BACKGROUND: The clinical effects of smartphone-based interventions for bipolar disorder (BD) have yet to be established. OBJECTIVES: To examine the efficacy of smartphone-based interventions in BD and how the included studies reported user-engagement indicators. METHODS: We conducted a systematic search on January 24, 2022, in PubMed, Scopus, Embase, APA PsycINFO, and Web of Science. We used random-effects meta-analysis to calculate the standardized difference (Hedges' g) in pre-post change scores between smartphone intervention and control conditions. The study was pre-registered with PROSPERO (CRD42021226668). RESULTS: The literature search identified 6034 studies. Thirteen articles fulfilled the selection criteria. We included seven RCTs and performed meta-analyses comparing the pre-post change in depressive and (hypo)manic symptom severity, functioning, quality of life, and perceived stress between smartphone interventions and control conditions. There was significant heterogeneity among studies and no meta-analysis reached statistical significance. Results were also inconclusive regarding affective relapses and psychiatric readmissions. All studies reported positive user-engagement indicators. CONCLUSION: We did not find evidence to support that smartphone interventions may reduce the severity of depressive or manic symptoms in BD. The high heterogeneity of studies supports the need for expert consensus to establish ideally how studies should be designed and the use of more sensitive outcomes, such as affective relapses and psychiatric hospitalizations, as well as the quantification of mood instability. The ISBD Big Data Task Force provides preliminary recommendations to reduce the heterogeneity and achieve more valid evidence in the field.

Centre for Psychiatric Research and Education Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden

Copenhagen Affective Disorder research Center Psychiatric Center Copenhagen Copenhagen Denmark

Department of Clinical Medicine University of Copenhagen Copenhagen Denmark

Department of Psychiatry and Behavioral Sciences UT Center of Excellence on Mood Disorders McGovern Medical School The University of Texas Health Science Center at Houston Houston TX USA

Department of Psychiatry and Behavioural Neurosciences McMaster University Hamilton ON Canada

Department of Psychiatry Dalhousie University Halifax NS Canada

Department of Psychiatry Queen's University Kingston ON Canada

Department of Psychiatry University Medical Center Groningen University of Groningen Groningen The Netherlands

Department of Psychiatry University of British Columbia Vancouver BC Canada

Department of Psychiatry University of Helsinki and Helsinki University Central Hospital Helsinki Finland

Department of Psychiatry University of Toronto Toronto ON Canada

Department of Psychiatry Western Psychiatric Institute and Clinic University of Pittsburgh School of Medicine Pittsburgh PA USA

Digital Innovation Group Bipolar and Depressive Disorders Unit Institute of Neuroscience Hospital Clinic University of Barcelona IDIBAPS CIBERSAM Barcelona Catalonia Spain

Early Psychosis Interventions and Clinical detection lab Department of Psychosis Studies Institute of Psychiatry Psychology and Neuroscience King's College London London UK

Imaging of Mood and Anxiety Related Disorders group IDIBAPS CIBERSAM Barcelona Spain

Laboratory of Molecular Psychiatry and Bipolar Disorder Program Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento Centro de Pesquisa Experimental do Hospital de Clínicas de Porto Alegre Universidade Federal do Rio Grande do Sul Porto Alegre Brazil

Mood Disorders Program Hospital Universitario San Vicente Fundación Medellín Colombia

Mood Disorders Psychopharmacology Unit University Health Network University of Toronto Toronto ON Canada

National Institute of Mental Health Klecany Czech Republic

Neuroscience Graduate Program McMaster University Hamilton Canada

Research Group in Psychiatry Department of Psychiatry Faculty of Medicine University of Antioquia Medellín Colombia

See more in PubMed

Carvalho AF, Firth J, Vieta E. Bipolar disorder. Ropper AH, ed. N Engl J Med. 2020;383(1):58‐66. doi:10.1056/NEJMra1906193 PubMed DOI

Salagre E, Dodd S, Aedo A, et al. Toward precision psychiatry in bipolar disorder: staging 2.0. Front Psych. 2018;9:641. doi:10.3389/fpsyt.2018.00641 PubMed DOI PMC

