New tests, new tools: mobile and connected technologies in advancing psychiatric diagnosis

npj Digital Medicine

Volumn 1, Issue 1, 2018, Pages

  Roberts, Laura Weiss ^a   Chan, Steven ^b   Torous, John ^c  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c HARVARD MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLINICAL RESEARCH; DIAGNOSIS; DIGITAL DEVICES;

'CURRENT; CLINICAL CARE; CLINICAL DATA; CLINICAL USE; DATA COLLECTION; DIGITAL TOOLS; INTERVENTIONAL; MENTAL HEALTH; MULTIPLE DOMAINS; SMART PHONES;

DISEASES;

ASSISTIVE TECHNOLOGY; BEHAVIOR ASSESSMENT; CLINICAL ASSESSMENT TOOL; CLINICAL RESEARCH; CLINICAL STUDY; DATA COMPRESSION; HUMAN; INFORMATION PROCESSING; MEDICAL TECHNOLOGY; MENTAL DISEASE; PHYSIOLOGICAL PROCESS; PRIORITY JOURNAL; PSYCHIATRIC DIAGNOSIS; REVIEW; SELF REPORT;

EID: 85089606357     PISSN: None     EISSN: 23986352     Source Type: Journal    
DOI: 10.1038/s41746-017-0006-0     Document Type: Review

References (28)

1. Kokkonen, E. W. et al. Use of electronic medical records differs by specialty and office settings. J. Am. Med. Inform. Assoc. 20, e33–e38 (2013)
2. Steinhubl, S. R., Muse, E. D. & Topol, E. J. Can mobile health technologies transform health care? J. Am. Med. Assoc. 310, 2395–2396 (2013)
3. Kessler, R. C. et al. Prevalence, persistence, and sociodemographic correlates of DSM-IV disorders in the National Comorbidity Survey Replication Adolescent Supplement. Arch. Gen. Psychiatry 69, 372–380 (2012)
4. Demyttenaere, K. et al. Prevalence, severity, and unmet need for treatment of mental disorders in the World Health Organization World Mental Health Surveys. J. Am. Med. Assoc. 291, 2581–2590 (2004)
5. Sadavoy, J., Meier, R. & Ong, A. Y. Barriers to access to mental health services for ethnic seniors: the Toronto study. Can. J. Psychiatry 49, 192–199 (2004)
6. Torous, J., Staples, P. & Onnela, J. P. Realizing the potential of mobile mental health: new methods for new data in psychiatry. Curr. Psychiatry Rep. 17, 1–7 (2015)
7. Torous, J., Kiang, M. V., Lorme, J. & Onnela, J. P. New tools for new research in psychiatry: a scalable and customizable platform to empower data driven smartphone research. JMIR Ment. Health 3, e16 (2016)
8. Marcano-Belisario, J. S. et al. Comparison of self-administered survey questionnaire responses collected using mobile apps versus other methods. Cochrane Database Syst. Rev. 7, MR000042 (2015)
9. Torous, J. et al. Patient smartphone ownership and interest in mobile apps to monitor symptoms of mental health conditions: a survey in four geographically distinct psychiatric clinics. JMIR Ment. Health 1, e5 (2014)
10. Hsin, H., Torous, J. & Roberts, L. An adjuvant role for mobile health in psychiatry. JAMA Psychiatry 73, 103–104 (2016)
11. Insel, T. et al. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am. J. Psychiatry 167, 748–751 (2010)
12. Torous, J. & Baker, J. Why psychiatry needs data science and data science needs psychiatry: connecting with technology. JAMA Psychiatry 73, 3–4 (2016)
13. Onnela, J. P. & Rauch, S. L. Harnessing smartphone-based digital phenotyping to enhance behavioral and mental health. Neuropsychopharmacology 41, 1691–1696 (2016)
14. Schneidewind, L., Borgmann, H. & Schmidt, S. Comparison of self-administered survey questionnaire responses collected using mobile apps versus other methods. Urologe A 55, 1608–1612 (2016)
15. Faurholt-Jepsen, M., Munkholm, K., Frost, M., Bardram, J. E. & Kessing, L. V. Electronic self-monitoring of mood using IT platforms in adult patients with bipolar disorder: a systematic review of the validity and evidence. BMC Psychiatry 16, 7 (2016)
16. Torous, J. & Powell, A. Current research and trends in the use of smartphone applications for mood disorders. Internet Interv. 2, 169–173 (2015)
17. Torous, J. et al. Utilizing a personal smartphone custom app to assess the patient health questionnaire-9 (PHQ-9) depressive symptoms in patients with major depressive disorder. JMIR Ment. Health 2, e8 (2015)
18. Gibbons, R. D. et al. Development of the CAT-ANX: a computerized adaptive test for anxiety. Am. J. Psychiatry 171, 187–194 (2014)
19. Walter, O. B. et al. Development and evaluation of a computer adaptive test for ‘Anxiety’ (Anxiety-CAT). Qual. Life Res. 16, 143–155 (2007)
20. Carroll, B. J. Limitations of computerized adaptive testing for anxiety. Am. J. Psychiatry 171, 692 (2014)
21. Moore, R. C., Depp, C. A., Wetherell, J. L. & Lenze, E. J. Ecological momentary assessment versus standard assessment instruments for measuring mindfulness, depressed mood, and anxiety among older adults. J. Psychiatr. Res. 75, 116–123 (2016)
22. Faurholt-Jepsen, M. et al. Smartphone data as objective measures of bipolar disorder symptoms. Psychiatry Res. 217, 124–127 (2014)
23. Saeb, S. et al. Mobile phone sensor correlates of depressive symptom severity in daily-life behavior: an exploratory study. J. Med. Internet Res. 17, e175 (2015)
24. Cummins, N. et al. A review of depression and suicide risk assessment using speech analysis. Speech Commun. 71, 10–49 (2015)
25. Bedi, G. et al. Automated analysis of free speech predicts psychosis onset in high-risk youths. NPJ Schizophr. 1, 15030 (2015)
26. Bär, K. J. et al. Non-linear complexity measures of heart rate variability in acute schizophrenia. Clin. Neurophysiol. 118, 2009–2015 (2007)
27. Naslund, J. A., Aschbrenner, K. A., Barre, L. K. & Bartels, S. J. Feasibility of popular m-health technologies for activity tracking among individuals with serious mental illness. Telemed. J. E. Health 21, 213–216 (2015)
28. Torous, J., Staples, P. & Onnela, J. P. Realizing the potential of mobile mental health: new methods for new data in psychiatry. Curr. Psychiatry Rep. 17, 1–7 (2015)