Abstract
The human pupil changes size in response to processing demands or cognitive (work)load and emotional processing. Therefore, it is important to test if automatic tracking of cognitive load by pupil-size measurement is possible under conditions of varying levels of emotion-related processing. Here, we investigated this question in an experiment simulating a highly relevant applied context in which cognitive load and emotional processing can vary independently: a clinical interview. Our participants conducted a live clinical interview via computer monitor with a confederate as an interviewee. We used eye-tracking and automatic extraction of participants’ pupil size to monitor cognitive load (single vs. dual tasks, between participants), while orthogonally varying the emotional content of the interviewee’s answers (neutral vs. negative, between participants). We ensured participants’ processing of the verbal content of the interview by asking all participants to report on the content of the interview in a subsequent memory test and by asking them to discriminate if the answers of the interviewee referred to only herself or to somebody else (too). In the dual-task condition, participants had to monitor additionally if the facial emotional expressions of the interviewee matched the content of her verbal responses. Results showed that pupil-size extraction reliably discriminated between high and low cognitive load, albeit to a lower degree under negative emotional content conditions. This was possible with an algorithmic online measure of cognitive load as well as with a conventional pupil-size measure, providing proof of the external validity of the algorithm/online measure.
Published Version
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