Post RM, Fleming J, Kapczinski F. Neurobiological correlates of illness progression in the recurrent affective disorders. J Psychiatr Res. 2012;46(5):561‐573. doi:10.1016/j.jpsychires.2012.02.004 PubMed DOI

Staudt Hansen P, Frahm Laursen M, Grøntved S, Puggard Vogt Straszek S, Licht RW, Nielsen RE. Increasing mortality gap for patients diagnosed with bipolar disorder‐A nationwide study with 20 years of follow‐up. Bipolar Disord. 2019;21(3):270‐275. doi:10.1111/bdi.12684 PubMed DOI

Kessing LV, Vradi E, Andersen PK. Life expectancy in bipolar disorder. Bipolar Disord. 2015;17(5):543‐548. doi:10.1111/bdi.12296 PubMed DOI

Ferrari AJ, Stockings E, Khoo JP, et al. The prevalence and burden of bipolar disorder: findings from the Global Burden of Disease Study 2013. Bipolar Disord. 2016;18(5):440‐450. doi:10.1111/bdi.12423 PubMed DOI

Ching CRK, Hibar DP, Gurholt TP, et al. What we learn about bipolar disorder from large‐scale neuroimaging: findings and future directions from the ENIGMA Bipolar Disorder Working Group. Hum Brain Mapp. 2020;43(1):56‐82. doi:10.1002/hbm.25098 PubMed DOI PMC

Kishi T, Ikuta T, Matsuda Y, et al. Mood stabilizers and/or antipsychotics for bipolar disorder in the maintenance phase: a systematic review and network meta‐analysis of randomized controlled trials. Mol Psychiatry. 2020;26(8):4146‐4157. doi:10.1038/s41380-020-00946-6 PubMed DOI PMC

Vieta E, Salagre E, Grande I, et al. Early intervention in bipolar disorder. Am J Psychiatry. 2018;175(5):411‐426. doi:10.1176/appi.ajp.2017.17090972 PubMed DOI

Kessing LV, Vradi E, Andersen PK. Starting lithium prophylaxis early v. late in bipolar disorder. Br J Psychiatry. 2014;205(3):214‐220. doi:10.1192/BJP.BP.113.142802 PubMed DOI

de Assis da Silva R, Mograbi DC, LAS S, et al. Insight across the different mood states of bipolar disorder. Psychiatry Q. 2015;86(3):395‐405. doi:10.1007/s11126-015-9340-z PubMed DOI

Pacchiarotti I, Anmella G, Colomer L, Vieta E. How to treat mania. Acta Psychiatr Scand. 2020;142(3):173‐192. doi:10.1111/acps.13209 PubMed DOI

Hidalgo‐Mazzei D, Young AH. Psychiatry foretold. Aust N Z J Psychiatry. 2019;53(4):365‐366. doi:10.1177/0004867418816821 PubMed DOI

Hidalgo‐Mazzei D, Young AH, Vieta E, Colom F. Behavioural biomarkers and mobile mental health: a new paradigm. Int J Bipolar Disord. 2018;6(1):9. doi:10.1186/s40345-018-0119-7 PubMed DOI PMC

Jain SH, Powers BW, Hawkins JB, Brownstein JS. The digital phenotype. Nat Biotechnol. 2015;33(5):462‐463. doi:10.1038/nbt.3223 PubMed DOI

Seppälä J, De Vita I, Jämsä T, et al. Mobile phone and wearable sensor‐based mHealth approaches for psychiatric disorders and symptoms: systematic review and link to the M‐REsist project. J Med Internet Res. 2019;6(2):e9819. doi:10.2196/mental.9819 PubMed DOI PMC

Melbye S, Kessing LV, Bardram JE, Faurholt‐Jepsen M. Smartphone‐based self‐monitoring, treatment, and automatically generated data in children, adolescents, and young adults with psychiatric disorders: systematic review. JMIR Ment Health. 2020;7(10):e17453. doi:10.2196/17453 PubMed DOI PMC

