Examining Emotion Regulation and Phasic Versus Tonic Physiological Activation in a Medical Diagnostic Reasoning Simulation

• In Event: 34.030 - Physiology of Emotion in Education: Theory, Methodology, and Insight

Abstract

Objectives. Research on emotions in academic achievement contexts has made great strides in the last couple of decades, including a growing number of studies exploring objective measures of emotion, such as physiological activation, as alternatives to self-reports (Calvo & D’Mello, 2010; Harley, 2015). Understanding the physiological component of emotion and its relationship with learning and individual differences is critical, but also challenging given the diversity of available approaches to measure it. Moreover, widely-used theories of emotion such as the process model of emotion regulation (Gross, 2015) and control-value theory of achievement emotion (Pekrun & Perry, 2014) do not distinguish between biological sources of activation and hypothesized relations with learning and individual differences. This paper will address this gap by examining the relationship between individuals’ emotion regulation (ER) tendencies and two different components of the electrodermal activation complex (EDA); both of which are thought to convey different information about emotional activation (Dawson, et al., 2001).

Methods. Data from an ongoing study were collected and analyzed from 33 medical students from a North American university who completed a 2.5 hour learning session in BioWorld (Lajoie, 2009). The analysis compared ER tendencies and intensity of emotional responding. The ER questionnaire (ERQ; Gross & John, 2003) was used to measure participant’s tendencies to regulate their emotions using reappraisal (i.e. changing how a situation is evaluated) and suppression strategies (i.e. changing how an emotion is expressed). The intensity of emotional responding was measured using one of two physiological activation measurement bracelets: Biopac (Alzoubi et al., 2015) which measured phasic EDA (n = 15) and Q-Sensor (Harley et al., 2015, 2016) which measured tonic EDA (n = 18). Phasic EDA is characterized by rapidly changing, meaningful peaks in activation whereas tonic EDA is slow changing, smooth, and understood in relation to individual’s physiological baseline (Braithwaite, et al., 2013).

Results. Tonic EDA data from the Q-Sensor bracelet was previously analyzed in Harley and colleagues (2016); this paper will summarize the new phasic Biopac results and contrast them with the latter using the same research questions. Consistent with previous tonic EDA findings (Harley et al., 2016), a multiple linear regression revealed a significant predictive model of emotion regulation tendencies and phasic physiological activation (R2 = .44, p = .03). Counter to prior tonic EDA findings, learner tendencies to use reappraisal positively and significantly predicted emotional intensity (B = .52, p = .034) while the inverse was true for suppression strategies (B = -.41, p = .085). Results related to learning and self-reported emotions will also be presented.

Significance. Formally comparing results obtained from phasic and tonic EDA provides (1) preliminary evidence that understanding physiological expressions of emotion requires an appreciation of the biological information being drawn upon and that (2) a more nuanced term than “activation” or “arousal” may be needed to meaningfully understand the relation between these objective measures of emotion and (a) learners and (b) learning. Theoretical, analytical, and methodological implications are discussed and best practices for analyzing EDA data in educational contexts will be shared.

Authors

• Jason Matthew Harley, University of Alberta

• Amanda Jarrell, McGill University

• Susanne P. Lajoie, McGill University