{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:04:40Z","timestamp":1782846280195,"version":"3.54.5"},"reference-count":28,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Ment Health"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Distinguishing pediatric bipolar disorder (BD) from attention-deficit\/hyperactivity disorder (ADHD) is challenging due to overlapping fluctuations in mood, energy, and activity. Combining objective actigraphy with self-reported mood and energy data may aid differential diagnosis and risk monitoring.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to test same-day associations between actigraphy-derived activity extremes and self-reported mood and energy, and to evaluate whether these measures predict same-day and next-day severe mood in adolescents with BD, ADHD, and other diagnoses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We analyzed 209 inpatients (2148 patient-days) across 4 groups (ADHD without BD: n=54; BD with ADHD: n=42; BD without ADHD: n=34; other diagnoses: n=79). Actigraphy data (Philips Actiwatch 2) were summarized into daily maximum and minimum quartiles (Max1-Max4 and Min1-Min4). Mood and Energy Thermometer (\u221210 to +10) ratings were categorized as follows: OK (&lt;3), mild (3\u20104), moderate (5\u20106), and severe (&gt;6). Group differences used Kruskal-Wallis and Mann-Whitney\n                      <jats:italic>U<\/jats:italic>\n                      tests with Bonferroni correction (\n                      <jats:italic>P<\/jats:italic>\n                      &lt;.004). Associations used chi-square tests\n                      <jats:sup\/>\n                      with Cram\u00e9r V. Leak-safe machine learning (patient-wise GroupKFold) classified SevereDay (same day) and SevereTomorrow (next day) using actigraphy, sleep, energy, and demographic data.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      BD without ADHD showed the tightest coupling of extreme activity with negative mood and energy (Cram\u00e9r V of up to 0.24;\n                      <jats:italic>P<\/jats:italic>\n                      &lt;.004). ADHD without BD showed stronger links between activity and positive energy. Machine learning achieved a receiver operating characteristic area under the curve (ROC-AUC) of 0.85, an accuracy of 0.79, and an\n                      <jats:italic>F<\/jats:italic>\n                      <jats:sub>1<\/jats:sub>\n                      -score of 0.67 for SevereDay. SevereTomorrow performance was moderate (ROC-AUC=0.80; accuracy=0.79;\n                      <jats:italic>F<\/jats:italic>\n                      <jats:sub>1<\/jats:sub>\n                      -score=0.60). Energy variability and actigraphy averages\/peaks were the top predictors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Integrating actigraphy, sleep, and daily energy ratings identifies severe mood days and provides early next-day risk signals in hospitalized adolescents. The findings support wearable-based phenotyping for precision monitoring, with external validation needed in outpatients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/78163","type":"journal-article","created":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T11:25:06Z","timestamp":1758194706000},"page":"e78163-e78163","source":"Crossref","is-referenced-by-count":0,"title":["Differentiating Pediatric Bipolar Disorder, Attention-Deficit\/Hyperactivity Disorder, and Other Psychopathologies Using Self-Reported Mood and Energy Data and Actigraphy Findings: Correlation and Machine Learning\u2013Based Prediction of Mood Severity"],"prefix":"10.2196","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5895-6572","authenticated-orcid":false,"given":"Rasim S","family":"Diler","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0803-7831","authenticated-orcid":false,"given":"Farzan","family":"Vahedifard","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9299-6519","authenticated-orcid":false,"given":"Boris","family":"Birmaher","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9329-6853","authenticated-orcid":false,"given":"Satish","family":"Iyengar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2385-4379","authenticated-orcid":false,"given":"Maria","family":"Wolfe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6541-7948","authenticated-orcid":false,"given":"Brianna