Saccaro LF, Amatori G, Cappelli A, Mazziotti R, Dell'Osso L, Rutigliano G. Portable technologies for digital phenotyping of bipolar disorder: a systematic review. J Affect Disord. 2021;295:323‐338. doi:10.1016/J.JAD.2021.08.052 PubMed DOI

Scott J, Murray G, Henry C, et al. Activation in bipolar disorders a systematic review. JAMA Psychiat. 2017;74(2):189‐196. doi:10.1001/jamapsychiatry.2016.3459 PubMed DOI

Faurholt‐Jepsen M, Busk J, Frost M, et al. Voice analysis as an objective state marker in bipolar disorder. Transl Psychiatry. 2016;6(7):e856. doi:10.1038/tp.2016.123 PubMed DOI PMC

Cho CH, Lee T, Kim MG, In HP, Kim L, Lee HJ. Mood prediction of patients with mood disorders by machine learning using passive digital phenotypes based on the circadian rhythm: prospective observational cohort study. J Med Internet Res. 2019;21(4):e11029. doi:10.2196/11029 PubMed DOI PMC

Stanislaus S, Vinberg M, Melbye S, et al. Smartphone‐based activity measurements in patients with newly diagnosed bipolar disorder, unaffected relatives and control individuals. Int J Bipolar Disord. 2020;8(1):32. doi:10.1186/s40345-020-00195-0 PubMed DOI PMC

Faurholt‐Jepsen M, Bauer M, Kessing LV. Smartphone‐based objective monitoring in bipolar disorder: status and considerations. Int J Bipolar Disord. 2018;6(1):6. doi:10.1186/s40345-017-0110-8 PubMed DOI PMC

Ebner‐Priemer UW, Mühlbauer E, Neubauer AB, et al. Digital phenotyping: towards replicable findings with comprehensive assessments and integrative models in bipolar disorders. Int J Bipolar Disord. 2020;8(1):35. doi:10.1186/s40345-020-00210-4 PubMed DOI PMC

Antosik‐Wójcińska AZ, Dominiak M, Chojnacka M, et al. Smartphone as a monitoring tool for bipolar disorder: a systematic review including data analysis, machine learning algorithms and predictive modelling. Int J Med Inform. 2020;138:104131. doi:10.1016/j.ijmedinf.2020.104131 PubMed DOI

Rajagopalan A, Shah P, Zhang MW, Ho RC. Digital platforms in the assessment and monitoring of patients with bipolar disorder. Brain Sci. 2017;7(11). doi:10.3390/brainsci7110150 PubMed DOI PMC

Insel TR. Digital phenotyping: technology for a new science of behavior. J Am Med Assoc. 2017;318(13):1215‐1216. doi:10.1001/jama.2017.11295 PubMed DOI

Daus H, Kislicyn N, Heuer S, Backenstrass M. Disease management apps and technical assistance systems for bipolar disorder: investigating the patients´ point of view. J Affect Disord. 2018;229:351‐357. doi:10.1016/j.jad.2017.12.059 PubMed DOI

Nicholas J, Larsen ME, Proudfoot J, Christensen H. Mobile apps for bipolar disorder: a systematic review of features and content quality. J Med Internet Res. 2015;17(8):e198. doi:10.2196/jmir.4581 PubMed DOI PMC

Lagan S, Ramakrishnan A, Lamont E, Ramakrishnan A, Frye M, Torous J. Digital health developments and drawbacks: a review and analysis of top‐returned apps for bipolar disorder. Int J Bipolar Disord. 2020;8(1):39. doi:10.1186/s40345-020-00202-4 PubMed DOI PMC

Firth J, Torous J, Nicholas J, et al. The efficacy of smartphone‐based mental health interventions for depressive symptoms: a meta‐analysis of randomized controlled trials. World Psychiatry. 2017;16(3):287‐298. doi:10.1002/wps.20472 PubMed DOI PMC

Firth J, Torous J, Nicholas J, Carney R, Rosenbaum S, Sarris J. Can smartphone mental health interventions reduce symptoms of anxiety? A meta‐analysis of randomized controlled trials. J Affect Disord. 2017;218:15‐22. doi:10.1016/J.JAD.2017.04.046 PubMed DOI

