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Stress and Human-Computer Interaction at the Workplace: Unobtrusive Tracking With Wearable Sensors and Computer Logs


The relationship between workplace stress and computer use has mostly been investigated with self-reports or in controlled environments. However, self-report methods are prone to memory and emotion expression biases, and can be interruptive to employees when implemented for continuous stress tracking in real workplace environments. Researchers have explored the use of wearable sensors for unobtrusive and continuous stress tracking, but mostly in controlled laboratory settings, which limit the understanding of factors influencing stress in real-workplace environments, and the extent to which passive sensing can reveal information about stress during uncontrolled computer interactions.

This dissertation presents novel findings on computer use and stress at the workplace by employing computational methods leveraging computer activity logging and wearable devices that unobtrusively and continuously measured physiological stress through heart-rate variability in two real-world workplace settings: information work and medical work.

In the first part of the dissertation, fifty office employees were tracked for three to four weeks. Time spent on the work computer during and outside workhours, email work strategy, window switching, and computer activity types explained 14\% of the variance in the daily stress duration. Individual differences (personality and work-life balance) moderate the relationship between workplace computer use factors and stress. A novel measure of variability in daily computer work was associated with perceived job demands, effort and overcommitment and arousal. Employees’ perspectives on technology-supported stress tracking at the workplace indicated trust in algorithmic output, confirmation bias, and challenges balancing unobtrusiveness and engagement.

The second part of the dissertation analyzed how physicians use Electronic Health Record (EHR) systems and measured their physiological stress throughout the workday. One month of EHR logs of 1275 physicians were analyzed to characterize EHR use. Temporal patterns of EHR inbox use were found to be different from other EHR functions in their distribution throughout the day. Factors associated with high EHR inbox use were identified. Physiological stress data were collected for 47 physicians for a week and paired with their EHR logs. Among three patterns of EHR inbox work identified, the pattern characterized by working mostly outside of workhours had the longest average stress duration. Inbox work duration, the rate of EHR window switching, working outside of workhours and batching inbox work were associated with physicians’ daily stress duration.

By evaluating a range of computer use factors and their association with daily physiological stress, the dissertation extends previous work that often focused on specific computer tasks or used self-reports. I provide recommendations and design implications for supporting different personal and organizational technology-supported stress tracking goals, and suggest future areas of work.

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