Hold Tight: Identifying Behavioral Patterns During Prolonged Work in VR through Video Analysis

TL;DR

This study investigates how knowledge workers behave during prolonged VR use by analyzing 559 hours of video from 16 participants across five VR days and five physical days. Using ELAN-based coding of 17 action categories and repeated-measures ANOVA, the authors reveal patterns of adaptation, such as reduced headset adjustments and supports, and longer but less frequent HMD-off periods, alongside persistent disruptions to eating and interactions with the physical world. The findings highlight gender differences in HMD-support behaviors and significant VR-versus-physical contrasts in screen time, standing, and everyday tasks, underscoring ergonomic and design challenges in long-duration VR work. The work demonstrates the value of extended, in-the-wild video analysis for informing hardware ergonomics and long-term usability considerations for VR-enabled knowledge work.

Abstract

VR devices have recently been actively promoted as tools for knowledge workers and prior work has demonstrated that VR can support some knowledge worker tasks. However, only a few studies have explored the effects of prolonged use of VR such as a study observing 16 participant working in VR and a physical environment for one work-week each and reporting mainly on subjective feedback. As a nuanced understanding of participants' behavior in VR and how it evolves over time is still missing, we report on the results from an analysis of 559 hours of video material obtained in this prior study. Among other findings, we report that (1) the frequency of actions related to adjusting the headset reduced by 46% and the frequency of actions related to supporting the headset reduced by 42% over the five days; (2) the HMD was removed 31% less frequently over the five days but for 41% longer periods; (3) wearing an HMD is disruptive to normal patterns of eating and drinking, but not to social interactions, such as talking. The combined findings in this work demonstrate the value of long-term studies of deployed VR systems and can be used to inform the design of better, more ergonomic VR systems as tools for knowledge workers.

Figures (2)

• Figure 1: Violin plots, showing the number and total duration of events per hour in vr separated by day, time and gender. The red dot displays the arithmetic mean. Stars indicate the level of significance in post-hoc tests: $*<0.05$, $**<0.01$, $***<0.001$.
• Figure 2: Violin plots showing the number of events per hour for vr and physical. The red dot displays the arithmetic mean. Stars indicate the level of significance in post-hoc tests: $*<0.05$, $**<0.01$, $***<0.001$.