Goreis A, Felnhofer A, Kafka JX, Probst T, Kothgassner OD. Efficacy of self‐management smartphone‐based apps for post‐traumatic stress disorder symptoms: a systematic review and meta‐analysis. Front Neurosci. 2020;14:3. doi:10.3389/fnins.2020.00003 PubMed DOI PMC

Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta‐analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097. doi:10.1371/journal.pmed.1000097 PubMed DOI PMC

Schardt C, Adams MB, Owens T, Keitz S, Fontelo P. Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Med Inform Decis Mak. 2007;7. doi:10.1186/1472-6947-7-16 PubMed DOI PMC

Sterne JAC, Savović J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019;366:l4898. doi:10.1136/bmj.l4898 PubMed DOI

Ma LL, Wang YY, Yang ZH, Huang D, Weng H, Zeng XT. Methodological quality (risk of bias) assessment tools for primary and secondary medical studies: what are they and which is better? Mil Med Res. 2020;7(1):1‐11. doi:10.1186/s40779-020-00238-8 PubMed DOI PMC

National Institutes of Health . Study Quality Assessment Tools|NHLBI, NIH ‐ Quality Assessment Tool for Before‐After (Pre‐Post) Studies With No Control Group. Accessed June 9, 2021. https://www.nhlbi.nih.gov/health‐topics/study‐quality‐assessment‐tools

R Core Team . R: a language and environment for statistical computing. R Foundation for Statistical Computing; 2020. Accessed July 22, 2021. https://www.r‐project.org/

DerSimonian R, Kacker R. Random‐effects model for meta‐analysis of clinical trials: an update. Contemp Clin Trials. 2007;28(2):105‐114. doi:10.1016/j.cct.2006.04.004 PubMed DOI

Albajes‐Eizagirre A, Solanes A, Radua J. Meta‐analysis of non‐statistically significant unreported effects. Stat Methods Med Res. 2019;28(12):3741‐3754. doi:10.1177/0962280218811349 PubMed DOI

Faurholt‐Jepsen M, Lindbjerg Tønning M, Frost M, et al. Reducing the rate of psychiatric re‐admissions in bipolar disorder using smartphones‐the RADMIS trial. Acta Psychiatr Scand. 2021;143(5):453‐465. doi:10.1111/acps.13274 PubMed DOI

Faurholt‐Jepsen M, Frost M, Ritz C, et al. Daily electronic self‐monitoring in bipolar disorder using smartphones ‐ the MONARCA I trial: a randomized, placebo‐controlled, single‐blind, parallel group trial. Psychol Med. 2015;45(13):2691‐2704. doi:10.1017/S0033291715000410 PubMed DOI

Faurholt‐Jepsen M, Frost M, Christensen EM, Bardram JE, Vinberg M, Kessing LV. The effect of smartphone‐based monitoring on illness activity in bipolar disorder: the MONARCA II randomized controlled single‐blinded trial. Psychol Med. 2020;50(5):838‐884. doi:10.1017/S0033291719000710 PubMed DOI

Depp CA, Ceglowski J, Wang VC, et al. Augmenting psychoeducation with a mobile intervention for bipolar disorder: a randomized controlled trial. J Affect Disord. 2015;174:23‐30. doi:10.1016/j.jad.2014.10.053 PubMed DOI PMC

Depp CA, Perivoliotis D, Holden J, Dorr J, Granholm EL. Single‐session mobile‐augmented intervention in serious mental illness: a three‐arm randomized controlled trial. Schizophr Bull. 2019;45(4):752‐762. doi:10.1093/schbul/sby135 PubMed DOI PMC

Ben‐Zeev D, Brian RM, Jonathan G, et al. Mobile health (mHealth) versus clinic‐based group intervention for people with serious mental illness: a randomized controlled trial. Psychiatr Serv. 2018;69(9):978‐985. doi:10.1176/appi.ps.201800063 PubMed DOI

