Not your typical mouse study.
Work-related stress is a growing global problem.
But itâs not growing fast enough, apparently, for these researchers, who envision workers being subject to continuous real-time collection of stress measurements so they can given timely stress-relieving interventions.
This can be achieved, they propose, by monitoring keyboard and mouse actions (such as keystroke error rate and wildness of mouse movements) of people while they work, which correlate even better than heart rate with workersâ self-reported stress levels. Â
Laboratory studies of stress-detection to date have lacked verisimilitude, among other problems, the authors of the current study write. They set out to remedy this with a machine-learning model based on combined behavioural, physiological and psychological data: namely, keyboard and mouse movements (via custom software), heart rate variability (via a wearable) and salivary cortisol (tested periodically during the experiment), and self-reported stress (via the Multidimensional Mood State Questionnaire).
Why pick keyboard and mouse movements? The connection is based on theories of stress in which a relevant stressor is detected and oneâs own resources deemed inadequate to meet it. This âimbalance between resources and demands leads to an increased signal-to-noise ratio in the brain, which is reflected in increased variations in human movementsâ.
Also, spying on peopleâs movements through alternative means such as camera and audio is a little invasive, âespecially in a work contextâ. No kidding.
The established the effectiveness of the technique by putting 90 participants in a simulated insurance company office environment with real-work-like tasks, randomly dividing them in two stress conditions and one control condition.
Stress condition subjects were then mock-interviewed for a promotion in front of their peers by an actor line manager, while the controls had ânon-evaluative professional training which involved reading a work-related dialogue aloud in unisonâ.
âAs an additional stressor, participants in stress condition 2 received frequent chat messages from their manager ⌠which interrupted them in their workflow with urgent questions related to their tasks and performance.â
This all would have been funny to watch, if nothing else.
The authors ponder what level of accuracy a model would need to attain before it becomes so annoying that workers would rather be left alone with their stress: âwhile false negatives increase the risk of missing to adequately treat a person at risk for serious stress-induced health consequences, too many false positives could simply impede a userâs workflow, increasing levels of stress and the likelihood of dropout from the stress management programmeâ.Â
In conclusion â ours, not theirs â the Back Page suspects an algorithm wrote this paper, as only an algorithm would think measuring a employeeâs stress levels through their computer hardware and jumping in with an unspecified intervention when those stress levels reach a certain threshold is a better idea than just making your workplace a little less damn stressful in the first place.
Sending story tips to penny@medicalrepublic.com.au is proven to relieve workplace tension.