Challenges and Opportunities for Human Behavior Research in the Coronavirus Disease (COVID-19) Pandemic

Abstract

The COVID-19 pandemic is a serious public health crisis that is causing major worldwide disruption. So far, the most widely deployed interventions have been non-pharmacological (NPI), such as various forms of social distancing, pervasive use of personal protective equipment (PPE), such as facemasks, shields, or gloves, and hand washing and disinfection of fomites. These measures will very likely continue to be mandated in the medium or even long term until an effective treatment or vaccine is found (Leung et al., 2020). Even beyond that time frame, many of these public health recommendations will have become part of individual lifestyles and hence continue to be observed. Moreover, it is implausible that the disruption caused by COVID-19 will dissipate soon. Analysis of transmission dynamics suggests that the disease could persist into 2025, with prolonged or intermittent social distancing in place until 2022 (Kissler et al., 2020). Human behavior research will be profoundly impacted beyond the stagnation resulting from the closure of laboratories during government-mandated lockdowns. In this viewpoint article, we argue that disruption provides an important opportunity for accelerating structural reforms already underway to reduce waste in planning, conducting, and reporting research (Cristea and Naudet, 2019). We discuss three aspects relevant to human behavior research: (1) unavoidable, extensive changes in data collection and ensuing untoward consequences; (2) the possibility of shifting research priorities to aspects relevant to the pandemic; (3) recommendations to enhance adaptation to the disruption caused by the pandemic. Data collection is very unlikely to return to the “old” normal for the foreseeable future. For example, neuroimaging studies usually involve placing participants in the confined space of a magnetic resonance imaging scanner. Studies measuring stress hormones, electroencephalography, or psychophysiology also involve close contact to collect saliva and blood samples or to place electrodes. Behavioral studies often involve interaction with persons who administer tasks or require that various surfaces and materials be touched. One immediate solution would be conducting “socially distant” experiments, for instance, by keeping a safe distance and making participants and research personnel wear PPE. Though data collection in this way would resemble pre-COVID times, it would come with a range of unintended consequences (Table 1). First, it would significantly augment costs in terms of resources, training of personnel, and time spent preparing experiments. For laboratories or researchers with scarce resources, these costs could amount to a drastic reduction in the experiments performed, with an ensuing decrease in publication output, which might further affect the capacity to attract new funding and retain researchers. Secondly, even with the use of PPE, some participants might be reluctant or anxious to expose themselves to close and unnecessary physical interaction. Participants with particular vulnerabilities, like neuroticism, social anxiety, or obsessive-compulsive traits, might find the trade-off between risks, and gains unacceptable. Thirdly, some research topics (e.g., face processing, imitation, emotional expression, dyadic interaction) or study populations (e.g., autistic spectrum, social anxiety, obsessive-compulsive) would become difficult to study with the current experimental paradigms (Table 1). New paradigms can be developed, but they will need to first be assessed for reliability and validated, which will undoubtedly take time. Finally, generalized use of PPE by participants and personnel could alter the “usual” experimental setting, introducing additional biases, similarly to the experimenter effect (Rosenthal, 1976). Table 1. Possible consequences of non-pharmacological interventions for COVID-19 on human behavior research. Data collection could also adapt by leveraging technology, such as running experiments remotely via available platforms, like for instance Amazon's Mechanical Turk (MTurk), where any task that programmable with standard browser technology can be used (Crump et al., 2013). Templates of already-programmed and easily customizable experimental tasks, such as the Stroop or Balloon Analog Risk Task, are also available on platforms like Pavlovia. Ecological momentary assessment is another feasible option, since it was conceived from the beginning for remote use, with participants logging in to fill in scales or activity journals in a naturalistic environment (Shiffman et al., 2008). Increasingly affordable wearables can be used for collecting physiological data (Javelot et al., 2014). Web-based research was already expanding before the pandemic, and the quality of the data collected in this way is comparable with that of laboratory studies (Germine et al., 2012). Still, there are lingering issues. For instance, for some MTurk experiments, disparities have been evidenced between laboratory and online data collection (Crump et al., 2013). Further clarifications about quality, such as consistency or interpretability (Abdolkhani et al., 2020), are also needed for data collected using wearables. Beyond updating data collection practices, a significant portion of human behavior research might change course to focus on the effects of the pandemic. For example, the incidence of mental disorders or of negative effects on psychological and physical well-being, particularly across populations of interest (e.g., recovered patients, caregivers, and healthcare workers), are crucial areas of inquiry. Many researchers might feel hard-pressed to not miss out on studying this critical period and embark on hastily planned and conducted studies. Multiplication and fragmentation of efforts are likely, for instance, by conducting highly overlapping surveys in widely accessible and oversampled populations...