Identifying objective physiological markers and modifiable behaviors for self-reported stress and mental health status using wearable sensors and mobile phones: Observational study

Journal of Medical Internet Research

Volumn 20, Issue 6, 2018, Pages

  Sano, Akane ^a   Taylor, Sara ^a   McHill, Andrew W ^b,c   Phillips, Andrew JK ^b,c   Barger, Laura K ^b,c   Klerman, Elizabeth ^b,c   Picard, Rosalind ^d  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b BRIGHAM AND WOMEN S HOSPITAL   (United States)

^c HARVARD MEDICAL SCHOOL   (United States)

^d NONE

Author keywords

Machine learning; Mental health; Mobile health; Mobile phone; Mood; Psychological stress; Smartphone; Wearable electronic devices

Indexed keywords

ADOLESCENT; ADULT; DEVICES; ELECTRONIC DEVICE; FEMALE; HUMAN; MALE; MENTAL HEALTH; MOBILE PHONE; OBSERVATIONAL STUDY; PSYCHOLOGY; SELF REPORT; STANDARDS; YOUNG ADULT;

ADOLESCENT; ADULT; CELL PHONE; FEMALE; HUMANS; MALE; MENTAL HEALTH; OBSERVATIONAL STUDIES AS TOPIC; SELF REPORT; WEARABLE ELECTRONIC DEVICES; YOUNG ADULT;

EID: 85048871457     PISSN: None     EISSN: 14388871     Source Type: Journal    
DOI: 10.2196/jmir.9410     Document Type: Article

References (74)

