Functional neurological disorder (FND) is an often-disabling condition characterized by neurological symptoms that are incongruent with recognized neurological or medical disease processes. Alongside the increased clinical interest in this condition, there remain diagnostic and conceptual challenges, with controversy pertaining to assessment methods, the notions of primary and secondary gain, and how testing should be used and interpreted. This is of particular importance for the pediatric population, where less work has been done and even less certainty exists around a codified understanding of FND mechanisms, subtypes, and frameworks. While the bulk of the literature to date on FND concerns adults, an emerging research-base is developing in children. Representing a meaningful proportion of pediatric neurology consultations, FND is a relevant condition for clinicians engaged in psychological and neuropsychological assessment. This commentary examines FND in children from a broader perspective, offering a preliminary view of FND, a review of primary and secondary gain constructs as they relate to FND, and diving in with a deeper perspective on psychological and neuropsychological assessment. Future directions for FND in children are offered and discussed.
Over-reporting is a form of response bias involving the exaggeration or fabrication of symptoms and impairment. Symptom validity tests (SVTs), including standalone measures and validity scales embedded within broadband personality inventories, are commonly used to assess over-reporting. Recent SVT development has increasingly emphasized symptom-domain specificity, including cognitive, somatic, and psychological presentations. This review examines current advances and challenges in symptom validity assessment, with particular attention to whether over-reporting indicators demonstrate meaningful domain-specific distinctions. Evidence regarding symptom-domain specificity remains mixed. Although some findings suggest that SVTs may differentially detect particular symptom presentations, other research indicates that these measures generally perform within a common range of over-reporting effects and do not consistently demonstrate the expected relationships between symptom domain and assessment context. To further evaluate these distinctions, we re-analyzed data from an independent meta-analysis of MMPI-2-RF over-reporting validity scales and conducted a random-effects meta-analysis of interscale correlations among MMPI-2-RF over-reporting indicators reported across the empirical literature. Across these complementary analyses, over-reporting indicators demonstrated substantial similarities in performance despite their proposed domain distinctions. Current evidence raises questions about the degree to which symptom-domain distinctions among over-reporting indicators reflect meaningfully separable constructs. Greater attention to construct definition, criterion selection, comparative scale performance, and multivariate patterns of responding is needed to determine when domain-specific interpretations are empirically warranted. Methodological and analytic improvements in these areas may strengthen the construct validity, clinical utility, and interpretive precision of symptom validity assessment.
Perinatal anxiety disorders and obsessive-compulsive disorder (OCD) are among the most prevalent conditions affecting birthing people during pregnancy and the postpartum period, yet remain systematically underidentified relative to perinatal depression. This review synthesizes current evidence on phenomenology, assessment, and treatment to support clinicians in delivering accurate, timely care. Perinatal anxiety affects 15–20
U.S. Veterans and service members undergoing disability evaluations represent a high-stakes assessment context in which broadband psychological instruments are used to evaluate response style and symptom credibility. This scoping review mapped empirical research on validity indicators from the MMPI, PAI, and MCMI families in Veterans Affairs and military disability-compensation settings. Seventeen studies met inclusion criteria. All included studies used MMPI-family or PAI instruments; no MCMI-family study met all eligibility criteria. Compensation-related contexts were generally associated with higher overreporting-scale scores or elevation rates, although findings varied by instrument, study design, analytic approach, and definition of compensation status. Several studies reported substantial intercorrelations among overreporting indicators, limiting scale-specific interpretation. Only four studies compared groups on elevation rates at recommended or established cut scores. Compensation context was operationalized inconsistently, including active claims, Compensation and Pension examinations, service-connected disability, Medical Evaluation Board status, and simulated disability conditions. No included study reported race- or ethnicity-stratified validity-scale findings. Current evidence supports contextual rather than uniform interpretation of validity-scale elevations. Future research should standardize compensation-context definitions, include more diverse samples, report classification metrics, and use advanced analytic approaches to clarify shared variance among indicators. Elevated scores should not be treated as direct evidence of intentional symptom exaggeration.
This commentary summarizes terminology and practice standards for assessing the validity of test scores obtained during neuropsychological evaluations. It also highlights conceptual gaps and emerging directions for improving validity assessment. The process of assessing the accuracy and interpretability of psychometric test scores is foundational to neuropsychology. However, terminology used to communicate these findings requires conceptual refinement to align with evolving practice standards and advances in psychometric theory. Such terminology must also reflect that validity problems are not reduced to poor effort or volitional exaggeration. Validity is a broader interpretive concern that applies to all practicing neuropsychologists, who must distinguish between presumed causes and patterns of invalidity, while also considering the intended use of scores relative to the patient and context. Symptom- and performance-based scores serve different interpretive purposes, and their validity should be evaluated separately. The strongest validity determinations are based on converging evidence across multiple complementary psychometric- and clinically-based indicators, with attention to base rates of invalid responding and genuinely low scores. Digital technologies may help the field keep pace with evolving standards and conceptual developments. Technologies can improve validity assessment by capturing more data, analyzing it with advanced algorithms, and doing so in ways that are more accessible for patients and efficient for clinicians. However, neuropsychologists must remain stewards of these digital methods, ensuring their development and use preserve clinical nuance, empirical rigor, and ethical standards. Used appropriately, digital tools may complement rather than replace the uniquely human aspects of validity assessment. Performance and symptom validity assessment is an evidence-based process used to determine whether neuropsychological test findings accurately reflect a person’s cognitive abilities or symptomatic experiences. However, terminology in this area has often been used inconsistently, blurring important distinctions among what validity measures assess, what invalid responding implies, and the factors that contribute to invalid responding. In this article, we clarify these distinctions by reviewing terminology used to describe validity assessment methods, patterns of invalid responding, and factors that may threaten validity. We then summarize best-practice standards for performance and symptom validity assessment, emphasizing the use of multiple psychometric and clinically based indicators to estimate the extent to which test scores reflect the constructs they are intended to represent. We explain why such validity findings must be interpreted in relation to the individual, the referral question, and the evaluation context, rather than being treated as sole or direct indicators of noncredible responding or its presumed causes. Finally, we explain how emerging technologies may improve this assessment process by capturing and analyzing additional information underlying a person’s invalid responses. We further describe how such technologies may help distinguish between the presence and appearance of invalid responding and its presumed causes. Ultimately, we contend that, as long as neuropsychologists remain stewards of these innovations, digital technologies can improve validity assessment while preserving the central role of clinical judgment.
