{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T02:40:13Z","timestamp":1787020813277,"version":"build-2736575974"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T00:00:00Z","timestamp":1731974400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T00:00:00Z","timestamp":1731974400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Child Adolesc Psychiatry Ment Health"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Wearable-generated data yield objective information on physical activity and sleep variables, which, are in turn, related to the phenomenology of depression. There is a dearth of wearable-generated data regarding physical activity and sleep variables among youth with clinical depression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Longitudinal (up to 24 months) quarterly collections of wearable-generated variables among adolescents diagnosed with current\/past major depression. Latent class analysis was employed to classify participants on the basis of wearable-generated: Activity, Sleep Duration, and Sleep efficiency. The Patient Health Questionnaire adapted for adolescents (PHQ-9-A), and the Ruminative Response Scale (RRS) at study intake were employed to predict class membership.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Seventy-two adolescents (72.5% girls) were recruited over 31 months. Activity, Sleep Duration, and Sleep efficiency were reciprocally correlated, and wearable-generated data were reducible into a finite number (3 to 4) of classes of individuals. A PHQ-A score in the clinical range (14 and above) at study intake predicted a class of low physical activity (Acceleration) and a class of shorter Sleep Duration.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Limitations<\/jats:title>\n                    <jats:p>Limited power related to the sample size and the interim nature of this study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study of wearable-generated variables among adolescents diagnosed with clinical depression shows that a large amount of longitudinal data is amenable to reduction into a finite number of classes of individuals. Interfacing wearable-generated data with clinical measures can yield insights on the relationships between objective psychobiological measures and symptoms of adolescent depression, and may improve clinical management of depression.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13034-024-00843-8","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T07:23:14Z","timestamp":1732000994000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Latent class analysis of actigraphy within the depression early warning (DEW) longitudinal clinical youth cohort"],"prefix":"10.1186","volume":"18","author":[{"given":"Lydia","family":"Sequeira","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pantea","family":"Fadaiefard","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jovana","family":"Seat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Madison","family":"Aitken","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Strauss","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Szatmari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Battaglia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,19]]},"reference":[{"issue":"6","key":"843_CR1","doi-asserted-by":"publisher","first-page":"e20161878","DOI":"10.1542\/peds.2016-1878","volume":"138","author":"R Mojtabai","year":"2016","unstructured":"Mojtabai R, Olfson M, Han B. National trends in the prevalence and treatment of depression in adolescents and young adults. Pediatrics. 2016;138(6):e20161878. https:\/\/doi.org\/10.1542\/peds.2016-1878.","journal-title":"Pediatrics"},{"issue":"10","key":"843_CR2","doi-asserted-by":"publisher","first-page":"1017","DOI":"10.1001\/jamapediatrics.2023.3221","volume":"177","author":"MJ Spoelma","year":"2023","unstructured":"Spoelma MJ, et al. Estimated prevalence of depressive disorders in Children from 2004 to 2019: a systematic review and Meta-analysis. JAMA Pediatr. 