{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T06:46:34Z","timestamp":1782283594921,"version":"3.54.5"},"reference-count":46,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T00:00:00Z","timestamp":1782259200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Long questionnaires can increase cognitive and motivational demands, causing response burden. This study investigates whether eye-movement behavior varies with instrument length.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Twenty-five participants completed the BFI-44 and the longer BFQ-2 during gaze recording. Analysis included a 2 x 3 repeated-measures ANOVA (Test x Time) and the evaluation of seven machine-learning classifiers (including Random Forest and AdaBoost) trained on the final questionnaire segment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Fixation, visit, glance, and pupil metrics decreased over time across both instruments. Significant Test x Time interactions revealed that the longer BFQ-2 produced more pronounced temporal variability in gaze behavior. The AdaBoost classifier achieved 73% accuracy in distinguishing between the two instruments.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Findings suggest that longer questionnaires elicit stronger temporal fluctuations in gaze, likely reflecting fatigue or strategic adaptation. Eye-tracking provides a valuable objective tool for assessing the stability of respondent engagement over time.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpsyg.2026.1757566","type":"journal-article","created":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T05:47:21Z","timestamp":1782280041000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrating eye-tracking into psychometric research: computational approaches to explore response burden in questionnaire completion"],"prefix":"10.3389","volume":"17","author":[{"given":"Monica","family":"Casella","sequence":"first","affiliation":[{"name":"Natural and Artificial Cognition Laboratory \u201cOrazio Miglino\u201d, Department of Humanistic Studies, University of Naples \u201cFederico II\u201d","place":["Naples, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesca","family":"Borghesi","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Turin","place":["Turin, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elena","family":"Lupi","sequence":"additional","affiliation":[{"name":"Natural and Artificial Cognition Laboratory \u201cOrazio Miglino\u201d, Department of Humanistic Studies, University of Naples \u201cFederico II\u201d","place":["Naples, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pietro","family":"Cipresso","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Turin","place":["Turin, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Davide","family":"Marocco","sequence":"additional","affiliation":[{"name":"Natural and Artificial Cognition Laboratory \u201cOrazio Miglino\u201d, Department of Humanistic Studies, University of Naples \u201cFederico II\u201d","place":["Naples, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,6,24]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1340","DOI":"10.1093\/bioinformatics\/btq134","article-title":"Permutation importance: a corrected feature importance measure","volume":"26","author":"Altmann","year":"2010","journal-title":"Bioinformatics"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"783","DOI":"10.1016\/s0893-6080(99)00032-5","article-title":"Improving support vector machine classifiers by modifying kernel functions","volume":"12","author":"Amari","year":"1999","journal-title":"Neural Netw."},{"key":"ref3","author":"Berkovsky","year":"2019"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/j.brainresrev.2008.07.001","article-title":"Mental fatigue: costs and benefits","volume":"59","author":"Boksem","year":"2008","journal-title":"Brain Res. 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