Automatically generated smartphone data and subjective stress in healthy individuals – a pilot study

References

• The European Union. Fifth European Working Conditions survey – 2010. 2010 [cited 2019 July 12]. Available from: https://www.eurofound.europa.eu/surveys/european-working-conditions-surveys/fifth-european-working-conditions-survey-2010.
   Google Scholar
• Þórarinsdóttir H, Kessing LV, Faurholt-Jepsen M. Smartphone-based self-assessment of stress in healthy adult individuals: a systematic review. J Med Internet Res. 2017;19(2):e41.
   PubMed Web of Science ®Google Scholar
• Bennion MR, Hardy GE, Moore RK, et al. e-Therapies in England for stress, anxiety or depression: how are apps developed? A survey of NHS e-therapy developers. BMJ Health Care Inform. 2019;26(1):e100027.
   PubMedGoogle Scholar
• Swendeman D, Comulada WS, Koussa M, et al. Longitudinal validity and reliability of brief smartphone self-monitoring of diet, stress, and physical activity in a diverse sample of mothers. JMIR mHealth Uhealth. 2018;6(9):e176.
   PubMed Web of Science ®Google Scholar
• Taylor K, Silver L. Smartphone Ownership Is Growing Rapidly Around the World, but Not Always Equally | Pew Research Center. 2019 [cited 2019 Feb 19]. Available from: http://www.pewglobal.org/2019/02/05/smartphone-ownership-is-growing-rapidly-around-the-world-but-not-always-equally/.
   Google Scholar
• Ericsson Mobility Report November. 2018. 32. https://www.ericsson.com/4acd7e/assets/local/mobility-report/documents/2019/emr-november-2019.pdf
   Google Scholar
• WHO. mHealth: New horizons for health through mobile technologies. 2011 [cited 2019 Dec 16]. Available from: http://www.who.int/goe/publications/goe_mhealth_web.pdf.
   Google Scholar
• Lal S, Adair CE. E-Mental health: a rapid review of the literature. Psychiatr Serv. 2014;65(1):24–32.
   PubMed Web of Science ®Google Scholar
• Roberts LW, Chan S, Torous J. New tests, new tools: mobile and connected technologies in advancing psychiatric diagnosis. Npj Digital Med. 2018;1(1):6.
   PubMed Web of Science ®Google Scholar
• Ebner-Priemer UW, Trull TJ. Ecological momentary assessment of mood disorders and mood dysregulation. Psychol Assess. 2009;21(4):463–475.
   PubMed Web of Science ®Google Scholar
• Faurholt-Jepsen M, Vinberg M, Frost M, et al. Behavioral activities collected through smartphones and the association with illness activity in bipolar disorder. Int J Methods Psychiatr Res. 2016;25(4):309–323.
   PubMed Web of Science ®Google Scholar
• 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–e856.
   PubMed Web of Science ®Google Scholar
• Faurholt-Jepsen M, Vinberg M, Frost M, et al. Smartphone data as an electronic biomarker of illness activity in bipolar disorder. Bipolar Disord. 2015;17(7):715–728.
   PubMed Web of Science ®Google Scholar
• Faurholt-Jepsen M, Busk J, Þórarinsdóttir H, et al. Objective smartphone data as a potential diagnostic marker of bipolar disorder. Aust N Z J Psychiatry. 2019;53(2):119–128.
   PubMed Web of Science ®Google Scholar
• Vahedi Z, Saiphoo A. The association between smartphone use, stress, and anxiety: a meta-analytic review. Stress Health. 2018;34(3):347–358.
   PubMed Web of Science ®Google Scholar
• Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–396.
   PubMed Web of Science ®Google Scholar
• Rosa AR, Sánchez-Moreno J, Martínez-Aran A, et al. Validity and reliability of the Functioning Assessment Short Test (FAST) in bipolar disorder. Clin Pract Epidemiol Ment Health. 2007;3(1):5.
   PubMedGoogle Scholar
• Hamilton M. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol. 1967;6(4):278–296.
   PubMedGoogle Scholar
• Kessing LV, Munkholm K, Faurholt-Jepsen M, et al. The bipolar illness onset study: research protocol for the bio cohort study. BMJ Open. 2017;7(6):e015462.
