{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T07:17:20Z","timestamp":1787728640259,"version":"build-2784847793"},"reference-count":30,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:00:00Z","timestamp":1750291200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012389","name":"National Institute of Information and Communications Technology","doi-asserted-by":"publisher","award":["178A05"],"award-info":[{"award-number":["178A05"]}],"id":[{"id":"10.13039\/501100012389","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005612","name":"Shionogi and Co Ltd","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005612","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Affective Disorders"],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1016\/j.jad.2025.119703","type":"journal-article","created":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T02:32:07Z","timestamp":1750300327000},"page":"119703","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Predicting symptom worsening in remitted depression on maintenance pharmacotherapy using digital biomarkers: A prognostic modeling study using machine learning"],"prefix":"10.1016","volume":"389","author":[{"given":"Ryo","family":"Kiguchi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ayano","family":"Hata","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Satoki","family":"Fujita","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuki","family":"Yoshida","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoshitake","family":"Kitanishi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junichiro","family":"Yoshimoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aran","family":"Tajika","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Toshi A.","family":"Furukawa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.jad.2025.119703_bb0005","doi-asserted-by":"crossref","DOI":"10.3389\/fpsyg.2022.856139","article-title":"Associations between severity of depression, lifestyle patterns, and personal factors related to health behavior: secondary data analysis from a randomized controlled trial","volume":"13","author":"Aguilar-Latorre","year":"2022","journal-title":"Front. Psychol."},{"key":"10.1016\/j.jad.2025.119703_bb0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.socscimed.2022.114703","article-title":"Engagement in leisure activities and depression in older adults in the United States: longitudinal evidence from the Health and Retirement Study","volume":"294","author":"Bone","year":"2022","journal-title":"Soc. Sci. Med."},{"key":"10.1016\/j.jad.2025.119703_bb0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.cpr.2019.101773","article-title":"Psychological theories of depressive relapse and recurrence: a systematic review and meta-analysis of prospective studies","volume":"74","author":"Brouwer","year":"2019","journal-title":"Clin. Psychol. Rev."},{"key":"10.1016\/j.jad.2025.119703_bb0020","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.cpr.2018.07.005","article-title":"Risk factors for relapse and recurrence of depression in adults and how they operate: a four-phase systematic review and meta-synthesis","volume":"64","author":"Buckman","year":"2018","journal-title":"Clin. Psychol. Rev."},{"key":"10.1016\/j.jad.2025.119703_bb0025","series-title":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"785","article-title":"XGBoost","author":"Chen","year":"2016"},{"key":"10.1016\/j.jad.2025.119703_bb0030","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1038\/s41746-021-00548-8","article-title":"Digital health tools for the passive monitoring of depression: a systematic review of methods","volume":"5","author":"De Angel","year":"2022","journal-title":"NPJ Digit. Med."},{"key":"10.1016\/j.jad.2025.119703_bb0035","series-title":"Cluster Analysis","author":"Everitte","year":"2011"},{"key":"10.1016\/j.jad.2025.119703_bb0040","series-title":"Statistical Methods for Rates and Proportions","author":"Fleiss","year":"2003"},{"key":"10.1016\/j.jad.2025.119703_bb0045","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1017\/S0033291702006700","article-title":"The performance of the K6 and K10 screening scales for psychological distress in the Australian National Survey of Mental Health and Well-Being","volume":"33","author":"Furukawa","year":"2003","journal-title":"Psychol. Med."},{"key":"10.1016\/j.jad.2025.119703_bb0050","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1002\/mpr.257","article-title":"The performance of the Japanese version of the K6 and K10 in the World Mental Health Survey Japan","volume":"17","author":"Furukawa","year":"2008","journal-title":"Int. J. Methods Psychiatr. Res."},{"key":"10.1016\/j.jad.2025.119703_bb0055","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1016\/S0140-6736(03)12599-8","article-title":"Relapse prevention with antidepressant drug treatment in depressive disorders: a systematic review","volume":"361","author":"Geddes","year":"2003","journal-title":"Lancet"},{"key":"10.1016\/j.jad.2025.119703_bb0060","doi-asserted-by":"crossref","DOI":"10.2196\/15188","article-title":"The true colours remote symptom monitoring system: a decade of evolution","volume":"22","author":"Goodday","year":"2020","journal-title":"J. Med. Internet Res."},{"key":"10.1016\/j.jad.2025.119703_bb0065","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1016\/S0091-7435(03)00042-2","article-title":"Association between physical activity and mental disorders among adults in the United States","volume":"36","author":"Goodwin","year":"2003","journal-title":"Prev. Med."