1. Torous J, Kiang MV, Lorme J, Onnela JP. New tools for new research in psychiatry: a scalable and customizable platform to empower data driven smartphone research. JMIR Ment Health 2016 May 5;3(2):e16 [FREE Full _text] [doi: 10.2196/mental.5165] [Medline: 27150677]
2. Jain SH, Powers BW, Hawkins JB, Brownstein JS. The digital phenotype. Nat Biotechnol 2015 May;33(5):462-463. [doi: 10.1038/nbt.3223] [Medline: 25965751]
3. Li X, Dunn J, Salins D, Zhou G, Zhou W, Schüssler-Fiorenza Rose SM, et al. Digital health: tracking physiomes and activity using wearable biosensors reveals useful health-related information. PLoS Biol 2017 Jan;15(1):e2001402 [FREE Full _text] [doi: 10.1371/journal.pbio.2001402] [Medline: 28081144]
4. Wang R, Chen F, Chen Z, Li T, Harari G, Tignor S, et al. StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones. 2014 Presented at: UbiComp '14 Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing; September 13-17, 2014; Seattle, Washington. [doi: 10.1145/2632048.2632054]
5. Bogomolov A, Lepri B, Pianesi F. Happiness recognition from mobile phone data. 2013 Presented at: International Conference on Social Computing; September 8-14, 2013; Alexandria, VA, USA. [doi: 10.1109/SocialCom.2013.118]
6. Bauer G, Lukowicz P. Can smartphones detect stress-related changes in the behaviour of individuals? 2012 Presented at: IEEE International Conference on Pervasive Computing and Communications Workshops; March 19-23, 2012; Lugano, Switzerland. [doi: 10.1109/PerComW.2012.6197525]
7. Bogomolov A, Lepri B, Ferron M, Pianesi F, Pentland A. Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits. 2014 Presented at: Proceedings of the 22nd ACM international conference on Multimedia; November 3-7, 2014; Orlando, Florida, USA. [doi: 10.1145/2647868.2654933]
8. Saeb S, Zhang M, Karr CJ, Schueller SM, Corden ME, Kording KP, et al. Mobile phone sensor correlates of depressive symptom severity in daily-life behavior: an exploratory study. J Med Internet Res 2015 Jul 15;17(7):e175 [FREE Full _text] [doi: 10.2196/jmir.4273] [Medline: 26180009]
9. Chow PI, Fua K, Huang Y, Bonelli W, Xiong H, Barnes LE, et al. Using mobile sensing to test clinical models of depression, social anxiety, state affect, and social isolation among college students. J Med Internet Res 2017 Mar 3;19(3):e62 [FREE Full _text] [doi: 10.2196/jmir.6820] [Medline: 28258049]
10. Place S, Blanch-Hartigan D, Rubin C, Gorrostieta C, Mead C, Kane J, et al. Behavioral indicators on a mobile sensing platform predict clinically validated psychiatric symptoms of mood and anxiety disorders. J Med Internet Res 2017 Mar 16;19(3):e75 [FREE Full _text] [doi: 10.2196/jmir.6678] [Medline: 28302595]
11. Muaremi A, Arnrich B, Tröster G. Towards measuring stress with smartphones and wearable devices during workday and sleep. Bionanoscience 2013;3:172-183 [FREE Full _text] [doi: 10.1007/s12668-013-0089-2] [Medline: 25530929]
12. Muaremi A, Bexheti A, Gravenhorst F, Arnrich B, Tröster G. Monitoring the Impact of Stress on the Sleep Patterns of Pilgrims using Wearable Sensors. 2014 Presented at: IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI); June 1-4, 2014; Valencia, Spain. [doi: 10.1109/BHI.2014.6864335]
13. Sano A, Picard RW. Stress Recognition Using Wearable Sensors and Mobile Phones. 2013 Presented at: Humaine Association Conference on Affective Computing and Intelligent Interaction; September 2-5, 2013; Geneva, Switzerland. [doi: 10.1109/ACII.2013.117]
14. Sano A, Phillips AJ, Yu AZ, McHill AW, Taylor S, Jaques N, et al. Recognizing academic performance, sleep quality, stress level, and mental health using personality traits, wearable sensors and mobile phones. 2015 Presented at: IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN); June 9-12, 2015; Cambridge, MA, USA. [doi: 10.1109/BSN.2015.7299420]
15. CACUSS. American College Health Association-National College Health Assessment II: Canadian Reference Group Executive Summary Spring 2017 URL: http://www.cacuss.ca/health_data.htm [accessed 2018-05-16] [WebCite Cache ID 6zT9bD7yo]
