group (M = 32.83) and the self-harm plus suicide attempt group (M = 31.03) (p < 0.001). For the BPI, the highest scores were observed in the group that had both engaged in self-harm and attempted suicide (M = 29.28), followed by the self-harm only group (M = 24.91) and the no self-harm or suicide group (M = 19.26) (p < 0.001). CONCLUSION: Adolescents with MDD who exhibit suicidal or self-harm behaviours have higher borderline personality traits and alexithymia levels, and lower resilience compared to their counterparts without such behaviours. These findings suggest the importance of early identification and intervention targeting these factors to mitigate the risk of self-harm and suicidal behaviour in depressed adolescents.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".