Hidalgo‐Mazzei D, Mateu A, Reinares M, et al. Psychoeducation in bipolar disorder with a SIMPLe smartphone application: feasibility, acceptability and satisfaction. J Affect Disord. 2016;200:58‐66. doi:10.1016/j.jad.2016.04.042 PubMed DOI

Hidalgo‐Mazzei D, Reinares M, Mateu A, et al. OpenSIMPLe: a real‐world implementation feasibility study of a smartphone‐based psychoeducation programme for bipolar disorder. J Affect Disord. 2018;241:436‐445. doi:10.1016/j.jad.2018.08.048 PubMed DOI

Ryan KA, Smith SN, Yocum AK, et al. The life goals self‐management mobile app for bipolar disorder: consumer feasibility, usability, and acceptability study. JMIR Form Res. 2021;5(12):e32450. doi:10.2196/32450 PubMed DOI PMC

Hidalgo‐Mazzei D, Reinares M, Mateu A, et al. Is a SIMPLe smartphone application capable of improving biological rhythms in bipolar disorder? J Affect Disord. 2017;223:10‐16. doi:10.1016/j.jad.2017.07.028 PubMed DOI

Ben‐Zeev D, Buck B, Chu PV, Razzano L, Pashka N, Hallgren KA. Transdiagnostic mobile health: smartphone intervention reduces depressive symptoms in people with mood and psychotic disorders. JMIR Ment Health. 2019;6(4):e13202. doi:10.2196/13202 PubMed DOI PMC

Faurholt‐Jepsen M, Ritz C, Frost M, et al. Mood instability in bipolar disorder type I versus type II‐continuous daily electronic self‐monitoring of illness activity using smartphones. J Affect Disord. 2015;186:342‐349. doi:10.1016/j.jad.2015.06.026 PubMed DOI

Ben‐Zeev D, Chander A, Tauscher J, et al. A smartphone intervention for people with serious mental illness: fully remote randomized controlled trial of CORE. J Med Internet Res. 2021;23(11):e29201. doi:10.2196/29201 PubMed DOI PMC

Faurholt‐Jepsen M, Frost M, Christensen EM, Bardram JE, Vinberg M, Kessing LV. The effect of smartphone‐based monitoring on illness activity in bipolar disorder: the MONARCA II randomized controlled single‐blinded trial. Psychol Med. 2020;50(5):838‐848. doi:10.1017/S0033291719000710 PubMed DOI

Cook JA, Copeland ME, Jonikas JA, et al. Results of a randomized controlled trial of mental illness self‐management using wellness recovery action planning. Schizophr Bull. 2012;38(4):881‐891. doi:10.1093/schbul/sbr012 PubMed DOI PMC

Ben‐Zeev D, Brenner CJ, Begale M, Duffecy J, Mohr DC, Mueser KT. Feasibility, acceptability, and preliminary efficacy of a smartphone intervention for schizophrenia. Schizophr Bull. 2014;40(6):1244‐1253. doi:10.1093/schbul/sbu033 PubMed DOI PMC

Ng MM, Firth J, Minen M, Torous J. User engagement in mental health apps: a review of measurement, reporting, and validity. Psychiatr Serv. 2019;70(7):538‐544. doi:10.1176/appi.ps.201800519 PubMed DOI PMC

Brooke J. SUS ‐ a quick and dirty usability scale. Usability Eval Ind. 1996;189:4‐7.

Liu J‐Y, Xu K‐K, Zhu G‐L, Zhang Q‐Q, Li X‐M. Effects of smartphone‐based interventions and monitoring on bipolar disorder: a systematic review and meta‐analysis. World J Psychiatry. 2020;10(11):272‐285. doi:10.5498/wjp.v10.i11.272 PubMed DOI PMC

Celano CM, Gomez‐Bernal F, Mastromauro CA, et al. A positive psychology intervention for patients with bipolar depression: a randomized pilot trial. J Ment Health. 2020;29(1):60‐68. doi:10.1080/09638237.2018.1521942 PubMed DOI PMC