16. Auerbach RP, Alonso J, Axinn WG, Cuijpers P, Ebert DD, Green JG, et al. Mental disorders among college students in the World Health Organization world mental health surveys. Psychol Med 2016 Oct;46(14):2955-2970 [FREE Full _text] [doi: 10.1017/S0033291716001665] [Medline: 27484622]
17. Eisenberg D, Golberstein E, Hunt J. Mental health and academic success in college. B E J Econom Anal Policy 2009;9(1):-. [doi: 10.2202/1935-1682.2191]
18. The American Association of Suicidology. Suicidology. 2016. College Students & Suicide Fact Sheet: 2016 Fact Sheet URL: http://www.suicidology.org/Portals/14/Re-Formatted%20College%20Students%20Fact%20Sheet.pdf?ver=2016-11-16-110354-547 [accessed 2018-05-16] [WebCite Cache ID _6zTBIkcVH]
19. The Association for University and College Counseling Center Directors. The association for university and college counseling center directors annual survey URL: http://files.cmcglobal.com/AUCCCD_2013_Monograph_Public.pdf [accessed 2018-05-16] [WebCite Cache ID _6zT9rC5tt]
20. Horne JA, Ostberg O. A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int J Chronobiol 1976;4(2):97-110. [Medline: 1027738]
21. Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res 1989 May;28(2):193-213. [Medline: 2748771]
22. John O, Srivastava S. Moityca.com.br. 1999. The Big Five trait taxonomy: History, measurement, and theoretical perspectives URL: http://moityca.com.br/pdfs/bigfive_John.pdf [accessed 2018-05-18] [WebCite Cache ID _6zVEjcmQv]
23. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav 1983 Dec;24(4):385-396. [Medline: 6668417]
24. Ware J, Kosinski M, Keller SD. A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care 1996 Mar;34(3):220-233. [Medline: 8628042]
25. Sano A, Picard RW, Stickgold R. Quantitative analysis of wrist electrodermal activity during sleep. Int J Psychophysiol 2014 Dec;94(3):382-389 [FREE Full _text] [doi: 10.1016/j.ijpsycho.2014.09.011] [Medline: 25286449]
26. Aharony N, Pan W, Ip C, Khayal I, Pentland A. Social fMRI: investigating and shaping social mechanisms in the real world. Pervasive Mob Comput 2011 Dec;7(6):643-659. [doi: 10.1016/j.pmcj.2011.09.004]
27. Cajochen C, Frey S, Anders D, Späti J, Bues M, Pross A, et al. Evening exposure to a light-emitting diodes (LED)-backlit computer screen affects circadian physiology and cognitive performance. J Appl Physiol (1985) 2011 May;110(5):1432-1438 [FREE Full _text] [doi: 10.1152/japplphysiol.00165.2011] [Medline: 21415172]
28. Chang AM, Aeschbach D, Duffy JF, Czeisler CA. Evening use of light-emitting eReaders negatively affects sleep, circadian timing, and next-morning alertness. Proc Natl Acad Sci U S A 2015 Jan 27;112(4):1232-1237 [FREE Full _text] [doi: 10.1073/pnas.1418490112] [Medline: 25535358]
29. Immersion. A people-centric view of your email life URL: https://immersion.media.mit.edu/ [accessed 2018-05-18] [WebCite Cache ID _6zVK7Rb2d]
30. Spielberger C. Manual for the State-Trait Anxiety Inventory (Form Y). Palo Alto, CA: Consulting Psychologists Press; 1983.
31. Van den Broeck J, Cunningham SA, Eeckels R, Herbst K. Data cleaning: detecting, diagnosing, and editing data abnormalities. PLoS Med 2005 Oct;2(10):e267 [FREE Full _text] [doi: 10.1371/journal.pmed.0020267] [Medline: 16138788]
32. Clifford GD, Lopez D, Li Q, Rezek I. Signal quality indices and data fusion for determining clinical acceptability of electrocardiograms. 2011 Presented at: Computing in Cardiology; September 18-21, 2011; Hangzhou, China.
33. Wood LB, Asada HH. Noise cancellation model validation for reduced motion artifact wearable PPG sensors using MEMS accelerometers. 2006 Presented at: International Conference of the IEEE Engineering in Medicine and Biology Society; August 30-September 03, 2006; New York, NY, USA. [doi: 10.1109/IEMBS.2006.260359]
34. Engels J. Imputation of missing longitudinal data: a comparison of methods. J Clin Epidemiol 2003 Oct;56(10):968-976. [doi: 10.1016/S0895-4356(03)00170-7]
35. Schmitt P, Mandel J, Guedj M. A comparison of six methods for missing data imputation. J Biom Biostat 2015;6:224. [doi: 10.4172/2155-6180.1000224]
