Age effects on virtual reality tasks vary by interaction method
Ageing, Digital Literacy, and Interaction Modality in Immer-sive Virtual Reality: Psychomotor Performance, Cognitive Flexibility, and Their Processing-Speed Association
Human-Computer InteractionComputers and Society
Summary
This paper looks at how age and digital skills influence how well people do tasks in virtual reality (VR). Older people tend to be slower at doing VR tasks, but the way they interact, like using hand controllers or eye movements, changes how much age matters. People with better digital skills do better on some VR thinking tests but not on all tasks. The study suggests VR assessments should pick one interaction method and consider both digital skills and motor speed when interpreting results.
What this means in practice
- •For virtual reality developers: Design VR training and assessment tools that account for age differences and select interaction methods that balance speed and age sensitivity.
- •For accessibility specialists: Create inclusive XR experiences by evaluating digital literacy and motor speed effects, enabling better adaptation for older adults.
Authors
Panagiotis Kourtesis, Katerina Denaxa, Lydia Asimakopoulo, Petros Roussos, Maria Roussou
Abstract
Extended reality (XR) increasingly supports training and cognitive assessment, yet the age sensitivity of its interaction techniques is unclear. This study examined age, digital literacy, and interaction modality as correlates of psychomotor and cognitive-flexibility performance in immersive virtual reality (VR). Two hundred and two adults (19-90 years) completed a five-mode Fitts' law task (eye-gaze, head-gaze, controller ray-casting, virtual finger, and controller direct touch), the Trail Making Test in VR (TMT-VR), and a digital-literacy questionnaire. Age was associated with slower task times across modes, but controller direct touch carried the steepest relative age gradient yet remained among the fastest in absolute terms; technique altered relative age sensitivity without determining absolute efficiency. Higher digital literacy was associated with faster TMT-VR completion but not Fitts task times. A Fitts-derived speed score predicted TMT-VR performance beyond age and partly accounted for its age association, consistent with shared processing-speed variance; an exploratory full-battery extension confined the Fitts-score association to completion-time and error-adjusted-time indices and the digital-literacy association to error-adjusted-time indices, not wrong-target errors, mean selection distance, or relative Part B indices. Age-inclusive XR assessment should standardise interaction modality, evaluate rather than exclude mid-air direct selection, and interpret cognitive scores alongside digital literacy and psychomotor speed.