Toward a multimodal measurement model for the neurobehavioral trait of affiliative capacity

A growing body of research supports the value of a multimodal assessment approach, drawing on measures from different response modalities, for clarifying how core biobehavioral processes relate to various clinical problems and dimensions of psychopathology. Using data for 507 healthy adults, the current study was undertaken to integrate self-report and neurophysiological (brain potential) measures as a step toward a multimodal measurement model for the trait of affiliative capacity (AFF) - a biobehavioral construct relevant to adaptive and maladaptive social-interpersonal functioning. Individuals low in AFF exhibit a lack of interpersonal connectedness, deficient empathy, and an exploitative-aggressive social style that may be expressed transdiagnostically in antagonistic externalizing or distress psychopathology. Specific aims were to (1) integrate trait scale and brain potential indicators into a multimodal measure of AFF and (2) evaluate associations of this multimodal measure with criterion variables of different types. Results demonstrated (1) success in creating a multimodal measure of AFF from self-report and neural indicators, (2) effectiveness of this measure in predicting both clinical-diagnostic and neurophysiological criterion variables, and (3) transdiagnostic utility of the multimodal measure at both specific-disorder and broad symptom-dimension levels. Our findings further illustrate the value of psychoneurometric operationalizations of biobehavioral trait dimensions as referents for clarifying transdiagnostic relationships between biological systems variables and empirically defined dimensions of psychopathology.

Incorporating neurophysiological measures into clinical assessments: Fundamental challenges and a strategy for addressing them

Recent scientific initiatives have called for increased use of neurobiological variables in clinical and other applied assessments. However, the task of incorporating neural measures into psychological assessments entails significant methodological challenges that have not been effectively addressed to date. As a result, neurophysiological measures remain underutilized in clinical and applied assessments, and formal procedures for integrating such measures with report-based measures are lacking. In this article, we discuss major methodological issues that have impeded progress in this direction, and propose a systematic research strategy for integrating neurophysiological measures into psychological assessment protocols. The strategy we propose is an iterative psychoneurometric approach that provides a means to establish multimethod (MM) measurement models for core biobehavioral traits that influence functioning across diverse areas of life. We provide a detailed illustration of a MM model for one such trait, inhibitory control (inhibition-disinhibition), and highlight work being done to develop counterpart models for other biobehavioral traits (i.e., threat sensitivity, reward sensitivity, affiliative capacity). We discuss how these measurement models can be refined and extended through use of already existing data sets, and outline steps that can be taken to establish norms for MM assessments and optimize the feasibility of their use in everyday practice. We believe this model-oriented strategy can provide a viable pathway toward effective use of neurophysiological measures in routine clinical assessments. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Psychoneurometric assessment of dispositional liabilities for suicidal behavior: phenotypic and etiological associations

BACKGROUND

Can core genetic liabilities for suicidal behavior be indexed using psychological and neural indicators combined? The current work addressed this question by examining phenotypic and genetic associations of two biobehavioral traits, threat sensitivity (THT) and disinhibition (DIS) - operationalized as psychoneurometric variables (i.e., composites of psychological-scale and neurophysiological measures) - with suicidal behaviors in a sample of adult twins.

METHODS

Participants were 444 identical and fraternal twins recruited from an urban community. THT was assessed using a psychological-scale measure of fear/fearlessness combined with physiological indicators of reactivity to aversive pictures, and DIS was assessed using scale measures of disinhibitory tendencies combined with indicators of brain response from lab performance tasks. Suicidality was assessed using items from structured interview and questionnaire protocols.

RESULTS

THT and DIS each contributed uniquely to prediction of suicidality when assessed psychoneurometrically (i.e., as composites of scale and neurophysiological indicators). In addition, these traits predicted suicidality interactively, with participants high on both reporting the greatest degree of suicidal behaviors. Biometric (twin-modeling) analyses revealed that a high percentage of the predictive association for each psychoneurometric trait (83% for THT, 68% for DIS) was attributable to genetic variance in common with suicidality.

CONCLUSIONS

Findings indicate that psychoneurometric assessments of biobehavioral traits index genetic liability for suicidal behavior, and as such, can serve as innovative targets for research on core biological processes contributing to severe psychopathology, including suicidal proclivities and actions.