Heart Rate and Heart Rate Variability Correlate with Clinical Reasoning Performance and Self-Reported Measures of Cognitive Load

Abstract

Cognitive load is a key mediator of cognitive processing that may impact clinical reasoning performance. The purpose of this study was to gather biologic validity evidence for correlates of different types of self-reported cognitive load, and to explore the association of self-reported cognitive load and physiologic measures with clinical reasoning performance. We hypothesized that increased cognitive load would manifest evidence of elevated sympathetic tone and would be associated with lower clinical reasoning performance scores. Fifteen medical students wore Holter monitors and watched three videos depicting medical encounters before completing a post-encounter form and standard measures of cognitive load. Correlation analysis was used to investigate the relationship between cardiac measures (mean heart rate, heart rate variability and QT interval variability) and self-reported measures of cognitive load, and their association with clinical reasoning performance scores. Despite the low number of participants, strong positive correlations were found between measures of intrinsic cognitive load and heart rate variability. Performance was negatively correlated with mean heart rate, as well as single-item cognitive load measures. Our data signify a possible role for using physiologic monitoring for identifying individuals experiencing high cognitive load and those at risk for performing poorly during clinical reasoning tasks.

Analyzing Relationships Between Causal and Assessment Factors of Cognitive Load: Associations Between Objective and Subjective Measures of Cognitive Load, Stress, Interest, and Self-Concept

“…This theoretical distinction is powerful because it allows to separate internal and external dimensions of cognitive load and can guide further research (Paas and van Merriënboer, 1994;Choi et al, 2014). However, mental load and mental effort are typically assessed using subjective self-reports on questionnaires (e.g., Krell, 2017), which assumes that the respondents are aware of their actual amount of cognitive load, which they invested to solve a task (Solhjoo et al, 2019). Furthermore, such subjective measures have been critically discussed due to issues of validity (de Jong, 2010;Kirschner et al, 2011;van Gog and Paas, 2008).…”

“…Furthermore, such subjective measures have been critically discussed due to issues of validity (de Jong, 2010;Kirschner et al, 2011;van Gog and Paas, 2008). Hence, some studies use objective, physiological measures as indicators for cognitive load (e.g., various heart rate or pupillometric measures; Solhjoo et al, 2019;Zheng and Cooke, 2012). However, it is not clear to which extent objective measures converge with subjective measures as indicators for an individual's cognitive load in the corresponding contexts.…”

Measuring Cognitive Load: Heart-rate Variability and Pupillometry Assessment

“…From the heart-rate variability, we expect light not to have any effect and cognitive load difference should be visible (similar to [22]).…”

“…Heart-rate variability (HRV) was deeply studied as a cognitive load indicator [22]. The autonomic nervous system contains the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS), which give respond to the body on activity and rest situations respectively.…”

“…The heart-rate variability is a well-studied metric and was shown to work well in certain scenarios [22], but it is sensitive to variance in the electromagnetic field and breathing cycle [7]. Recent high frequency micro-camera grant the possibility to use pupil information that acts as a proxy of mental effort [25], but wearable (glasses) are noisy and sensitive to the environment [3].…”