Detecting Negative Response Bias Within the Trauma Symptom Inventory–2 (TSI-2): a Review of the Literature
Bibliographic record
Abstract
Abstract This systematic review was performed to summarize existing research on the symptom validity scales within the Trauma Symptom Inventory–Second Edition (TSI-2), a relatively new self-report measure designed to assess the psychological sequelae of trauma. The TSI-2 has built-in symptom validity scales to monitor response bias and alert the assessor of non-credible symptom profiles. The Atypical Response scale (ATR) was designed to identify symptom exaggeration or fabrication. Proposed cutoffs on the ATR vary from ≥ 7 to ≥ 15, depending on the assessment context. The limited evidence available suggests that ATR has the potential to serve as measure of symptom validity, although its classification accuracy is generally inferior compared to well-established scales. While the ATR seems sufficiently sensitive to symptom over-reporting, significant concerns about its specificity persist. Therefore, it is proposed that the TSI-2 should not be used in isolation to determine the validity of the symptom presentation. More research is needed for development of evidence-based guidelines about the interpretation of ATR scores.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".