2023;177(10):1017\u201327. https:\/\/doi.org\/10.1001\/jamapediatrics.2023.3221.","journal-title":"JAMA Pediatr"},{"issue":"10","key":"843_CR3","doi-asserted-by":"publisher","first-page":"1008","DOI":"10.1001\/jamapediatrics.2023.3130","volume":"177","author":"S Madigan","year":"2023","unstructured":"Madigan S, Korczak DJ. Is it time to reconsider the diagnostic construct validity of depressive disorders for young children? JAMA Pediatr. 2023;177(10):1008\u201310. https:\/\/doi.org\/10.1001\/jamapediatrics.2023.3130.","journal-title":"JAMA Pediatr"},{"issue":"9","key":"843_CR4","doi-asserted-by":"publisher","first-page":"863","DOI":"10.1001\/jamapsychiatry.2023.1298","volume":"80","author":"A Aftab","year":"2023","unstructured":"Aftab A, Druss BG. Addressing the mental health crisis in youth-sick individuals or sick societies? JAMA Psychiatry. 2023;80(9):863\u20134. https:\/\/doi.org\/10.1001\/jamapsychiatry.2023.1298.","journal-title":"JAMA Psychiatry"},{"issue":"3","key":"843_CR5","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1111\/j.1469-7610.2008.01958.x","volume":"50","author":"M Nobile","year":"2009","unstructured":"Nobile M, et al. The influence of family structure, the TPH2 G-703T and the 5-HTTLPR serotonergic genes upon affective problems in children aged 10\u201314 years. J Child Psychol Psychiatry. 2009;50(3):317\u201325. https:\/\/doi.org\/10.1111\/j.1469-7610.2008.01958.x.","journal-title":"J Child Psychol Psychiatry"},{"issue":"2","key":"843_CR6","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1001\/jamapsychiatry.2018.3546","volume":"76","author":"KR Merikangas","year":"2019","unstructured":"Merikangas KR, et al. Real-time mobile monitoring of the dynamic associations among motor activity, energy, mood, and sleep in adults with bipolar disorder. JAMA Psychiatry. 2019;76(2):190\u20138. https:\/\/doi.org\/10.1001\/jamapsychiatry.2018.3546.","journal-title":"JAMA Psychiatry"},{"key":"843_CR7","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1016\/j.jad.2019.11.156","volume":"265","author":"L Sequeira","year":"2020","unstructured":"Sequeira L, et al. Mobile and wearable technology for monitoring depressive symptoms in children and adolescents: a scoping review. J Affect Disord. 2020;265:314\u201324. https:\/\/doi.org\/10.1016\/j.jad.2019.11.156.","journal-title":"J Affect Disord"},{"issue":"4","key":"843_CR8","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1093\/aje\/kwac212","volume":"192","author":"K Wilhite","year":"2023","unstructured":"Wilhite K, et al. Combinations of physical activity, sedentary behavior, and sleep duration and their associations with physical, psychological, and educational outcomes in children and adolescents: a systematic review. Am J Epidemiol. 2023;192(4):665\u201379. https:\/\/doi.org\/10.1093\/aje\/kwac212.","journal-title":"Am J Epidemiol"},{"key":"843_CR9","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2019-032255","author":"P Spinazze","year":"2019","unstructured":"Spinazze P, et al. Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol. BMJ Open. 2019. https:\/\/doi.org\/10.1136\/bmjopen-2019-032255.","journal-title":"BMJ Open"},{"issue":"1","key":"843_CR10","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.jad.2012.07.001","volume":"145","author":"C Burton","year":"2013","unstructured":"Burton C, et al. Activity monitoring in patients with depression: a systematic review. J Affect Disord. 2013;145(1):21\u20138. https:\/\/doi.org\/10.1016\/j.jad.2012.07.001.","journal-title":"J Affect Disord"},{"key":"843_CR11","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17103738","author":"V Gianfredi","year":"2020","unstructured":"Gianfredi V, et al. Depression and objectively measured physical activity: a systematic review and meta-analysis. Int J Environ Res Public Health. 2020. https:\/\/doi.org\/10.3390\/ijerph17103738.","journal-title":"Int J Environ Res Public Health"},{"key":"843_CR12","doi-asserted-by":"publisher","DOI":"10.1001\/jamapsychiatry.2024.1321","author":"SJ Kang","year":"2024","unstructured":"Kang SJ, et al. Integrative modeling of accelerometry-derived sleep, physical activity, and circadian rhythm domains with current or remitted major depression. JAMA Psychiatry. 