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Eye-Based Construct Measurement and Its Validity

Feiyan Jia et al.

Journal of Database Management2025https://doi.org/10.4018/jdm.394245article
AJG 1ABDC A
Weight
0.50

Abstract

Objective eye movement data have the potential to measure users' states instantly and in real time, providing a basis for timely intervention and personalized adaptation. Despite the broad applicability of eye-based construct measurement, research on its development and validation remains limited. Following the preferred reporting items for systematic reviews and meta-analyses guidelines, this review analyzes 127 studies that investigate the use of eye-tracking metrics to measure abstract constructs and the corresponding validity evidence. The findings reveal that eye-tracking metrics can measure a wide variety of constructs. Drawing on validity evidence commonly employed in psychometric-based construct measurement, this study synthesizes and summarizes validity evidence applicable to eye-based construct measurement. To illustrate the application of eye-tracking metrics and their supporting evidence, this article uses the example of detecting a vehicle driver's cognitive load, offering guidance for future studies and practical applications.

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https://doi.org/https://doi.org/10.4018/jdm.394245

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@article{feiyan2025,
  title        = {{Eye-Based Construct Measurement and Its Validity}},
  author       = {Feiyan Jia et al.},
  journal      = {Journal of Database Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.4018/jdm.394245},
}

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Eye-Based Construct Measurement and Its Validity

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.