{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T06:24:10Z","timestamp":1787293450580,"version":"build-2736575974"},"reference-count":42,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T00:00:00Z","timestamp":1787270400000},"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. Hum. Neurosci."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To examine the acceptance and influencing factors of brain-computer interface (BCI) technology among Chinese college students based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT) model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A questionnaire survey was administered to 800 students recruited from 10 universities across eastern, central, and western China using a convergent mixed-methods design. Additionally, 40 students were selected for semi-structured in-depth interviews. We analyzed the quantitative data using partial least squares structural equation modeling (PLS-SEM) and the qualitative data using thematic analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Teacher support (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      =\u202f0.337,\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt;\u202f0.001), personal innovativeness (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      =\u202f0.219,\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt;\u202f0.001), and effort expectancy (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      =\u202f0.156,\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt;\u202f0.001) were positively associated with behavioral intention, while social influence showed a smaller, marginally significant association (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      =\u202f0.121,\n                      <jats:italic>p<\/jats:italic>\n                      =\u202f0.049). Neither performance expectancy nor facilitating conditions turned out to be significant predictors, and neuroethical concerns did not reach significance either (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      =\u202f\u22120.044). The model still accounted for a substantial 62.6% of the variance in behavioral intention (R\n                      <jats:sup>2<\/jats:sup>\n                      =\u202f0.626). On the qualitative side, four broad barrier categories emerged from the data: privacy anxiety, technological unfamiliarity, insufficient institutional readiness, and the absence of ethical review.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The findings reveal that BCI technology acceptance follows a distinct psychological mechanism from traditional IT. Teacher support, rather than performance expectancy, emerges as the strongest predictor. Four main barriers were identified: privacy anxiety, technological unfamiliarity, insufficient institutional readiness, and the absence of ethical review. The study expands the UTAUT framework for neurotechnology applications in higher education and provides evidence-based recommendations for implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnhum.2026.1884532","type":"journal-article","created":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T05:35:44Z","timestamp":1787290544000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A study on Chinese college students\u2019 acceptance of brain-computer interface technology and its underlying logic\u2014an empirical analysis based on the extended UTAUT model"],"prefix":"10.3389","volume":"20","author":[{"given":"Jing","family":"Gao","sequence":"first","affiliation":[{"name":"Yantai Institute of Science and Technology","place":["Yantai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianfeng","family":"Hu","sequence":"additional","affiliation":[{"name":"Yantai Institute of Science and Technology","place":["Yantai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Chai","sequence":"additional","affiliation":[{"name":"Yantai Institute of Science and Technology","place":["Yantai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiyong","family":"Ning","sequence":"additional","affiliation":[{"name":"Yantai Institute of Science and Technology","place":["Yantai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,21]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1287\/isre.9.2.204","article-title":"A conceptual and operational definition of personal innovativeness in the domain of information technology","volume":"9","author":"Agarwal","year":"1998","journal-title":"Inf. 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