2024. https:\/\/doi.org\/10.1001\/jamapsychiatry.2024.1321.","journal-title":"JAMA Psychiatry"},{"issue":"5","key":"843_CR13","doi-asserted-by":"publisher","first-page":"1126","DOI":"10.1093\/schbul\/sbaa024","volume":"46","author":"N Meyer","year":"2020","unstructured":"Meyer N, et al. Sleep and circadian rhythm disturbance in remitted Schizophrenia and bipolar disorder: a systematic review and meta-analysis. Schizophr Bull. 2020;46(5):1126\u201343. https:\/\/doi.org\/10.1093\/schbul\/sbaa024.","journal-title":"Schizophr Bull"},{"key":"843_CR14","doi-asserted-by":"publisher","DOI":"10.7860\/JCDR\/2021\/48760.15293","author":"R Ransing","year":"2021","unstructured":"Ransing R, et al. A systematic review of studies comparing actigraphy indices in patients with depression and Schizophrenia. J Clin Diagn Res. 2021. https:\/\/doi.org\/10.7860\/JCDR\/2021\/48760.15293.","journal-title":"J Clin Diagn Res"},{"key":"843_CR15","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1016\/j.jad.2019.04.087","volume":"253","author":"Y Tazawa","year":"2019","unstructured":"Tazawa Y, et al. Actigraphy for evaluation of mood disorders: a systematic review and meta-analysis. J Affect Disord. 2019;253:257\u201369. https:\/\/doi.org\/10.1016\/j.jad.2019.04.087.","journal-title":"J Affect Disord"},{"issue":"2","key":"843_CR16","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/j.sleh.12.003","volume":"5","author":"AT Berger","year":"2019","unstructured":"Berger AT, Wahlstrom KL, Widome R. Relationships between sleep duration and adolescent depression: a conceptual replication. Sleep Health. 2019;5(2):175\u20139. https:\/\/doi.org\/10.1016\/j.sleh.12.003.","journal-title":"Sleep Health"},{"issue":"4","key":"843_CR17","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1001\/jamapsychiatry.2018.4175","volume":"76","author":"KW Choi","year":"2019","unstructured":"Choi KW, et al. Assessment of Bidirectional relationships between physical activity and depression among adults: a 2-Sample mendelian randomization study. JAMA Psychiatry. 2019;76(4):399\u2013408. https:\/\/doi.org\/10.1001\/jamapsychiatry.2018.4175.","journal-title":"JAMA Psychiatry"},{"issue":"9","key":"843_CR18","doi-asserted-by":"publisher","first-page":"813","DOI":"10.1016\/S2215-0366(21)00034-1","volume":"8","author":"JJ Crouse","year":"2021","unstructured":"Crouse JJ, et al. Circadian rhythm sleep-wake disturbances and depression in young people: implications for prevention and early intervention. Lancet Psychiatry. 2021;8(9):813\u201323. https:\/\/doi.org\/10.1016\/S2215-0366(21)00034-1.","journal-title":"Lancet Psychiatry"},{"key":"843_CR19","doi-asserted-by":"publisher","first-page":"895860","DOI":"10.3389\/fpsyt.2022.895860","volume":"13","author":"R Maatoug","year":"2022","unstructured":"Maatoug R, et al. Digital phenotype of mood disorders: a conceptual and critical review. Front Psychiatry. 2022;13:895860. https:\/\/doi.org\/10.3389\/fpsyt.2022.895860.","journal-title":"Front Psychiatry"},{"key":"843_CR20","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1146\/annurev-clinpsy-032816-044949","volume":"13","author":"DC Mohr","year":"2017","unstructured":"Mohr DC, Zhang M, Schueller SM. Personal sensing: understanding mental health using ubiquitous sensors and machine learning. Annu Rev Clin Psychol. 2017;13:23\u201347. https:\/\/doi.org\/10.1146\/annurev-clinpsy-032816-044949.","journal-title":"Annu Rev Clin Psychol"},{"issue":"3","key":"843_CR21","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1016\/S2215-0366(20)30034-1","volume":"7","author":"A Kandola","year":"2020","unstructured":"Kandola A, et al. Depressive symptoms and objectively measured physical activity and sedentary behaviour throughout adolescence: a prospective cohort study. Lancet Psychiatry. 