36. Taylor S, Jaques N, Chen W, Fedor S, Sano A, Picard R. Automatic identification of artifacts in electrodermal activity data. 2015 Presented at: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); August 25-29, 2015; Milan, Italy URL: http://europepmc.org/abstract/MED/26736662 [doi: 10.1109/EMBC.2015.7318762]
37. Doberenz S, Roth WT, Wollburg E, Maslowski NI, Kim S. Methodological considerations in ambulatory skin conductance monitoring. Int J Psychophysiol 2011;80(2):87-95. [doi: 10.1016/j.ijpsycho.2011.02.002]
38. Dawson ME, Schell AM, Filion DL. The electrodermal system. In: Handbook of Psychophysiology. New York, NY, US: Cambridge University Press; 2007:159-181.
39. Wenzel A. The SAGE Encyclopedia of Abnormal and Clinical Psychology. Thousand Oaks, California: SAGE Publications, Inc; 2017.
40. Texas Instruments. TIDA-00824 Human Skin Temperature Sensing for Wearable Applications Reference Design URL: http://www.ti.com/lit/ug/tiduay7/tiduay7.pdf [accessed 2018-05-16] [WebCite Cache ID _6zTAnV7XJ]
41. Bolge SC, Flores NM, Phan JH. The burden of poor mental well-being among patients with type 2 diabetes mellitus: examining health care resource use and work productivity loss. J Occup Environ Med 2016 Nov;58(11):1121-1126 [FREE Full _text] [Medline: 27820762]
42. Wolff JL, Roter DL. Older adults' mental health function and patient-centered care: does the presence of a family companion help or hinder communication? J Gen Intern Med 2012 Jun;27(6):661-668 [FREE Full _text] [doi: 10.1007/s11606-011-1957-5] [Medline: 22180197]
43. Boucsein W, Fowles DC, Grimnes S, Ben-Shakhar G, Roth WT, Dawson ME, Society for Psychophysiological Research Ad Hoc Committee on Electrodermal Measures. Publication recommendations for electrodermal measurements. Psychophysiology 2012 Aug;49(8):1017-1034. [doi: 10.1111/j.1469-8986.2012.01384.x] [Medline: 22680988]
44. Boucsein W. Electrodermal Activity. United States: Springer US; 2012.
45. Thomée S, Härenstam A, Hagberg M. Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults--a prospective cohort study. BMC Public Health 2011 Jan;11:66 [FREE Full _text] [doi: 10.1186/1471-2458-11-66] [Medline: 21281471]
46. Sano A, Phillips A, McHill A, Taylor S, Barger L, Czeisler C, et al. Influence of weekly sleep regularity on self-reported wellbeing. Sleep 2017;40(suppl_1):A67-A68. [doi: 10.1093/sleepj/zsx050.181]
47. Phillips AJK, Clerx WM, O'Brien CS, Sano A, Barger LK, Picard RW, et al. Irregular sleep/wake patterns are associated with poorer academic performance and delayed circadian and sleep/wake timing. Sci Rep 2017 Jun 12;7(1):3216 [FREE Full _text] [doi: 10.1038/s41598-017-03171-4] [Medline: 28607474]
48. Canzian L, Musolesi M. Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis. 2015 Presented at: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing; September 7-11, 2015; Osaka, Japan. [doi: 10.1145/2750858.2805845]
49. Jaques N, Taylor S, Azaria A, Ghandeharioun A, Sano A, Picard R. Predicting students' happiness from physiology, phone, mobility, and behavioral data. 2015 Presented at: International Conference on Affective Computing and Intelligent Interaction (ACII); September 21-24, 2015; Xi'an, China URL: http://europepmc.org/abstract/MED/28515966 [doi: 10.1109/ACII.2015.7344575]
50. Tibshirani R. Regression selection shrinkage via the Lasso. J R Stat Soc Series B Stat Methodol 2011;73(3):273-282. [doi: 10.1111/j.1467-9868.2011.00771.x]
51. Kohavi R, John GH. Wrappers for feature subset selection. Artif Intell 1997 Dec;97(1-2):273-324. [doi: 10.1016/S0004-3702(97)00043-X] [Medline: 356583]
52. Forman G, Scholz M. Apples-to-apples in cross-validation studies: pitfalls in classifier performance measurement. SIGKDD Explor 2010;12:49-57. [doi: 10.1145/1882471.1882479]
53. Agresti A, Coull BA. Approximate is better than “Exact” for interval estimation of binomial proportions. Am Stat 1998 May;52(2):119-126. [doi: 10.1080/00031305.1998.10480550]
54. Healey JA, Picard RW. Affect.media.mit.edu. 2005. Detecting Stress During Real-World Driving Tasks Using Physiological Sensors URL: https://affect.media.mit.edu/pdfs/05.healey-picard.pdf [accessed 2018-05-18] [WebCite Cache ID _6zVI8MWT1]
