Cognitive workload in extended reality (XR) interventions for older adults: an integrative review

Introduction Cognitive workload is a key determinant of how older adults process information, perform tasks, and engage with technology-driven interventions amid age- related physiological changes. Its optimization is therefore essential to ensure that technologies remain effective and accessible rather than overwhelming. Although Extended Reality (XR) is increasingly applied in health, rehabilitation, and cognitive training, its effectiveness depends on how cognitive workload is managed. However, studies that explicitly examine cognitive workload as an attribute in XR interventions for older adults remain limited. Methodology This integrative review synthesizes existing literature to examine cognitive workload in XR- based interventions, including an assessment of bibliometric trends, study purposes and outcomes, keyword network analysis, XR technologies with cognitive load metrics, and the tools used to measure cognitive workload. Guided by Whittemore and Knafl’s five-stage framework, 14 studies (n = 14) published from 2010 to 2026 were included in the final analysis. Results and Discussion Most papers are published in health journals (n = 9), with samples ranging from 10 to 114 participants (M = 32.29, SD = 24.04), primarily using non-probability sampling, and concentrated in the Americas (n = 6) and Western Pacific (n = 5). Thematization of article purpose and outcome revealed five domains, namely: (1) Influences: Cognitive Load and Performance, (2) Interventions: Intervention and Rehabilitation, (3) Interactions: Dual-Tasking and Performance, (4) Interception: User Experience and Safety, and (5) Interface: Interface Design and Usability. Similarly, keyword network analysis conveyed nine clusters describing article groups, namely: (1) Computerized Rehabilitation, (2) Cueing via Mixed Reality, (3) Concurrent Tasks and Falls, (4) Cognitive Spatial AR, (5) Cognitive Hearing and Balance, (6) Cognitive Load and Movement, (7) Cognitive and Motor Control, (8) Consumer-Friendly Design, and (9) Computer Interaction and Games. Among all XR types, virtual reality was the most commonly used modality (n = 7). In terms of tool measurement, cognitive workload was assessed through diverse, construct-based approaches spanning subjective self-report, behavioral/task-performance, physiological/eye-tracking, and neurobiological methods, with one study combining multiple measures. Conclusion Ultimately, findings indicate that while XR interventions vary in application and methodology, cognitive workload is conceptualized and measured in diverse ways. Future studies should use clearer, age-sensitive, and XR-specific approaches to measuring cognitive workload so that findings can be compared across studies and interpreted more directly for rehabilitation and health-technology design. Systematic Review Registration https://osf.io/t9gan/overview .