Kilbourne AM, Prenovost KM, Liebrecht C, et al. Randomized controlled trial of a collaborative care intervention for mood disorders by a national commercial health plan. Psychiatr Serv. 2019;70(3):219‐224. doi:10.1176/appi.ps.201800336 PubMed DOI PMC

Gliddon E, Cosgrove V, Berk L, et al. A randomized controlled trial of MoodSwings 2.0: an internet‐based self‐management program for bipolar disorder. Bipolar Disord. 2019;21(1):28‐39. doi:10.1111/bdi.12669 PubMed DOI

Miklowitz DJ, Price J, Holmes EA, et al. Facilitated integrated mood management for adults with bipolar disorder. Bipolar Disord. 2012;14(2):185‐197. doi:10.1111/j.1399-5618.2012.00998.x PubMed DOI PMC

Van Til K, McInnis MG, Cochran A. A comparative study of engagement in mobile and wearable health monitoring for bipolar disorder. Bipolar Disord. 2020;22(2):182‐190. doi:10.1111/bdi.12849 PubMed DOI PMC

Patoz MC, Hidalgo‐Mazzei D, Pereira B, et al. Patients’ adherence to smartphone apps in the management of bipolar disorder: a systematic review. Int J Bipolar Disord. 2021;9(1):1‐15. doi:10.1186/S40345-021-00224-6/TABLES/3 PubMed DOI PMC

Beiwinkel T, Kindermann S, Maier A, et al. Using smartphones to monitor bipolar disorder symptoms: a pilot study. JMIR Ment Health. 2016;3(1):e2. doi:10.2196/mental.4560 PubMed DOI PMC

Ryan KA, Babu P, Easter R, et al. A smartphone app to monitor mood symptoms in bipolar disorder: development and usability study. JMIR Ment Health. 2020;7(9):e19476. doi:10.2196/19476 PubMed DOI PMC

Schärer LO, Krienke UJ, Graf SM, Meltzer K, Langosch JM. Validation of life‐charts documented with the personal life‐chart app ‐ a self‐monitoring tool for bipolar disorder. BMC Psychiatry. 2015;15(1):49. doi:10.1186/s12888-015-0414-0 PubMed DOI PMC

Tsanas A, Saunders KEA, Bilderbeck AC, et al. Daily longitudinal self‐monitoring of mood variability in bipolar disorder and borderline personality disorder. J Affect Disord. 2016;205:225‐233. doi:10.1016/j.jad.2016.06.065 PubMed DOI PMC

Chan EC, Sun Y, Aitchison KJ, Sivapalan S. Mobile app‐based self‐report questionnaires for the assessment and monitoring of bipolar disorder: systematic review. JMIR Form Res. 2021;5(1):e13770. doi:10.2196/13770 PubMed DOI PMC

Ortiz A, Maslej MM, Husain MI, Daskalakis ZJ, Mulsant BH. Apps and gaps in bipolar disorder: a systematic review on electronic monitoring for episode prediction. J Affect Disord. 2021;295:1190‐1200. doi:10.1016/J.JAD.2021.08.140 PubMed DOI

Mobile Health Index and Navigation Database, App Evaluation Resources from the Division of Digital Psychiatry at BIDMC. Accessed February 1, 2022. https://mindapps.org/

One Mind PsyberGuide|A Mental Health App Guide. Accessed February 1, 2022. https://onemindpsyberguide.org/

Tohen M, Frank E, Bowden CL, et al. The International Society for Bipolar Disorders (ISBD) Task Force report on the nomenclature of course and outcome in bipolar disorders. Bipolar Disord. 2009;11(5):453‐473. doi:10.1111/j.1399-5618.2009.00726.x PubMed DOI

Khan A, Leventhal RM, Khan SR, Brown WA. Severity of depression and response to antidepressants and placebo: an analysis of the Food and Drug Administration database. J Clin Psychopharmacol. 2002;22(1):40‐45. http://www.ncbi.nlm.nih.gov/pubmed/11799341 PubMed

