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 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 | 0.017 | 0.075 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".