Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-30T19:37:42.709Z Has data issue: false hasContentIssue false
  • English
  • Français

Daily electronic self-monitoring in bipolar disorder using smartphones – the MONARCA I trial: a randomized, placebo-controlled, single-blind, parallel group trial

Published online by Cambridge University Press:  29 July 2015

M. Faurholt-Jepsen ,
M. Frost ,
C. Ritz ,
E. M. Christensen ,
A. S. Jacoby ,
R. L. Mikkelsen ,
U. Knorr ,
J. E. Bardram ,
M. Vinberg  and
L. V. Kessing
M. Faurholt-Jepsen*
Affiliation:
The Copenhagen Clinic for Affective Disorder, Psychiatric Centre Copenhagen, Rigshospitalet, Copenhagen, Denmark
M. Frost
Affiliation:
The Pervasive Interaction Laboratory (PIT Lab), IT University of Copenhagen, Copenhagen, Denmark
C. Ritz
Affiliation:
Department of Basic Sciences and Environment, Faculty of Life Sciences, University of Copenhagen, Copenhagen, Denmark
E. M. Christensen
Affiliation:
The Copenhagen Clinic for Affective Disorder, Psychiatric Centre Copenhagen, Rigshospitalet, Copenhagen, Denmark
A. S. Jacoby
Affiliation:
The Copenhagen Clinic for Affective Disorder, Psychiatric Centre Copenhagen, Rigshospitalet, Copenhagen, Denmark
R. L. Mikkelsen
Affiliation:
The Copenhagen Clinic for Affective Disorder, Psychiatric Centre Copenhagen, Rigshospitalet, Copenhagen, Denmark
U. Knorr
Affiliation:
The Copenhagen Clinic for Affective Disorder, Psychiatric Centre Copenhagen, Rigshospitalet, Copenhagen, Denmark
J. E. Bardram
Affiliation:
The Pervasive Interaction Laboratory (PIT Lab), IT University of Copenhagen, Copenhagen, Denmark
M. Vinberg
Affiliation:
The Copenhagen Clinic for Affective Disorder, Psychiatric Centre Copenhagen, Rigshospitalet, Copenhagen, Denmark
L. V. Kessing
Affiliation:
The Copenhagen Clinic for Affective Disorder, Psychiatric Centre Copenhagen, Rigshospitalet, Copenhagen, Denmark
*
* Address for correspondence: Dr M. Faurholt-Jepsen, The Copenhagen Clinic for Affective Disorder, Psychiatric Centre Copenhagen, Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen, Denmark. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

The number of studies on electronic self-monitoring in affective disorder and other psychiatric disorders is increasing and indicates high patient acceptance and adherence. Nevertheless, the effect of electronic self-monitoring in patients with bipolar disorder has never been investigated in a randomized controlled trial (RCT). The objective of this trial was to investigate in a RCT whether the use of daily electronic self-monitoring using smartphones reduces depressive and manic symptoms in patients with bipolar disorder.

Method

A total of 78 patients with bipolar disorder according to ICD-10 criteria, aged 18–60 years, and with 17-item Hamilton Depression Rating Scale (HAMD-17) and Young Mania Rating Scale (YMRS) scores ≤17 were randomized to the use of a smartphone for daily self-monitoring including a clinical feedback loop (the intervention group) or to the use of a smartphone for normal communicative purposes (the control group) for 6 months. The primary outcomes were differences in depressive and manic symptoms measured using HAMD-17 and YMRS, respectively, between the intervention and control groups.

Results

Intention-to-treat analyses using linear mixed models showed no significant effects of daily self-monitoring using smartphones on depressive as well as manic symptoms. There was a tendency towards more sustained depressive symptoms in the intervention group (B = 2.02, 95% confidence interval −0.13 to 4.17, p = 0.066). Sub-group analysis among patients without mixed symptoms and patients with presence of depressive and manic symptoms showed significantly more depressive symptoms and fewer manic symptoms during the trial period in the intervention group.

Conclusions

These results highlight that electronic self-monitoring, although intuitive and appealing, needs critical consideration and further clarification before it is implemented as a clinical tool.