Fournier JC, DeRubeis RJ, Hollon SD, et al. Antidepressant drug effects and depression severity: a patient‐level meta‐analysis. J Am Med Assoc. 2010;303(1):47‐53. doi:10.1001/jama.2009.1943 PubMed DOI PMC

Samara MT, Goldberg Y, Levine SZ, et al. Initial symptom severity of bipolar I disorder and the efficacy of olanzapine: a meta‐analysis of individual participant data from five placebo‐controlled studies. Lancet Psychiatry. 2017;4(11):859‐867. doi:10.1016/S2215-0366(17)30331-0 PubMed DOI

Faurholt‐Jepsen M, Frost M, Busk J, et al. Is smartphone‐based mood instability associated with stress, quality of life, and functioning in bipolar disorder? Bipolar Disord. 2019;21(7):611‐620. doi:10.1111/BDI.12796 PubMed DOI

Vieta E, Berk M, Schulze TG, et al. Bipolar disorders. Nat Rev Dis Primers. 2018;4:18008. doi:10.1038/nrdp.2018.8 PubMed DOI

Carvalho AF, Solmi M, Husain MI, Berk M, Vieta E. The rebirth of lithium as the archetypal mood stabilizer. Bipolar Disord. 2021;23(2):211‐212. doi:10.1111/bdi.13031 PubMed DOI

Colom F, Vieta E, Sánchez‐Moreno J, et al. Group psychoeducation for stabilised bipolar disorders: 5‐year outcome of a randomised clinical trial. Br J Psychiatry. 2009;194(3):260‐265. doi:10.1192/bjp.bp.107.040485 PubMed DOI

Colom F, Vieta E, Martínez‐Arán A, et al. A randomized trial on the efficacy of group psychoeducation in the prophylaxis of recurrences in bipolar patients whose disease is in remission. Arch Gen Psychiatry. 2003;60(4):402‐407. doi:10.1001/archpsyc.60.4.402 PubMed DOI

Miklowitz DJ. Adjunctive psychotherapy for bipolar disorder: state of the evidence. Am J Psychiatry. 2008;165(11):1408‐1419. doi:10.1176/appi.ajp.2008.08040488 PubMed DOI PMC

da Costa RT, Cheniaux E, Rosaes PAL, et al. The effectiveness of cognitive behavioral group therapy in treating bipolar disorder: a randomized controlled study. Rev Bras Psiquiatr. 2011;33(2):144‐149. doi:10.1590/s1516-44462011005000008 PubMed DOI

Lewandowski KE, Sperry SH, Cohen BM, et al. Treatment to enhance cognition in bipolar disorder (TREC‐BD): efficacy of a randomized controlled trial of cognitive remediation versus active control. J Clin Psychiatry. 2017;78(9):e1242‐e1249. doi:10.4088/JCP.17m11476 PubMed DOI

Torrent C, Bonnin CM, Martínez‐Arán A, et al. Efficacy of functional remediation in bipolar disorder: a multicenter randomized controlled study. Am J Psychiatry. 2013;170(8):852‐859. doi:10.1176/appi.ajp.2012.12070971 PubMed DOI

Bonnin CM, Torrent C, Arango C, et al. Functional remediation in bipolar disorder: 1‐year follow‐up of neurocognitive and functional outcome. Br J Psychiatry. 2016;208(1):87‐93. doi:10.1192/bjp.bp.114.162123 PubMed DOI

Miklowitz DJ, Efthimiou O, Furukawa TA, et al. Adjunctive psychotherapy for bipolar disorder: a systematic review and component network meta‐analysis. JAMA Psychiat. 2021;78(2):141‐150. doi:10.1001/JAMAPSYCHIATRY.2020.2993 PubMed DOI PMC

Miller IW, Solomon DA, Ryan CE, Keitner GI. Does adjunctive family therapy enhance recovery from bipolar I mood episodes? J Affect Disord. 2004;82(3):431‐436. doi:10.1016/j.jad.2004.01.010 PubMed DOI

