From the Lab to the Market

Measuring user engagement for the “average” users and experiences: Can psychophysiological measurement help?

I recently attended the Input-Output conference in Brighton, UK. The theme of the conference was “Interdisciplinary approaches to Causality in Engagement, Immersion, and Presence in Performance and Human-Computer Interaction”. I wanted to learn about  psychophysiological measurement.

I am myself on a quest: understand what is user engagement and how to measure it, with a focus on web applications with thousands to millions of users. To this end, I am looking at three measurement approaches: self-reporting (e.g., questionnaires); observational methods (e.g., facial expression analysis, mouse tracking); and of course web analytics (dwell time, page views, absence time).

Observational methods include measurement from psychophysiology, a branch of physiology that studies the relationship between physiological processes and thoughts, emotions, and behaviours. Indeed, the body responds to physiological processes: when we exercise, we sweat; when we get embarrassed, our cheeks get red and warm.

Common measurements include:

• Event-related potentials – the electroencephalogram (EEG) is based on recordings of electrical brain activity measured at the surface of the scalp.
• Functional magnetic resonance imaging (fMRI) – this technique involves imaging blood oxygenation using an MRI machine
• Cardiovascular measures – heart rate (HR); beats per minute (BPM); heart rate variability (HRV).
• Respiratory sensors – monitor oxygen intake and carbon dioxide output.
• Electromyographic (EMG) sensors – measure electrical activity in muscles.
• Pupillometry – measures measure variations in the diameter of the pupillary aperture of the eye in response to psychophysical and/or psychological stimuli.
• Galvanic skin response (GSR) – measures perspiration/sweat gland activity, also called Skin Conductance Level  (SCL).
• Temperature sensors – measure changes in blood flow and body temperature.

I learned how these measures are used, why, and some outcomes. But I started to ask myself. Yes these measures can help understanding engagement (and other related phenomena) for extreme cases, for example:

• patient with a psychiatric disorder (such as depersonalisation disorder),
• strong emotion caused by an intense experience (a play where the audience is part of the stage, or when on a roller coaster ride), or
• total immersion (while playing a computer game), which actually goes beyond engagement.

In my work, I am measuring user engagement for the “average” users and experiences; millions of users who visit a news site on a daily basis to consume the latest news. Can these measures tell me something?

Some recent work published in the Journal of Cyberpsychology, Behavior, and Social Networking explored many of the above measures to study the body responses of 30 healthy subjects during a 3-minute exposure to a slide show of natural panoramas (relaxation condition), their personal social network account (Facebook), and a mathematical task (stress condition). They found differences in the measures depending on the condition. Neither the subjects nor the experiences were “extreme”. However, the experiences were different enough. Can a news portal experiment with three comparably distinct conditions?

Psychophysiology measurement can help understanding user engagement and other  phenomena. But to be able to do so for the average users or experiences, we are likely to need to conduct “large-ish scale” studies to obtain significant insights.

How large-ish? I do not know.

This is in itself an interesting and important question to ask, a question to keep in mind when exploring these types of measurement, as they are still expensive to conduct, cumbersome, and obtrusive. This is a fascinating area to dive into.

Image/photo credits: The Cognitive Neuroimaging Laboratory, and Image Editor and benarent ((Creative Commons BY).