Keywords

Bipolar disorderelectronic self-monitoringfeedback looprandomized controlled trialsmartphonethe MONARCA I trial
Type
Original Articles
Information
Psychological Medicine , Volume 45 , Issue 13 , October 2015 , pp. 2691 - 2704
Copyright
Copyright © Cambridge University Press 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Altman, EG, Hedeker, D, Peterson, JL, Davis, JM (1997). The Altman self-rating mania scale. Biological Psychiatry 42, 948–955.CrossRefGoogle ScholarPubMed
Baldessarini, RJ, Salvatore, P, Kaur Khalsa, H-M, Gebre-Medhin, P, Imaz, H, González-Pinto, A, Perez, J, Cruz, N, Maggini, C, Tohen, M (2010). Morbidity in 303 first-episode bipolar I disorder patients. Bipolar Disorders 12, 264–270.Google Scholar
Bardram, J, Frost, M, Szanto, K, Margu, G (2012). The MONARCA self-assessment system: a persuasive personal monitoring system for bipolar patients. In Proceeding IHI ’12. Proceedings of the 2nd ACM SIGHIT, ACM, New York, NY, USA, 2012, pp. 21–30.CrossRefGoogle Scholar
Bardram, JE, Frost, M, Szánto, K, Faurholt-Jepsen, M, Vinberg, M, Kessing, LV (2013). Designing mobile health technology for bipolar disorder: a field trial of the Monarca system. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA, 2013, pp. 2627–2636.CrossRefGoogle Scholar
Bauer, MS, Crits-Christoph, P, Ball, WA, Dewees, E, McAllister, T, Alahi, P, Cacciola, J, Whybrow, PC (1991). Independent assessment of manic and depressive symptoms by self-rating. Scale characteristics and implications for the study of mania. Archives of General Psychiatry 48, 807–812.Google Scholar
Bech, P, Olsen, LR (2001). Discovering depression. Ugeskrift for laeger 163, 1980–1982.Google Scholar
Bech, P, Rasmussen, NA, Olsen, LR, Noerholm, V, Abildgaard, W (2001). The sensitivity and specificity of the major depression inventory, using the present state examination as the index of diagnostic validity. Journal of Affective Disorders 66, 159–164.Google Scholar
Bonsall, MB, Wallace-Hadrill, SMA, Geddes, JR, Goodwin, GM, Holmes, EA (2012). Nonlinear time-series approaches in characterizing mood stability and mood instability in bipolar disorder. Proceedings of the Royal Society of London, Series B: Biological Sciences 279, 916–924.Google Scholar
Bopp, JM, Miklowitz, DJ, Goodwin, GM, Stevens, W, Rendell, JM, Geddes, JR (2010). The longitudinal course of bipolar disorder as revealed through weekly text messaging: a feasibility study. Bipolar Disorders 12, 327–334.CrossRefGoogle ScholarPubMed
Boutron, I, Moher, D, Altman, DG, Schulz, KF, Ravaud, P (2008). Extending the CONSORT statement to randomized trials of nonpharmacologic treatment: explanation and elaboration. Annals of Internal Medicine 148, 295–309.Google Scholar
Cohen, S, Kamarck, T, Mermelstein, R (1983). A global measure of perceived stress. Journal of Health and Social Behavior 24, 385–396.Google Scholar
Colom, F, Vieta, E, Martinez-Aran, A, Reinares, M, Goikolea, JM, Benabarre, A, Torrent, C et al. (2003). A randomized trial on the efficacy of group psychoeducation in the prophylaxis of recurrences in bipolar patients whose disease is in remission. Archives of General Psychiatry 60, 402–407.CrossRefGoogle ScholarPubMed
De Assis da Silva, R, Mograbi, DC, Silva Silveira, LA, Santos Nunes, AL, Novis, FD, Landeira-Fernandez, J, Cheniaux, E (2015). Insight across the different mood states of bipolar disorder. Psychiatric Quarterly. Published online: 18 January 2015. doi:10.1007/s11126-015-9340-z.Google Scholar
Depp, CA, Kim, DH, de Dios, LV, Wang, V, Ceglowski, J (2012). A pilot study of mood ratings captured by mobile phone versus paper-and-pencil mood charts in bipolar disorder. Journal of Dual Diagnosis 8, 326–332.Google Scholar
Depp, CA, Mausbach, B, Granholm, E, Cardenas, V, Ben-Zeev, D, Patterson, TL, Lebowitz, BD, Jeste, DV (2010). Mobile interventions for severe mental illness: design and preliminary data from three approaches. Journal of Nervous and Mental Disease 198, 715–721.Google Scholar
Endler, NS, Parker, JD (1998). Coping Inventory for Stressful Situations (CISS), 2nd edn. Multi-health Systems. Manual.Google Scholar
Faurholt-Jepsen, M, Frost, M, Vinberg, M, Christensen, EM, Bardram, JE, Kessing, LV (2014). Smartphone data as objective measures of bipolar disorder symptoms. Psychiatry Research 217, 124-127.Google Scholar