N","family":"Lepore","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3118-8432","authenticated-orcid":false,"given":"Mariah","family":"Chobany","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-6560-2816","authenticated-orcid":false,"given":"Halimah","family":"Abdul-Waalee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6641-6733","authenticated-orcid":false,"given":"Greeshma","family":"Malgireddy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0825-2587","authenticated-orcid":false,"given":"Jonathan A","family":"Hart","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3857-1226","authenticated-orcid":false,"given":"Michele A","family":"Bertocci","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2025,12,4]]},"reference":[{"issue":"3","key":"R1","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1111\/camh.12021","article-title":"Bipolar disorder in children and adolescents","volume":"18","author":"Birmaher","journal-title":"Child Adolesc Ment Health"},{"issue":"2","key":"R2","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1007\/s10803-009-0804-6","article-title":"Rasim Somer Diler (ed): pediatric bipolar disorder: a global perspective","volume":"40","author":"Kleinman","journal-title":"J Autism Dev Disord"},{"issue":"2","key":"R3","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1038\/mp.2013.116","article-title":"Independence of familial transmission of mania and depression: results of the NIMH family study of affective spectrum disorders","volume":"19","author":"Merikangas","journal-title":"Mol Psychiatry"},{"key":"R4","unstructured":"Barkley RA Murphy KR Fischer M . ADHD in Adults: What the Science Says. Guilford Press; 2008. ISBN: 9781593855864"},{"issue":"7","key":"R5","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1016\/j.eurpsy.2013.04.001","article-title":"Sleep-wake cycle and melatonin rhythms in adolescents and young adults with mood disorders: comparison of unipolar and bipolar phenotypes","volume":"28","author":"Robillard","journal-title":"Eur Psychiatry"},{"issue":"2","key":"R6","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1111\/j.1468-2850.2009.01164.x","article-title":"Sleep disturbance in bipolar disorder across the lifespan","volume":"16","author":"Harvey","journal-title":"Clin Psychol (New York)"},{"key":"R7","doi-asserted-by":"publisher","DOI":"10.1016\/j.smrv.2016.05.003","article-title":"Actigraphic features of bipolar disorder: a systematic review and meta-analysis","volume":"33","author":"De Crescenzo","journal-title":"Sleep Med Rev"},{"issue":"2","key":"R8","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1001\/jamapsychiatry.2018.3546","article-title":"Real-time mobile monitoring of the dynamic associations among motor activity, energy, mood, and sleep in adults with bipolar disorder","volume":"76","author":"Merikangas","journal-title":"JAMA Psychiatry"},{"issue":"1","key":"R9","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.jad.2012.07.001","article-title":"Activity monitoring in patients with depression: a systematic review","volume":"145","author":"Burton","journal-title":"J Affect Disord"},{"issue":"1","key":"R10","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1176\/appi.ajp.2016.15091132","article-title":"Increased activity or energy as a primary criterion for the diagnosis of bipolar mania in DSM-5: findings from the STEP-BD study","volume":"174","author":"Machado-Vieira","journal-title":"Am J Psychiatry"},{"key":"R11","doi-asserted-by":"publisher","DOI":"10.47626\/2237-6089-2022-0551","article-title":"Mood or energy\/activity symptoms in bipolar mania: which are the most informative?","volume":"46","author":"Cheniaux","journal-title":"Trends Psychiatry Psychother"},{"issue":"5","key":"R12","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1016\/j.smrv.2011.10.002","article-title":"Use of actigraphy for assessment in pediatric sleep research","volume":"16","author":"Meltzer","journal-title":"Sleep Med Rev"},{"issue":"9","key":"R13","doi-asserted-by":"publisher","first-page":"1497","DOI":"10.5665\/sleep.4998","article-title":"Reproducibility of a standardized actigraphy scoring algorithm for sleep in a US Hispanic\/Latino population","volume":"38","author":"Patel","journal-title":"Sleep"},{"key":"R14","doi-asserted-by":"publisher","DOI":"10.1016\/j.comppsych.2019.152148","article-title":"The Kiddie Schedule for Affective Disorders and Schizophrenia Present and Lifetime Version (K-SADS-PL) for DSM-5: a validation for neurodevelopmental disorders in Japanese outpatients","volume":"96","author":"Nishiyama","journal-title":"Compr