Medical Expert Witness Assessments (MEWA) are international standard to generate information involving medical questions in litigations, such as the capacity to work. While this procedure is widely utilized and guidelines for assessing the validity of symptoms using psychometric tools and non-psychometric criteria have been developed, the scientific foundation of this multimodal Criteria-Based Validity Assessment (CVA) is weak. This study aims to provide empirical validation of CVA using psychometric Symptom (SVT) and Performance Validity Tests (PVT) as areference point. 466 MEWA conducted in the law of the German Statutory Pension Insurance (GPI), all uniformly having addressed the question of the capacity to work, were analyzed. Information about scores regarding the Structured Inventory of Malingered Symptomatology (SIMS), Amsterdam Short-Term Memory Test (ASTM) aswell as the seven CVA criteria were extracted. A logistic regression using CVA data to group the MEWA into plausible and implausible (over- and/or under reporting of symptoms) cases showed a significant association between implausible cases and SIMS scores ( OR = 1. 067; 95% - CI [1.037, 1.098]; p <. 0 01) as well as ASTM scores ( OR = 0.965; 95% - CI [0.936, 0.994]; p <.05). In this highly comparable real-world dataset, we find evidence that CVA is indeed a valid tool in terms of convergent validity using a SVT and PVT as the point of reference and provide descriptive data on SVT and PVT that facilitates the interpretation of psychometric test results in such cases.

Background: Medical expert witness assessments (MEWAs) evaluate case validity on the basis of both psychometric and non-psychometric modalities. Although symptom validity tests (SVTs) and performance validity tests (PVTs) are widely used, many thresholds were developed in analogue and known-groups validation contexts, and their transferability to MEWAs remains uncertain. Prior research validated a Criteria-Based Validity Assessment (CVA) as a multimodal framework for assessing case plausibility, but it remained unclear whether CVA and psychometric thresholds perform similarly across different legal contexts, such as pension insurance versus accident insurance evaluations. Objective: This study aimed to investigate differences in CVA, SVT, and PVT results across pension and accident insurance cases. Methods: A total of 721 MEWAs (572 pension; 149 accident) were analyzed. CVA criteria were rated by trained raters, and response biases were assessed psychometrically using the SIMS and the ASTM. Two-component beta-binomial mixture models were applied to derive CVA plausibility thresholds. Results: Mixture modeling reliably identified a distinct bimodal distribution of conspicuous CVA criteria counts, interpreted as plausible and implausible subgroups in both pension and accident cases, with ≥4 conspicuous CVA criteria representing the optimal plausibility threshold. Pension claimants showed significantly higher SIMS scores and lower ASTM scores than accident claimants, independent of case plausibility. Conclusion: CVA can be used to assess validity information collected from multiple data sources (longitudinal and cross-sectional) and to assess the validity of health-related claims across different legal settings. CVA, however, was not a tool for measuring context-specific response biases. Cases with ≤2 conspicuous CVA criteria may be valid, cases with three conspicuous criteria require individual examination because feigning is possible but not certain, and ≥4 conspicuous criteria supported a conservative classification of CVA-defined case implausibility.