Faurholt-Jepsen, M, Vinberg, M, Christensen, EM, Frost, M, Bardram, J, Kessing, LV (2013). Daily electronic self-monitoring of subjective and objective symptoms in bipolar disorder – the MONARCA trial protocol (MONitoring, treAtment and pRediCtion of bipolAr Disorder Episodes): a randomised controlled single-blind trial. British Medical Journal Open 3: e003353.Google ScholarPubMed
Fava, M, Iosifescu, DV, Pedrelli, P, Baer, L (2009). Reliability and validity of the Massachusetts general hospital cognitive and physical functioning questionnaire. Psychotherapy and Psychosomatics 78, 91–97.Google Scholar
Frost, M, Faurholt-Jepsen, M, Doryab, A, Kessing, LV, Bardram, JE (in press). Increasing awareness, insight and adherence in treatment of bipolar disorder through personal health technology: pilot study. Journal of Medical Internet Research.Google Scholar
Ghaemi, SN, Rosenquist, KJ (2004) Is insight in mania state-dependent?: a meta-analysis. Journal of Nervous and Mental Disease 192, 771–775.Google Scholar
Guilera, G, Pino, O, Gómez-Benito, J, Rojo, JE, Vieta, E, Tabarés-Seisdedos, R, Segarra, N et al. (2009). Clinical usefulness of the Screen for Cognitive Impairment in Psychiatry (SCIP-S) Scale in patients with type I bipolar disorder. Health and Quality of Life Outcomes 7, 28.Google Scholar
Hamilton, M (1967). Development of a rating scale for primary depressive illness. British Journal of Social and Clinical Psychology 6, 278–296.Google Scholar
Henry, C, Van den Bulke, D, Bellivier, F, Roy, I, Swendsen, J, M'Baïlara, K, Siever, LJ, Leboyer, M (2008). Affective lability and affect intensity as core dimensions of bipolar disorders during euthymic period. Psychiatry Research 159, 1–6.Google Scholar
Husky, MM, Gindre, C, Mazure, CM, Brebant, C, Nolen-Hoeksema, S, Sanacora, G, Swendsen, J (2010). Computerized ambulatory monitoring in mood disorders: feasibility, compliance, and reactivity. Psychiatry Research 178, 440–442.Google Scholar
Kessing, LV, Hansen, HV, Hvenegaard, A, Christensen, EM, Dam, H, Gluud, C, Wetterslev, J (2013). Treatment in a specialised out-patient mood disorder clinic v. standard out-patient treatment in the early course of bipolar disorder: randomised clinical trial. British Journal of Psychiatry 202, 212–219.Google Scholar
Kessing, LV, Hansen, MG, Andersen, PK (2004). Course of illness in depressive and bipolar disorders. naturalistic study, 1994–1999. British Journal of Psychiatry 185, 372–377.Google Scholar
Kessing, LV, Søndergård, L, Kvist, K, Andersen, PK (2007). Adherence to lithium in naturalistic settings: results from a nationwide pharmacoepidemiological study. Bipolar Disorders 9, 730–736.Google Scholar
Kreindler, D, Levitt, A, Woolridge, N, Lumsden, CJ (2003). Portable mood mapping: the validity and reliability of analog scale displays for mood assessment via hand-held computer. Psychiatry Research 120, 165–177.CrossRefGoogle ScholarPubMed
Látalová, K (2012). Insight in bipolar disorder. Psychiatric Quarterly 83, 293–310.CrossRefGoogle ScholarPubMed
Laursen, RP, Dalskov, S-M, Damsgaard, CT, Ritz, C (2014). Back-transformation of treatment differences-an approximate method. European Journal of Clinical Nutrition 68, 277–280.Google Scholar
Lecrubier, Y, Bech, P (2007). The Ham D(6) is more homogenous and as sensitive as the Ham D(17). European Psychiatry 22, 252–255.Google Scholar
Leverich, GS, Nolen, WA, Rush, AJ, McElroy, SL, Keck, PE, Denicoff, KD, Suppes, T, Althuler, LL, Kupka, R, Kramlinger, KG, Post, RM (2001). The Stanley Foundation bipolar treatment outcome network. I. Longitudinal methodology. Journal of Affective Disorders 67, 33–44.Google Scholar
Lieberman, DZ, Kelly, TF, Douglas, L, Goodwin, FK (2010). A randomized comparison of online and paper mood charts for people with bipolar disorder. Journal of Affective Disorders 124, 85–89.Google Scholar
MacQueen, GM, Marriott, M, Begin, H, Robb, J, Joffe, RT, Young, LT (2003). Subsyndromal symptoms assessed in longitudinal, prospective follow-up of a cohort of patients with bipolar disorder. Bipolar Disorders 5, 349–355.Google Scholar
