Beyond abuse and neglect: validation of the childhood interpersonal trauma inventory in a community sample of adults
Bibliographic record
Abstract
Introduction: Childhood trauma is not restricted to abuse or neglect and other potentially traumatic experiences need to be pondered in practice and research. The study aimed to collect validity evidence of a new measure of exposure to a broad range of potentially traumatic experiences, the Childhood Interpersonal Trauma Inventory (CITI), by evaluating whether the CITI provides important additional information compared to a gold standard measure of childhood trauma. Methods: The sample consisted of 2,518 adults who completed the CITI and self-reported measures of trauma (Childhood Trauma Questionnaire; CTQ) and psychiatric symptoms (PTSD Checklist for DSM-5; Kessler Psychological Distress Scale; Dissociative Experiences Scale). Results: First, the sensitivity to properly detect participants having been exposed to childhood maltreatment, as measured by the CTQ (here used as the gold standard), ranged between 64.81% and 88.71%, and the specificity ranged between 68.55% and 89.54%. Second, hierarchical regressions showed that the CITI predicted between 5.6 and 14.0% of the variance in psychiatric symptoms while the CTQ only captured a very small additional part of variance (0.3 to 0.7%). Finally, 25% (n = 407) of CTQ-negative participants screened positive at the CITI. The latter reported higher severity of psychiatric symptoms than participants without trauma, suggesting that the CITI permits the identification of adults exposed to significant traumas that remain undetected using other well-validated measures. Discussion: The findings underscore the utility of the CITI for research purposes and the latter's equivalence to a gold standard self-reported questionnaire to predict negative outcomes.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".