{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T03:19:51Z","timestamp":1790306391133,"version":"4.1.0"},"reference-count":39,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2015,9,23]],"date-time":"2015-09-23T00:00:00Z","timestamp":1442966400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100004963","name":"Seventh Framework Programme","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004963","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bipolar Disorders"],"published-print":{"date-parts":[[2015,11]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Objective methods are lacking for continuous monitoring of illness activity in bipolar disorder. Smartphones offer unique opportunities for continuous monitoring and automatic collection of real\u2010time data. The objectives of the paper were to test the hypotheses that (i) daily electronic self\u2010monitored data and (ii) automatically generated objective data collected using smartphones correlate with clinical ratings of depressive and manic symptoms in patients with bipolar disorder.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Software for smartphones (the\n                      <jats:styled-content style=\"fixed-case\">MONARCA<\/jats:styled-content>\n                      I system) that collects automatically generated objective data and self\u2010monitored data on illness activity in patients with bipolar disorder was developed by the authors. A total of 61 patients aged 18\u201360 years and with a diagnosis of bipolar disorder according to\n                      <jats:styled-content style=\"fixed-case\">ICD<\/jats:styled-content>\n                      \u201010 used the\n                      <jats:styled-content style=\"fixed-case\">MONARCA<\/jats:styled-content>\n                      I system for six months. Depressive and manic symptoms were assessed monthly using the Hamilton Depression Rating Scale 17\u2010item (\n                      <jats:styled-content style=\"fixed-case\">HDRS<\/jats:styled-content>\n                      \u201017) and the Young Mania Rating Scale (\n                      <jats:styled-content style=\"fixed-case\">YMRS<\/jats:styled-content>\n                      ), respectively. Data are representative of over 400 clinical ratings. Analyses were computed using linear mixed\u2010effect regression models allowing for both between individual variation and within individual variation over time.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Analyses showed significant positive correlations between the duration of incoming and outgoing calls\/day and scores on the\n                      <jats:styled-content style=\"fixed-case\">HDRS<\/jats:styled-content>\n                      \u201017, and significant positive correlations between the number and duration of incoming calls\/day and scores on the YMRS; the number of and duration of outgoing calls\/day and scores on the\n                      <jats:styled-content style=\"fixed-case\">YMRS<\/jats:styled-content>\n                      ; and the number of outgoing text messages\/day and scores on the YMRS. Analyses showed significant negative correlations between self\u2010monitored data (i.e., mood and activity) and scores on the\n                      <jats:styled-content style=\"fixed-case\">HDRS<\/jats:styled-content>\n                      \u201017, and significant positive correlations between self\u2010monitored data (i.e., mood and activity) and scores on the\n                      <jats:styled-content style=\"fixed-case\">YMRS<\/jats:styled-content>\n                      . Finally, the automatically generated objective data were able to discriminate between affective states.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Automatically generated objective data and self\u2010monitored data collected using smartphones correlate with clinically rated depressive and manic symptoms and differ between affective states in patients with bipolar disorder. Smartphone apps represent an easy and objective way to monitor illness activity with real\u2010time data in bipolar disorder and may serve as an electronic biomarker of illness activity.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/bdi.12332","type":"journal-article","created":{"date-parts":[[2015,9,23]],"date-time":"2015-09-23T01:56:11Z","timestamp":1442973371000},"page":"715-728","source":"Crossref","is-referenced-by-count":161,"title":["Smartphone data as an electronic biomarker of illness activity in bipolar disorder"],"prefix":"10.1111","volume":"17","author":[{"given":"Maria","family":"Faurholt\u2010Jepsen","sequence":"first","affiliation":[{"name":"The Copenhagen Clinic for Affective Disorder Rigshospitalet Psychiatric Center Copenhagen Copenhagen Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maj","family":"Vinberg","sequence":"additional","affiliation":[{"name":"The Copenhagen Clinic for Affective Disorder Rigshospitalet Psychiatric 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