CVLT-II Forced Choice Recognition Trial as an Embedded Validity Indicator: A Systematic Review of the Evidence
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: The Forced Choice Recognition (FCR) trial of the California Verbal Learning Test, 2nd edition, was designed as an embedded performance validity test (PVT). To our knowledge, this is the first systematic review of classification accuracy against reference PVTs. METHODS: Results from peer-reviewed studies with FCR data published since 2002 encompassing a variety of clinical, research, and forensic samples were summarized, including 37 studies with FCR failure rates (N=7575) and 17 with concordance rates with established PVTs (N=4432). RESULTS: All healthy controls scored >14 on FCR. On average, 16.9% of the entire sample scored ≤14, while 25.9% failed reference PVTs. Presence or absence of external incentives to appear impaired (as identified by researchers) resulted in different failure rates (13.6% vs. 3.5%), as did failing or passing reference PVTs (49.0% vs. 6.4%). FCR ≤14 produced an overall classification accuracy of 72%, demonstrating higher specificity (.93) than sensitivity (.50) to invalid performance. Failure rates increased with the severity of cognitive impairment. CONCLUSIONS: In the absence of serious neurocognitive disorder, FCR ≤14 is highly specific, but only moderately sensitive to invalid responding. Passing FCR does not rule out a non-credible presentation, but failing FCR rules it in with high accuracy. The heterogeneity in sample characteristics and reference PVTs, as well as the quality of the criterion measure across studies, is a major limitation of this review and the basic methodology of PVT research in general. (JINS, 2016, 22, 851-858).
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it