Adapting psychophysiological data collection for COVID-19: The "Virtual Assessment" model.

Abstract

The COVID-19 pandemic has significantly disrupted research activities globally. Researchers need safe and creative procedures to resume data collection, particularly for projects evaluating infant mental health interventions. Remote research is uniquely challenging for psychophysiological data collection, which typically requires close contact between researchers and participants as well as technical equipment frequently located in laboratory settings. In accordance with public health guidance, we adapted procedures and developed novel protocols for a "virtual assessment" in which women and infants provided behavioral and psychophysiological data from their own homes while researchers coordinated remotely. Data collected at virtual visits included video-recorded parent-child interactions and autonomic nervous system data. Adaptations were designed to optimize safety and data quality while minimizing participant burden. In the current paper, we describe these adaptations and present data evaluating their success across two sites in the United States (University of Delaware and University of Utah), focusing specifically on autonomic nervous system data collected during the well-validated Still-Face Paradigm (SFP). We also discuss advantages and challenges of translating traditional lab procedures into the virtual assessment model. Ultimately, we hope that disseminating these procedures will help other researchers resume safe data collection related to infant mental health during the COVID-19 pandemic and beyond.