},{"key":"10.1016\/j.jad.2025.119703_bb0070","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1016\/S0140-6736(21)02141-3","article-title":"Time for united action on depression: a Lancet-World Psychiatric Association Commission","volume":"399","author":"Herrman","year":"2022","journal-title":"Lancet"},{"key":"10.1016\/j.jad.2025.119703_bb0075","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.psychres.2004.03.014","article-title":"Gradations of clinical severity and sensitivity to change assessed with the Beck Depression Inventory-II in Japanese patients with depression","volume":"135","author":"Hiroe","year":"2005","journal-title":"Psychiatry Res."},{"key":"10.1016\/j.jad.2025.119703_bb0080","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1017\/S0033291703007827","article-title":"Time to recurrence after recovery from major depressive episodes and its predictors","volume":"33","author":"Kanai","year":"2003","journal-title":"Psychol. Med."},{"key":"10.1016\/j.jad.2025.119703_bb0085","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1038\/s41380-019-0585-z","article-title":"Prospective biomarkers of major depressive disorder: a systematic review and meta-analysis","volume":"25","author":"Kennis","year":"2020","journal-title":"Mol. Psychiatry"},{"key":"10.1016\/j.jad.2025.119703_bb0090","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1001\/archpsyc.60.2.184","article-title":"Screening for serious mental illness in the general population","volume":"60","author":"Kessler","year":"2003","journal-title":"Arch. Gen. Psychiatry"},{"key":"10.1016\/j.jad.2025.119703_bb0095","doi-asserted-by":"crossref","DOI":"10.1186\/s12888-019-2382-2","article-title":"Predicting recurrence of depression using lifelog data: an explanatory feasibility study with a panel VAR approach","volume":"19","author":"Kumagai","year":"2019","journal-title":"BMC Psychiatry"},{"key":"10.1016\/j.jad.2025.119703_bb0100","doi-asserted-by":"crossref","DOI":"10.1016\/j.psychres.2021.113919","article-title":"Assessing recurrence of depression using a zero-inflated negative binomial model: a secondary analysis of lifelog data","volume":"300","author":"Kumagai","year":"2021","journal-title":"Psychiatry Res."},{"key":"10.1016\/j.jad.2025.119703_bb0105","author":"Kursa"},{"key":"10.1016\/j.jad.2025.119703_bb0110","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v036.i11","article-title":"Feature selection with the Boruta package","volume":"36","author":"Kursa","year":"2010","journal-title":"J. Stat. Softw."},{"key":"10.1016\/j.jad.2025.119703_bb0115","doi-asserted-by":"crossref","first-page":"159","DOI":"10.2307\/2529310","article-title":"The measurement of observer agreement for categorical data","volume":"33","author":"Landis","year":"1977","journal-title":"Biometrics"},{"key":"10.1016\/j.jad.2025.119703_bb0120","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1186\/s12888-022-03753-1","article-title":"Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD): recruitment, retention, and data availability in a longitudinal remote measurement study","volume":"22","author":"Matcham","year":"2022","journal-title":"BMC Psychiatry"},{"key":"10.1016\/j.jad.2025.119703_bb0125","article-title":"Prognostic models for predicting relapse or recurrence of major depressive disorder in adults","volume":"5","author":"Moriarty","year":"2021","journal-title":"Cochrane Database Syst. Rev."},{"key":"10.1016\/j.jad.2025.119703_bb0130","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1038\/s41746-022-00680-z","article-title":"Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder","volume":"5","author":"Oetzmann","year":"2022","journal-title":"NPJ Digit. Med."},{"key":"10.1016\/j.jad.2025.119703_bb0135","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1038\/s41386-020-0771-3","article-title":"Opportunities and challenges in the collection and analysis of digital phenotyping data","volume":"46","author":"Onnela","year":"2021","journal-title":"Neuropsychopharmacology"},{"key":"10.1016\/j.jad.2025.119703_bb0140","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1111\/j.1440-1819.2011.02236.x","article-title":"Screening performance of K6\/K10 and other screening instruments for mood and anxiety disorders in Japan","volume":"65","author":"Sakurai","year":"2011","journal-title":"Psychiatry Clin. Neurosci."},{"key":"10.1016\/j.jad.2025.119703_bb0145","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.euroneuro.2022.05.007","article-title":"Digital tools for the assessment of pharmacological treatment for depressive disorder: state of the art","volume":"60","author":"Van Assche","year":"2022","journal-title":"Eur. Neuropsychopharmacol."},{"key":"10.1016\/j.jad.2025.119703_bb0150","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.jad.2015.03.045","article-title":"Multiple risk factors predict recurrence of major depressive disorder in women","volume":"180","author":"van Loo","year":"2015","journal-title":"J. Affect. Disord."}],"container-title":["Journal of Affective Disorders"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0165032725011450?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0165032725011450?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T04:56:17Z","timestamp":1776920177000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0165032725011450"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":30,"alternative-id":["S0165032725011450"],"URL":"https:\/\/doi.org\/10.1016\/j.jad.2025.119703","relation":{},"ISSN":["0165-0327"],"issn-type":[{"value":"0165-0327","type":"print"}],"subject":[],"published":{"date-parts":[[2025,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Predicting symptom worsening in remitted depression on maintenance pharmacotherapy using digital biomarkers: A prognostic modeling study using machine learning","name":"articletitle","label":"Article Title"},{"value":"Journal of Affective Disorders","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jad.2025.119703","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Authors. Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"119703"}}