Clarkin JF, Carpenter D, Hull J, Wilner P, Glick I. Effects of psychoeducational intervention for married patients with bipolar disorder and their spouses. Psychiatr Serv. 1998;49(4):531‐533. doi:10.1176/ps.49.4.531 PubMed DOI

Reinares M, Sánchez‐Moreno J, Fountoulakis KN. Psychosocial interventions in bipolar disorder: what, for whom, and when. J Affect Disord. 2014;156:46‐55. doi:10.1016/j.jad.2013.12.017 PubMed DOI

Eiring Ø, Nylenna M, Nytrøen K. Patient‐important outcomes in the long‐term treatment of bipolar disorder: a mixed‐methods approach investigating relative preferences and a proposed taxonomy. Patient. 2015;9(2):91‐102. doi:10.1007/S40271-015-0128-X PubMed DOI

Bonsall MB, Wallace‐Hadrill SMA, Geddes JR, Goodwin GM, Holmes EA. Nonlinear time‐series approaches in characterizing mood stability and mood instability in bipolar disorder. Proc R Soc B Biol Sci. 2012;279(1730):916‐924. doi:10.1098/rspb.2011.1246 PubMed DOI PMC

O'Donnell LA, Ellis AJ, Van de Loo MM, et al. Mood Instability as a Predictor of Clinical and Functional Outcomes in Adolescents with Bipolar I and Bipolar II Disorder HHS Public Access. J Affect Disord. 2018;236:199‐206. doi:10.1016/j.jad.2018.04.021 PubMed DOI PMC

Patel R, Lloyd T, Jackson R, et al. Mood instability is a common feature of mental health disorders and is associated with poor clinical outcomes. BMJ Open. 2015;5(5):e007504. doi:10.1136/BMJOPEN-2014-007504 PubMed DOI PMC

Stanislaus S, Faurholt‐Jepsen M, Vinberg M, et al. Mood instability in patients with newly diagnosed bipolar disorder, unaffected relatives, and healthy control individuals measured daily using smartphones. J Affect Disord. 2020;271:336‐344. doi:10.1016/J.JAD.2020.03.049 PubMed DOI

Strejilevich SA, Martino DJ, Murru A, et al. Mood instability and functional recovery in bipolar disorders. Acta Psychiatr Scand. 2013;128(3):194‐202. doi:10.1111/acps.12065 PubMed DOI

Bopp JM, Miklowitz DJ, Goodwin GM, Stevens W, Rendell JM, Geddes JR. The longitudinal course of bipolar disorder as revealed through weekly text messaging: a feasibility study. Bipolar Disord. 2010;12(3):327‐334. doi:10.1111/J.1399-5618.2010.00807.X PubMed DOI PMC

Broome MR, Saunders KEA, Harrison PJ, Marwaha S. Mood instability: significance, definition and measurement. Br J Psychiatry. 2015;207(4):283‐285. doi:10.1192/BJP.BP.114.158543 PubMed DOI PMC

Faurholt‐Jepsen M, Geddes JR, Goodwin GM, et al. Reporting guidelines on remotely collected electronic mood data in mood disorder (eMOOD)—recommendations. Transl Psychiatry. 2019;9(1):162. doi:10.1038/S41398-019-0484-8 PubMed DOI PMC

Joo J, Sang Y. Exploring Koreans’ smartphone usage: an integrated model of the technology acceptance model and uses and gratifications theory. Comput Hum Behav. 2013;29(6):2512‐2518. doi:10.1016/J.CHB.2013.06.002 DOI

Dutot V, Bhatiasevi V, Bellallahom N. Applying the technology acceptance model in a three‐countries study of smartwatch adoption. J High Technol Managem Res. 2019;30(1):1‐14. doi:10.1016/J.HITECH.2019.02.001 DOI

Zhou L, Bao J, Setiawan I, Saptono A, Parmanto B. The mHealth app usability questionnaire (MAUQ): development and validation study. JMIR Mhealth Uhealth. 2019;21(4):e11500. doi:10.2196/11500 PubMed DOI PMC

PITT Usability Questionnaire. Accessed February 1, 2022. https://ux.hari.pitt.edu/v2/portal/#/