2020;7(3):262\u201371. https:\/\/doi.org\/10.1016\/S2215-0366(20)30034-1.","journal-title":"Lancet Psychiatry"},{"issue":"3","key":"843_CR22","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1016\/s1054-139x(01)00333-0","volume":"30","author":"JG Johnson","year":"2002","unstructured":"Johnson JG, et al. The patient health questionnaire for adolescents: validation of an instrument for the assessment of mental disorders among adolescent primary care patients. J Adolesc Health. 2002;30(3):196\u2013204. https:\/\/doi.org\/10.1016\/s1054-139x(01)00333-0.","journal-title":"J Adolesc Health"},{"issue":"9","key":"843_CR23","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1046\/j.1525-1497.2001.016009606.x","volume":"16","author":"K Kroenke","year":"2001","unstructured":"Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606\u201313. https:\/\/doi.org\/10.1046\/j.1525-1497.2001.016009606.x.","journal-title":"J Gen Intern Med"},{"issue":"7","key":"843_CR24","doi-asserted-by":"publisher","first-page":"4210","DOI":"10.1007\/s12144-020-00913-y","volume":"41","author":"A Brose","year":"2022","unstructured":"Brose A, Raedt RD, Vanderhasselt M-A. Eight items of the ruminative response scale are sufficient to measure weekly within-person variation in rumination. Curr Psychol, 2022. 41(7): pp. 4210\u20138. https:\/\/doi.org\/10.1007\/s12144-020-00913-y","journal-title":"Curr Psychol"},{"key":"843_CR25","doi-asserted-by":"crossref","unstructured":"Svenaeus F, Diagnosing mental disorders and saving the normal: American Psychiatric Association, 2013. Diagnostic and statistical manual of mental disorders, 5thAmerican Psychiatric Publishing:, Washington. DC. 991 pp., ISBN: 978-0890425558. Price: $122.70. Medicine, Health Care and Philosophy, 2014. 17(2): pp. 241\u2013244.","DOI":"10.1007\/s11019-013-9529-6"},{"issue":"2","key":"843_CR26","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1038\/mp.2013.116","volume":"19","author":"KR Merikangas","year":"2014","unstructured":"Merikangas KR, et al. Independence of familial transmission of mania and depression: results of the NIMH family study of affective spectrum disorders. Mol Psychiatry. 2014;19(2):214\u20139. https:\/\/doi.org\/10.1038\/mp.2013.116.","journal-title":"Mol Psychiatry"},{"issue":"1","key":"843_CR27","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1037\/0022-3514.61.1.115","volume":"61","author":"S Nolen-Hoeksema","year":"1991","unstructured":"Nolen-Hoeksema S, Morrow J. A prospective study of depression and posttraumatic stress symptoms after a natural disaster: the 1989 Loma Prieta earthquake. J Person Soc Psychol. 1991;61(1):115\u201321.","journal-title":"J Person Soc Psychol"},{"issue":"3","key":"843_CR28","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1023\/A:1023910315561","volume":"27","author":"W Treynor","year":"2003","unstructured":"Treynor W, Gonzalez R, Nolen-Hoeksema S. Rumination reconsidered: a psychometric analysis: rumination and depression: advances in theory and research. Cogn Therapy Res. 2003;27(3):247\u201359.","journal-title":"Cogn Therapy Res"},{"issue":"2","key":"843_CR29","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1016\/j.jbi.2008.08.010","volume":"42","author":"PA Harris","year":"2009","unstructured":"Harris PA, et al. Research electronic data capture (REDCap)\u2014a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377\u201381. https:\/\/doi.org\/10.1016\/j.jbi.2008.08.010.","journal-title":"J Biomed Inform"},{"issue":"6","key":"843_CR30","doi-asserted-by":"publisher","first-page":"1085","DOI":"10.1249\/MSS.0b013e31820513be","volume":"43","author":"DW Esliger","year":"2011","unstructured":"Esliger DW, et al. Validation of the GENEA Accelerometer. Med Sci Sports Exerc. 