Whose Signals Are Being Amplified? Toward a More Equitable Clinical Psychophysiology

Abstract

Research using psychophysiological methods holds great promise for refining clinical assessment, identifying risk factors, and informing treatment. Unfortunately, unique methodological features of existing approaches limit inclusive research participation and, consequently, generalizability. In this brief overview and commentary, we provide a snapshot of the current state of representation in clinical psychophysiology with a focus on the forms and consequences of ongoing exclusion of Black participants. We illustrate issues of inequity and exclusion that are unique to clinical psychophysiology and consider intersections among social constructions of Blackness and biased design of current technology used to measure electroencephalography, skin conductance, and other signals. We then highlight work by groups dedicated to quantifying and addressing these limitations. We discuss the need for reflection and input from a wider variety of affected individuals to develop and refine new technologies given the risk of further widening disparities. Finally, we provide broad recommendations for clinical-psychophysiology research.

Neural and psychophysiological markers of intolerance of uncertainty

“…While the broad extent of conceptual and methodological variability across the special issue highlights the wide-ranging relevance of intolerance of uncertainty to many processes, this variability also calls for efforts towards systematic investigation and operationalisations of intolerance of uncertainty on different outcome measures and within diverse sample populations (e.g. other samples from around the world; Running Head: Editorial for SI Kumar et al, 2021;Yao et al, 2021;and within non WEIRD samples;Bradford, et al, 2022). Systematic investigations through cross-lab collaboration efforts, largescale replication endeavours, and preregistration and standardisation of some methodological approaches will facilitate reproducibility (Baldwin, 2017).…”

Interdisciplinary views of fNIRS: Current advancements, equity challenges, and an agenda for future needs of a diverse fNIRS research community

“…In fact, data collected on participants with darker skin and hair is often discarded due to bad data quality (Webb et al, 2022), creating a source of methodological bias. Popular devices such as smartwatches and pulse oximetry monitoring devices that use optical light face the same issue, leading to the exclusion of meaningful data from a significant percentage of the general population (Bradford et al, 2022). This has been an issue present in most research, as people of color are notoriously underrepresented in research, including general statistics datasets such as National IQ datasets (Sear, 2022) and clinical psychology (Bradford et al, 2022).…”

“…Popular devices such as smartwatches and pulse oximetry monitoring devices that use optical light face the same issue, leading to the exclusion of meaningful data from a significant percentage of the general population (Bradford et al, 2022). This has been an issue present in most research, as people of color are notoriously underrepresented in research, including general statistics datasets such as National IQ datasets (Sear, 2022) and clinical psychology (Bradford et al, 2022). fNIRS researchers must work to develop proper data collection techniques for underrepresented populations including ensuring proper cap size and using tools to optimize optode-to-skin contact.…”

“…Optimizing signal quality for participants in which typical caps and optodes do not work presents an important challenge to hardware development. Technical challenges often involve dark, thick, and curly hair styles that greatly increase the distance from optode to scalp and absorb a portion of the signal light (Bradford et al, 2022). This creates a gap in the literature studying those with cultural differences that keep them from wearing a typical fNIRS cap and optodes.…”

“…While technological advancements have allowed the exploration of new research spaces, the hardware itself makes it difficult to collect fNIRS data on certain populations including people with darker skin and hair (Kwasa et al, 2022) and those with sensorymotor issues (Arenth et al, 2007). Another avenue for bias is from prejudice and harmful views present in society that infiltrate this type of research in many ways (Roberts et al, 2020;Bradford et al, 2022), that will be explored later in the paper (see Section 4).…”