   PubMed Web of Science ®Google Scholar
• Þórarinsdóttir H, Faurholt-Jepsen M, Ullum H, et al. The validity of daily self-assessed perceived stress measured using smartphones in healthy individuals: cohort study. JMIR Mhealth Uhealth. 2019;7(8):e13418.
   PubMed Web of Science ®Google Scholar
• Bardram JE, Frost M, Szánto K, et al. Designing mobile health technology for bipolar disorder: a field trial of the monarca system. In: In Proceedings of the SIGCHI Conference on Human Factors in Computing System New York, NY, USA, 2013: 2013. p. 2627–2636.
   Google Scholar
• 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.
   PubMed Web of Science ®Google Scholar
• Faurholt-Jepsen M, Frost M, Christensen EM, et al. The effect of smartphone-based monitoring on illness activity in bipolar disorder: the MONARCA II randomized controlled single-blinded trial. Psychol Med. 45(13):1–11.
   PubMed Web of Science ®Google Scholar
• Wing JK, Babor T, Brugha T, et al. SCAN. Schedules for Clinical Assessment in Neuropsychiatry. Arch Gen Psychiatry. 1990;47(6):589–593.
   PubMed Web of Science ®Google Scholar
• Worboys M. The hamilton rating scale for depression: the making of a “gold standard” and the unmaking of a chronic illness, 1960–1980. Chronic Illn. 2013;9(3):202–219.
   PubMedGoogle Scholar
• Hussain M, Al-Haiqi A, Zaidan AA, et al. The landscape of research on smartphone medical apps: Coherent taxonomy, motivations, open challenges and recommendations. Comput Methods Programs Biomed. 2015;122(3):393–408.
   PubMed Web of Science ®Google Scholar
• Lin YH, Lin YC, Lee YH, et al. Time Distortion Associated With Smartphone Addiction: Identifying Smartphone Addiction via a Mobile Application (App). J Psychiatr Res. 2015;65:139–45. PMID: 25935253. doi: 10.1016/j.jpsychires.2015.04.003.
   PubMed Web of Science ®Google Scholar
• Coccia C, Darling CA. Having the time of their life: college student stress, dating and satisfaction with life. Stress Health. 2016;32(1):28–35.
   PubMed Web of Science ®Google Scholar
• Harwood J, Dooley JJ, Scott AJ, Joiner R. Constantly connected – the effects of smart-devices on mental health. Computers in Human Behavior. 2014; 34:267–272.
   Web of Science ®Google Scholar
• Murdock KK. Texting while stressed: implications for students’ burnout, sleep, and well-being. Psychol Pop Media Cult. 2013;2(4):207–221.
   Google Scholar
• Muaremi A, Arnrich B, Tröster G. Towards measuring stress with smartphones and wearable devices during workday and sleep. Bio Nano Sci. 2013;3(2):172–183.
   Google Scholar
• Garcia-Ceja E, Osmani V, Mayora O. Automatic stress detection in working environments from smartphones’ accelerometer data: a first step. IEEE J Biomed Health Inform. 2016;20(4):1053–1060.
   PubMed Web of Science ®Google Scholar
• Vildjiounaite E, Kallio J, Kyllönen V, et al. Unobtrusive stress detection on the basis of smartphone usage data. Pers Ubiquit Comput. 2018;22(4):671–688.
   Web of Science ®Google Scholar
• Werkkala CM, Bäckmand HM, Kuosmanen LM, et al. Efficacy of a real-time patient feedback system: patient satisfaction study in psychiatry. Nord J Psychiatry. 2019:1–8. [Epub ahead of print]
   PubMed Web of Science ®Google Scholar
• Faurholt-Jepsen M, Torri E, Cobo J, et al. Smartphone-based self-monitoring in bipolar disorder: evaluation of usability and feasibility of two systems. Int J Bipolar Disord. 2019;7(1):1.
   PubMed Web of Science ®Google Scholar
• Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. Annu Rev Clin Psychol. 2008;4(1):1–32.
   PubMed Web of Science ®Google Scholar
• Schwartz S, Susser E. The use of well controls: an unhealthy practice in psychiatric research. Psychol Med. 2011;41(6):1127–1131.
   PubMed Web of Science ®Google Scholar
• Götz FM, Stieger S, Reips U-D. Users of the main smartphone operating systems (iOS, Android) differ only little in personality. PLoS One. 2017;12(5):e0176921.
   PubMed Web of Science ®Google Scholar