Comparison of childhood trauma between depressive disorders and personality disorders
Bibliographic record
Abstract
The relationship between childhood trauma with major depressive disorder (MDD) and personality disorders is complex. We explored the differences in the subjective reporting of childhood trauma to determine whether there were differences between those with a diagnosis of personality disorder and those with MDD. Adult patients with depressive symptoms were recruited from three adult psychiatry inpatient wards. Sixty inpatients fulfilled the study criteria and were requested to complete the childhood trauma questionnaire (CTQ). At discharge, diagnosis was determined and was allocated mainly to two groups: those with MDD and those with personality disorder. Those with MDD, dysthymia and subsyndromal depressive symptoms were included in the Depression Broad Definition (DBD) group (secondary analysis). Significantly higher subjective reporting of childhood trauma was observed in the personality disorder group compared with MDD in three CTQ domains. Similarly, significantly higher reporting of childhood trauma was observed in all five CTQ domains in those with a personality disorder compared with the DBD group. In conclusion, the presence of personality disorder was associated with greater subjective reporting of childhood trauma compared with those with MDD, and further research is required to explore the differences in objective experience of childhood trauma between the diagnoses using objective measures.
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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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".