Construct Validation of the Trauma Symptom Checklist–40 Total and Subscale Scores
Bibliographic record
Abstract
The Trauma Symptom Checklist-40 (TSC-40) is commonly used in clinical research to index history of childhood maltreatment and assess complex trauma symptomatology in adults. Yet the dimensional structure of this measure has not been examined. We examined the factor structure of the TSC-40 in a sample of 706 undergraduate students, measurement invariance of the TSC-40 across groups with or without a history of abuse-related and multiple trauma, and the association between the TSC-40 and other trauma indices. A higher order model of complex trauma symptomatology was optimal. The higher order model also demonstrated strong measurement invariance across participants with or without abuse-related and multiple trauma histories. The current findings support the dimensional structure of the TSC-40, as well as extending and revising its subscale composition. This study provided support for using the TSC-40 to measure trauma symptoms across groups exposed to different and multiple types of trauma and provided further evidence for the construct of complex trauma symptomatology.
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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 | 0.019 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".