Parental bonding and personality characteristics of first episode intention to suicide or deliberate self-harm without a history of mental disorders
Bibliographic record
Abstract
BACKGROUND: There is substantial overlap between deliberate self-harm (DSH) and intention to suicide (ITS), although the psychopathologies and motivations behind these behaviors are distinctly different. The purpose of this study was to investigate (i) the pathway relationship among parental bonding, personality characteristics, and alexithymic traits, and (ii) the association of these features with ITS and DSH using structural equation modeling to determine the risks and protective factors for these behaviors. METHODS: Sixty-nine first-time DSH and 36 first-time ITS patients without medical or psychiatric illnesses, and 66 controls were recruited. The Parental Bonding Inventory (PBI), Eysenck Personality Questionnaire (EPQ), 20-item Toronto Alexithymia Scale (TAS-20), and the Chinese Health Questionnaire (CHQ) were filled out by the participants. RESULTS: Our structural equation models showed that parental bonding had the greatest influence on the development of DSH behavior in patients. On the other hand, participants who were younger, less extraverted, with a greater extent of the alexithymic trait of difficulty identifying feeling (DIF), and a worse mental health condition, were more likely to develop ITS behavior. Males were more likely than females to develop the alexithymic trait of DIF. CONCLUSIONS: Although there are many covariates that affect both ITS and DSH behaviors, these covariates may have different functions in the development of these behaviors, thus revealing the psychopathological difference between DSH and ITS. Policymakers should consider these differences and build intervention and prevention programs for gender- and age-specific high-risk groups to target the differences, with a focus on family counseling to treat DSH and a focus on attempting to increase emotional awareness to treat ITS.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".