Psychiatry"},{"issue":"5","key":"R15","doi-asserted-by":"publisher","first-page":"488","DOI":"10.1111\/j.1399-5618.2012.01029.x","article-title":"Will disruptive mood dysregulation disorder reduce false diagnosis of bipolar disorder in children?","volume":"14","author":"Margulies","journal-title":"Bipolar Disord"},{"issue":"2","key":"R16","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1176\/appi.ajp.2012.12010132","article-title":"Prevalence, comorbidity, and correlates of DSM-5 proposed disruptive mood dysregulation disorder","volume":"170","author":"Copeland","journal-title":"Am J Psychiatry"},{"issue":"4","key":"R17","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1111\/j.1468-2850.2010.01226.x","article-title":"Bipolar and ADHD comorbidity: both artifact and outgrowth of shared mechanisms","volume":"17","author":"Youngstrom","journal-title":"Clin Psychol (New York)"},{"issue":"7","key":"R18","doi-asserted-by":"publisher","first-page":"748","DOI":"10.1176\/appi.ajp.2010.09091379","article-title":"Research domain criteria (RDoC): toward a new classification framework for research on mental disorders","volume":"167","author":"Insel","journal-title":"Am J Psychiatry"},{"issue":"1","key":"R19","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1002\/wps.20175","article-title":"Transdiagnostic factors of mental disorders","volume":"14","author":"Krueger","journal-title":"World Psychiatry"},{"issue":"10","key":"R20","doi-asserted-by":"publisher","first-page":"1139","DOI":"10.1001\/archpsyc.63.10.1139","article-title":"Phenomenology of children and adolescents with bipolar spectrum disorders","volume":"63","author":"Axelson","journal-title":"Arch Gen Psychiatry"},{"issue":"6","key":"R21","doi-asserted-by":"publisher","first-page":"264","DOI":"10.9740\/mhc.2018.11.264","article-title":"Recognition and treatment of mood dysregulation in adults with intellectual disability","volume":"8","author":"Noel","journal-title":"Ment Health Clin"},{"issue":"10","key":"R22","doi-asserted-by":"publisher","DOI":"10.1007\/s11920-014-0478-4","article-title":"Using stimulants to treat ADHD-related emotional lability","volume":"16","author":"Posner","journal-title":"Curr Psychiatry Rep"},{"issue":"7","key":"R23","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.5664\/jcsm.7230","article-title":"Use of actigraphy for the evaluation of sleep disorders and circadian rhythm sleep-wake disorders: an American Academy of Sleep Medicine clinical practice guideline","volume":"14","author":"Smith","journal-title":"J Clin Sleep Med"},{"issue":"3","key":"R24","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1017\/S0954579408000424","article-title":"Prevention of bipolar disorder in at-risk children: theoretical assumptions and empirical foundations","volume":"20","author":"Miklowitz","journal-title":"Dev Psychopathol"},{"issue":"6","key":"R25","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.1002\/ana.26617","article-title":"Circadian rest-activity rhythms, delirium risk, and progression to dementia","volume":"93","author":"Gao","journal-title":"Ann Neurol"},{"key":"R26","doi-asserted-by":"publisher","DOI":"10.2196\/72229","article-title":"Using digital phenotyping to discriminate unipolar depression and bipolar disorder: systematic review","volume":"27","author":"Zhong","journal-title":"J Med Internet Res"},{"key":"R27","doi-asserted-by":"publisher","DOI":"10.2196\/66187","article-title":"Smartphone ecological momentary assessment and wearable activity tracking in pediatric depression: cohort study","volume":"9","author":"Unzueta Saavedra","journal-title":"JMIR Form Res"},{"key":"R28","doi-asserted-by":"publisher","DOI":"10.2196\/47006","article-title":"Digital phenotyping for mood disorders: methodology-oriented pilot feasibility study","volume":"25","author":"Breitinger","journal-title":"J Med Internet Res"}],"container-title":["JMIR Mental Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/mental.jmir.org\/2025\/1\/e78163","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T18:10:40Z","timestamp":1782843040000},"score":1,"resource":{"primary":{"URL":"https:\/\/mental.jmir.org\/2025\/1\/e78163"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,4]]},"references-count":28,"URL":"https:\/\/doi.org\/10.2196\/78163","relation":{},"ISSN":["2368-7959"],"issn-type":[{"value":"2368-7959","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,4]]},"article-number":"v12i3e78163"}}