Moher, D, Hopewell, S, Schulz, KF, Montori, V, Gøtzsche, PC, Devereaux, PJ, Elbourne, D, Egger, M, Altman, DG (2010). CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials. British Medical Journal (Clinical Research Edition) 340, c869.Google Scholar
Morriss, RK, Faizal, MA, Jones, AP, Williamson, PR, Bolton, C, McCarthy, JP (2007). Interventions for helping people recognise early signs of recurrence in bipolar disorder. Cochrane Database of Systematic Reviews. Art no. CD004854. doi:10.1002/14651858.CD004854.pub2.Google Scholar
National Institute for Clinical Excellence (2004). Depression: Management of Depression in Primary and Secondary Care. National Institute for Clinical Excellence: London, England.Google Scholar
Olsen, LR, Jensen, DV, Noerholm, V, Martiny, K, Bech, P (2003). The internal and external validity of the major depression inventory in measuring severity of depressive states. Psychological Medicine 33, 351–356.Google Scholar
Paykel, ES, Abbott, R, Morriss, R, Hayhurst, H, Scott, J (2006). Sub-syndromal and syndromal symptoms in the longitudinal course of bipolar disorder. British Journal of Psychiatry 189, 118–123.Google Scholar
Perry, A, Tarrier, N, Morriss, R, McCarthy, E, Limb, K (1999). Randomised controlled trial of efficacy of teaching patients with bipolar disorder to identify early symptoms of relapse and obtain treatment. British Medical Journal (Clinical Research Edition) 318, 149–153.Google Scholar
Rojo, E, Pino, O, Guilera, G, Gómez-Benito, J, Purdon, SE, Crespo-Facorro, B, Cuesta, MJ et al. (2010). Neurocognitive diagnosis and cut-off scores of the Screen for Cognitive Impairment in Psychiatry (SCIP-S). Schizophrenia Research 116, 243–251.Google Scholar
Rosa, AR, Sánchez-Moreno, J, Martínez-Aran, A, Salamero, M, Torrent, C, Reinares, M, Comes, M et al. (2007). Validity and reliability of the Functioning Assessment Short Test (FAST) in bipolar disorder. Clinical Practice and Epidemiology in Mental Health: CP & EMH 3, 5.Google Scholar
Sachs, G (2014). Step-BD blank mood chart (http://www.manicdepressive.org/images/samplechart.gif).Google Scholar
Schärer, LO, Hartweg, V, Hoern, M, Graesslin, Y, Strobl, N, Frey, S, Biedermann, C, Walser, S, Walden, J (2002). Electronic diary for bipolar patients. Neuropsychobiology 46 (Suppl. 1), 10–12.Google Scholar
Scott, J, Colom, F (2008). Gaps and limitations of psychological interventions for bipolar disorders. Psychotherapy and Psychosomatics 77, 4–11.Google Scholar
Simon, GE, Ludman, EJ, Bauer, MS, Unützer, J, Operskalski, B (2006). Long-term effectiveness and cost of a systematic care program for bipolar disorder. Archives of General Psychiatry 63, 500–508.Google Scholar
Stone, AA, Shiffman, S, Schwartz, JE, Broderick, JE, Hufford, MR (2003). Patient compliance with paper and electronic diaries. Controlled Clinical Trials 24, 182–199.Google Scholar
Strejilevich, SA, Martino, DJ, Murru, A, Teitelbaum, J, Fassi, G, Marengo, E, Igoa, A, Colom, F (2013). Mood instability and functional recovery in bipolar disorders. Acta Psychiatrica Scandinavica 128, 194–202.Google Scholar
Totterdell, P, Briner, RB, Parkinson, B, Reynolds, S (1996). Fingerprinting time series: dynamic patterns in self-report and performance measures uncovered by a graphical non-linear method. British Journal of Psychology 87, 43–60.Google Scholar
WHO (1998). Development of the World Health Organization WHOQOL-BREF Quality of Life Assessment. The WHOQOL Group. Psychological Medicine 28, 551–558.Google Scholar
Whybrow, PC, Grof, P, Gyulai, L, Rasgon, N, Glenn, T, Bauer, M (2003). The electronic assessment of the longitudinal course of bipolar disorder: The ChronoRecord Software. Pharmacopsychiatry 36 (Suppl. 3), S244–S249.Google Scholar
Wing, JK, Babor, T, Brugha, T, Burke, J, Cooper, JE, Giel, R, Jablenski, A, Regier, D, Sartorius, N (1990). SCAN. Schedules for Clinical Assessment in Neuropsychiatry. Archives of General Psychiatry 47, 589–593.Google Scholar
Yen, C-F, Chen, C-S, Ko, C-H, Yen, J-Y, Huang, C-F (2007). Changes in insight among patients with bipolar I disorder: a 2-year prospective study. Bipolar Disorders 9, 238–242.Google Scholar
Young, RC, Biggs, JT, Ziegler, VE, Meyer, DA (1978). A rating scale for mania: reliability, validity and sensitivity. British Journal of Psychiatry 133, 429–435.Google Scholar