2011;43(6):1085\u201393. https:\/\/doi.org\/10.1249\/MSS.0b013e31820513be.","journal-title":"Med Sci Sports Exerc"},{"issue":"19","key":"843_CR31","doi-asserted-by":"publisher","first-page":"2182","DOI":"10.1080\/02640414.2022.2147134","volume":"40","author":"AV Rowlands","year":"2022","unstructured":"Rowlands AV, et al. Stepping up with GGIR: validity of step cadence derived from wrist-worn research-grade accelerometers using the verisense step count algorithm. J Sports Sci. 2022;40(19):2182\u201390. https:\/\/doi.org\/10.1080\/02640414.2022.2147134.","journal-title":"J Sports Sci"},{"issue":"12","key":"843_CR32","doi-asserted-by":"publisher","first-page":"5382","DOI":"10.3390\/s23125382","volume":"23","author":"AV Rowlands","year":"2023","unstructured":"Rowlands AV, et al. Accelerometer-assessed physical activity in people with type 2 diabetes: accounting for sleep when determining associations with markers of health. Sensors. 2023;23(12):5382. https:\/\/doi.org\/10.3390\/s23125382.","journal-title":"Sensors"},{"issue":"1","key":"843_CR33","doi-asserted-by":"publisher","first-page":"12975","DOI":"10.1038\/s41598-018-31266-z","volume":"8","author":"VT van Hees","year":"2018","unstructured":"van Hees VT, et al. Estimating sleep parameters using an accelerometer without sleep diary. Sci Rep. 2018;8(1):12975\u201311. https:\/\/doi.org\/10.1038\/s41598-018-31266-z.","journal-title":"Sci Rep"},{"key":"843_CR34","volume-title":"A language and environment for statistical computing","author":"R Team","year":"2021","unstructured":"Team R, Core R. A language and environment for statistical computing. R Foundation for Statistical Computing: Vienna, Austria; 2021."},{"key":"843_CR35","volume-title":"IBM SPSS statistics for Windows","author":"IBM Corp","year":"2020","unstructured":"IBM Corp. IBM SPSS statistics for Windows. Armonk, NY: IBM Corp; 2020."},{"key":"843_CR36","unstructured":"Pinheiro J. B.D., nlme: Linear and Nonlinear Mixed Effects Models. R package version 3.1\u2013165, https:\/\/CRAN.R-project.org\/package=nlme. 2024."},{"issue":"1","key":"843_CR37","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1002\/hbm.25100","volume":"43","author":"JM Bas-Hoogendam","year":"2022","unstructured":"Bas-Hoogendam JM, et al. ENIGMA\u2010anxiety working group: Rationale for and organization of large\u2010scale neuroimaging studies of anxiety disorders. Hum Brain Mapp. 2022;43(1):83\u2013112. https:\/\/doi.org\/10.1002\/hbm.25100.","journal-title":"Hum Brain Mapp"},{"issue":"10","key":"843_CR38","doi-asserted-by":"publisher","first-page":"918","DOI":"10.1002\/da.22674","volume":"34","author":"M Battaglia","year":"2017","unstructured":"Battaglia M, et al. Early childhood trajectories of separation anxiety: bearing on mental health, academic achievement, and physical health from mid-childhood to preadolescence. Depress Anxiety. 2017;34(10):918\u201327. https:\/\/doi.org\/10.1002\/da.22674.","journal-title":"Depress Anxiety"},{"key":"843_CR39","unstructured":"Lucasius C, Ali M, Patel T, Kundur D, Szatmari P, Strauss J, Battaglia M. Machine learning for psychiatry: a procedural overview of the why, when, and how. Nat Mental Health, 2024."}],"container-title":["Child and Adolescent Psychiatry and Mental Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13034-024-00843-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13034-024-00843-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13034-024-00843-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T20:04:43Z","timestamp":1732046683000},"score":1,"resource":{"primary":{"URL":"https:\/\/capmh.biomedcentral.com\/articles\/10.1186\/s13034-024-00843-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,19]]},"references-count":39,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["843"],"URL":"https:\/\/doi.org\/10.1186\/s13034-024-00843-8","relation":{},"ISSN":["1753-2000"],"issn-type":[{"value":"1753-2000","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,19]]},"assertion":[{"value":"30 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 November 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 November 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Institutional Research Board (IRB) approval for the DEW study was granted by the CAMH Research Ethics Board. Consent for publication was granted by all authors.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"149"}}