55. Hernandez J, Morris RR, Picard RW. Call Center Stress Recognition with Person-Specific Models. 2011 Presented at: International Conference on Affective Computing and Intelligent Interaction; October 09-12, 2011; Memphis, USA. [doi: 10.1007/978-3-642-24600-5_16]
56. Setz C, Arnrich B, Schumm J, La Marca R, Tröster G, Ehlert U. Discriminating stress from cognitive load using a wearable EDA device. IEEE Trans Inf Technol Biomed 2010 Mar;14(2):410-417. [doi: 10.1109/TITB.2009.2036164] [Medline: 19906598]
57. Ward NG, Doerr HO, Storrie MC. Skin conductance: a potentially sensitive test for depression. Psychiatry Res 1983 Dec;10(4):295-302. [Medline: 6583718]
58. Argyle N. Skin conductance levels in panic disorder and depression. J Nerv Ment Dis 1991 Sep;179(9):563-566. [Medline: 1919559]
59. Rottenberg J. Mood and emotion in major depression. Curr Dir Psychol Sci 2005;14(3):167-170. [doi: 10.1111/j.0963-7214.2005.00354.x]
60. Nutt D, Wilson S, Paterson L. Sleep disorders as core symptoms of depression. Dialogues Clin Neurosci 2008;10(3):329-336 [FREE Full _text] [Medline: 18979946]
61. Abad VC, Guilleminault C. Sleep and psychiatry. Dialogues Clin Neurosci 2005;7(4):291-303 [FREE Full _text] [Medline: 16416705]
62. Vinkers CH, Penning R, Hellhammer J, Verster JC, Klaessens JH, Olivier B, et al. The effect of stress on core and peripheral body temperature in humans. Stress 2013 Sep;16(5):520-530. [doi: 10.3109/10253890.2013.807243] [Medline: 23790072]
63. Sano A, Picard RW. Comparison of sleep-wake classification using electroencephalogram and wrist-worn multi-modal sensor data. Conf Proc IEEE Eng Med Biol Soc 2014;2014:930-933 [FREE Full _text] [doi: 10.1109/EMBC.2014.6943744]
64. Barbini B, Benedetti F, Colombo C, Guglielmo E, Campori E, Smeraldi E. Perceived mood and skin body temperature rhythm in depression. Eur Arch Psychiatry Clin Neurosci 1998;248(3):157-160. [Medline: 9728735]
65. Zschucke E, Gaudlitz K, Ströhle A. Exercise and physical activity in mental disorders: clinical and experimental evidence. J Prev Med Public Health 2013 Jan;46 Suppl 1:S12-S21 [FREE Full _text] [doi: 10.3961/jpmph.2013.46.S.S12] [Medline: 23412549]
66. Vollrath M. Personality and stress. Scand J Psychol 2001;42(4):335-347. [Medline: 11547909]
67. Ebstrup JF, Eplov LF, Pisinger C, Jørgensen T. Association between the Five Factor personality traits and perceived stress: is the effect mediated by general self-efficacy? Anxiety Stress Coping 2011 Jul;24(4):407-419. [doi: 10.1080/10615806.2010.540012] [Medline: 21213153]
68. van Straten A, Cuijpers P, van Zuuren FJ, Smits N, Donker M. Personality traits and health-related quality of life in patients with mood and anxiety disorders. Qual Life Res 2007 Feb;16(1):1-8 [FREE Full _text] [doi: 10.1007/s11136-006-9124-x] [Medline: 17033892]
69. Götz FM, Stieger S, Reips UD. Users of the main smartphone operating systems (iOS, Android) differ only little in personality. PLoS One 2017 May;12(5):e0176921 [FREE Full _text] [doi: 10.1371/journal.pone.0176921] [Medline: 28467473]
70. Mayor E. Gender roles and traits in stress and health. Front Psychol 2015 Jun;6:779 [FREE Full _text] [doi: 10.3389/fpsyg.2015.00779] [Medline: 26106354]
71. Zuckerman DM. Stress, self-esteem, and mental health: How does gender make a difference? Sex Roles 1989 Apr;20(7-8):429-444. [doi: 10.1007/BF00288001]
72. Sigmon ST, Pells JJ, Boulard NE, Whitcomb-Smith S, Edenfield TM, Hermann BA, et al. Gender differences in self-reports of depression: the response bias hypothesis revisited. Sex Roles 2005;53(5-6):401-411. [doi: 10.1007/s11199-005-6762-3]
73. Sandanger I, Nygård JF, Sørensen T, Moum T. Is women's mental health more susceptible than men's to the influence of surrounding stress? Soc Psychiatry Psychiatr Epidemiol 2004 Mar;39(3):177-184. [doi: 10.1007/s00127-004-0728-6] [Medline: 14999449]
74. Verma R, Balhara YP, Gupta CS. Gender differences in stress response: role of developmental and biological determinants. Ind Psychiatry J 2011 Jan;20(1):4-10 [FREE Full _text] [doi: 10.4103/0972-6748.98407] [Medline: 22969173]