Childhood Maltreatment, Pathological Personality Dimensions, and Suicide Risk in Young Adults
Bibliographic record
Abstract
Several studies have demonstrated that child maltreatment (psychological, physical, and sexual abuse, and neglect) may be a significant factor in the development of pathological personality traits that increase the risk for suicidal ideation and behavior from adolescence to adulthood. Currently, the challenge is to understand how different forms of early negative experiences render an individual prone to develop specific personality traits and, in turn, be more vulnerable to suicide risk. To understand the relationship between childhood maltreatment and personality dimensions in suicide risk, our study aims to explore the role of self-criticism and dependency, two different pathological personality traits, as potential mediators of the link between different types of childhood maltreatment and suicide risk in young adults. For this purpose, 306 students from three Italian public universities were recruited. We used the Italian version of the Childhood Experience of Care and Abuse Questionnaire (CECA.Q) to assess experiences of lack of care by parents (i.e., antipathy and neglect) as well as psychological and physical abuse before the age of 17 years. The Depressive Experiences Questionnaire (DEQ) was used to assess the personality dimensions of self-criticism and dependency, and the Suicide History Self-Rating Screening Scale was administered to assess suicide risk. Results revealed that lack of care and psychological abuse were significantly associated with suicide risk and this association was partially mediated by the maladaptive personality dimension of self-criticism. These findings suggest that the combined effect of specific forms of dysfunctional parental behavior during childhood and the development of rigid and dysfunctional negative personality traits may increase the risk for suicidal ideation and behavior during adulthood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".