{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:44:47Z","timestamp":1785545087118,"version":"3.56.0"},"reference-count":55,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Aging"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Previous research has shown that in-lab motor skill acquisition (supervised by an experimenter) is sensitive to biomarkers of Alzheimer disease (AD). However, remote unsupervised screening of AD risk through a skill-based task via the web has the potential to sample a wider and more diverse pool of individuals at scale.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n \n The purpose of this study was to examine a web-based motor skill game (\u201cSuper G\u201d) and its sensitivity to risk factors of AD (eg, age, sex,\n APOE<\/jats:italic>\n \u03b54 carrier status, and verbal learning deficits).\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n Emails were sent to 662 previous MindCrowd participants who had agreed to be contacted for future research and have their\n APOE<\/jats:italic>\n \u03b54 carrier status recorded and those who were at least 45 years of age or older. Participants who chose to participate were redirected to the Super G site where they completed the Super G task using their personal computer remotely and unsupervised. Once completed, different Super G variables were derived. Linear and logistic multivariable regression was used to examine the relationship between available AD risk factors (age, sex,\n APOE<\/jats:italic>\n \u03b54 carrier status, and verbal learning) and distinct Super G performance metrics.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Fifty-four participants (~8% response rate) from the MindCrowd web-based cohort (mean age of 62.39 years; 39 females; and 23\n APOE<\/jats:italic>\n \u03b54 carriers) completed 75 trials of Super G. Results show that Super G performance was significantly associated with each of the targeted risk factors. Specifically, slower Super G response time was associated with being an\n APOE<\/jats:italic>\n \u03b54 carrier (odds ratio 0.12, 95% CI 0.02-0.44;\n P<\/jats:italic>\n =.006), greater Super G time in target (TinT) was associated with being male (odds ratio 32.03, 95% CI 3.74-1192,61;\n P<\/jats:italic>\n =.01), and lower Super G TinT was associated with greater age (\n \u03b2<\/jats:italic>\n \u22123.97, 95% CI \u22126.64 to \u22121.30;\n P<\/jats:italic>\n =.005). Furthermore, a sex-by-TinT interaction demonstrated a differential relationship between Super G TinT and verbal learning depending on sex (\u03b2\n male:TinT<\/jats:sub>\n 6.77, 95% CI 0.34-13.19;\n P<\/jats:italic>\n =.04).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n This experiment demonstrated that this web-based game, Super G, has the potential to be a skill-based digital biomarker for screening of AD risk on a large scale with relatively limited resources.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/67298","type":"journal-article","created":{"date-parts":[[2025,4,24]],"date-time":"2025-04-24T15:16:51Z","timestamp":1745507811000},"page":"e67298-e67298","source":"Crossref","is-referenced-by-count":0,"title":["Relationship Between Within-Session Digital Motor Skill Acquisition and Alzheimer Disease Risk Factors Among the MindCrowd Cohort: Cross-Sectional Descriptive 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