Threats to the validity of eye-movement research in psychology
Open accessAbstract
Eyetracking research in psychology has grown exponentially over the past decades, as equipment has become cheaper and easier to use. The surge in eyetracking research has not, however, been equaled by a growth in methodological awareness, and practices that are best avoided have become commonplace. We describe nine threats to the validity of eyetracking research and provide, whenever possible, advice on how to avoid or mitigate these challenges. These threats concern both internal and external validity and relate to the design of eyetracking studies, to data preprocessing, to data analysis, and to the interpretation of eyetracking data.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
All eye-tracking sessions were conducted under stable lighting conditions with screen resolution and display scaling held constant.
“All sessions were conducted under stable lighting conditions, with the screen resolution and display scaling held constant (Carter and Luke, 2020; Orquin and Holmqvist, 2018).”
From Responsible use of generative AI in Chinese vocational education: eye-tracking evidence on source verification and immediate near-transfer across three information-seeking conditions (2026) · cites this paper as Orquin and Holmqvist, 2018
Cites
Stereotypes and prejudice: Their automatic and controlled components
Devine, P. G. (1989) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.56.1.5 · Cited by 5,673 · see citing works
The Handbook of Research Synthesis and Meta-Analysis
(2019) · doi:10.7758/9781610448864 · Cited by 4,553 · see citing works
Gaze bias both reflects and influences preference
Shimojo, S., Simion, C., Shimojo, E., & Scheier, C. (2003) · Nature Neuroscience · doi:10.1038/nn1150 · Cited by 924 · see citing works
Wicherts, J. M., Veldkamp, C. L. S., Augusteijn, H. E. M., Bakker, M., van Aert, R. C. M., & van Assen, M. A. L. M. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.01832 · Cited by 754 · see citing works
Eye movement assessment of selective attentional capture by emotional pictures.
Nummenmaa, L., Hyönä, J., & Calvo, M. G. (2006) · Emotion · doi:10.1037/1528-3542.6.2.257 · Cited by 454 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Attentional bias towards negative stimuli in healthy individuals and the effects of trait anxiety
Veerapa, E., Grandgenevre, P., El Fayoumi, M., Vinnac, B., Haelewyn, O., Szaffarczyk, S., Vaiva, G., & D’Hondt, F. (2020) · Scientific Reports · doi:10.1038/s41598-020-68490-5 · Cited by 73 · see citing works
Ma, J., Yue, H., & Li, X. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1946196
- Authors
- Orquin, J. L., & Holmqvist, K.
- Affiliations
- Aarhus University (DK)
- Masaryk University (CZ)
- Corresponding author
- Orquin, Jacob L.
- Venue
- Behavior Research Methods
- Published
- 2017-12-07
- Volume
- 50
- Issue
- 4
- Pages
- 1645-1656
- ISSN
- 1554-351X (ISSN-L)
- 1554-3528
- OpenAlex
- W2771386160
- Cited by
- 280
- References
- 5
- Citations by year
- 2026: 40 · 2025: 28 · 2024: 28 · 2023: 35 · 2022: 45 · 2021: 32 · 2020: 33 · 2019: 26 · 2018: 11 · 2015: 1
- FWCI
- 22.10
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Behavior Research Methods (publishedVersion)
- PubMed (publishedVersion)
- University of Regensburg Publication Server (University of Regensburg) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Keywords
- eye tracking, research validity, internal validity, generalizability, methodological issues, data preprocessing, data analysis, research design, eye movement research
- MeSH terms
- Eye Movements, Humans, Research Design, Software, Reproducibility of Results, Behavioral Research, Eye Movement Measurements
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review