{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T03:48:56Z","timestamp":1792036136728,"version":"4.4.0"},"reference-count":49,"publisher":"JMIR Publications Inc.","issue":"9","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The assessment of behaviors related to mental health typically relies on self-report data. Networked sensors embedded in smartphones can measure some behaviors objectively and continuously, with no ongoing effort.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aims to evaluate whether changes in phone sensor\u2013derived behavioral features were associated with subsequent changes in mental health symptoms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This longitudinal cohort study examined continuously collected phone sensor data and symptom severity data, collected every 3 weeks, over 16 weeks. The participants were recruited through national research registries. Primary outcomes included depression (8-item Patient Health Questionnaire), generalized anxiety (Generalized Anxiety Disorder 7-item scale), and social anxiety (Social Phobia Inventory) severity. Participants were adults who owned Android smartphones. Participants clustered into 4 groups: multiple comorbidities, depression and generalized anxiety, depression and social anxiety, and minimal symptoms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 282 participants were aged 19-69 years (mean 38.9, SD 11.9 years), and the majority were female (223\/282, 79.1%) and White participants (226\/282, 80.1%). Among the multiple comorbidities group, depression changes were preceded by changes in GPS features (Time: r=\u22120.23, P=.02; Locations: r=\u22120.36, P&lt;.001), exercise duration (r=0.39; P=.03) and use of active apps (r=\u22120.31; P&lt;.001). Among the depression and anxiety groups, changes in depression were preceded by changes in GPS features for Locations (r=\u22120.20; P=.03) and Transitions (r=\u22120.21; P=.03). Depression changes were not related to subsequent sensor-derived features. The minimal symptoms group showed no significant relationships. There were no associations between sensor-based features and anxiety and minimal associations between sensor-based features and social anxiety.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Changes in sensor-derived behavioral features are associated with subsequent depression changes, but not vice versa, suggesting a directional relationship in which changes in sensed behaviors are associated with subsequent changes in symptoms.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/22844","type":"journal-article","created":{"date-parts":[[2021,9,6]],"date-time":"2021-09-06T11:12:40Z","timestamp":1630926760000},"page":"e22844","source":"Crossref","is-referenced-by-count":87,"title":["Evaluation of Changes in Depression, Anxiety, and Social Anxiety Using Smartphone Sensor Features: Longitudinal Cohort 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