| Literature DB >> 25098314 |
John Torous1, Rohn Friedman, Matcheri Keshavan.
Abstract
BACKGROUND: Patient retrospective recollection is a mainstay of assessing symptoms in mental health and psychiatry. However, evidence suggests that these retrospective recollections may not be as accurate as data collection though the experience sampling method (ESM), which captures patient data in "real time" and "real life." However, the difficulties in practical implementation of ESM data collection have limited its impact in psychiatry and mental health. Smartphones with the capability to run mobile applications may offer a novel method of collecting ESM data that may represent a practical and feasible tool for mental health and psychiatry.Entities:
Keywords: applications; depression; mobile; psychiatry; smartphone; technology
Year: 2014 PMID: 25098314 PMCID: PMC4114412 DOI: 10.2196/mhealth.2994
Source DB: PubMed Journal: JMIR Mhealth Uhealth ISSN: 2291-5222 Impact factor: 4.773
Percent access to the Internet stratified by age (N=99).a
| Age (yr) | n (%) access to Internet |
| <30 (n=18) | 18 (100) |
| 30-45 (n=31) | 31 (100) |
| 45-60 (n=26) | 22 (85) |
| >60 (n=24) | 18 (75) |
| Total (N=99) | 89 (90) |
a χ 2 3=12.172, P<.007
Mobile phone and smartphone ownership (N=99).
| Age (yr) | Percent mobile phone ownershipa
| Self-reported percent smartphone ownershipb | Percent smartphone ownership by criteriac |
| n (%) | n (%) | n (%) | |
| <30 (n=18) | 18 (100) | 15 (83) | 15 (83) |
| 30-45 (n=31) | 31 (100) | 28 (90) | 26 (84) |
| 45-60 (n=26) | 26 (100) | 19 (73) | 16 (62) |
| >60 (n=24) | 21 (87.5) | 9 (35) | 9 (38) |
| Total (N=99) | 96 (97) | 71 (72) | 66 (67) |
a χ 2 3=9.668, P<.02
b χ 2 3=21.842, P<.001
c χ 2 3=15.874, P<.001
Smartphone applications (N=86).
| Age (yr) | Number of total applications currently on smartphone | Number of healthcare applications currently on smartphonea | Number of applications downloaded each month to smartphone |
| mean (median) | mean (median) | mean (median) | |
| <30 | 30 (28) | 1.6 (1) | 3.4 (3) |
| 30-45 | 20 (15) | 0.8 (0) | 2 (1) |
| 45-60 | 8 (2.4) | 0 (0) | 0.6 (0) |
| >60 | 9.7 (6) | 0.6 (0) | 0.6 (0) |
| Overall | 17 (12) | 0.6 (0) | 1.6 (1) |
a χ 2 3=35.759, P<.02
Use of smartphone to access health care information (N=96).
| Age (yr) | Percent accessed general health care information from phone in previous 6 monthsa | Percent accessed personal health care information from phone in previous 6 monthsb |
| n (%) | n (%) | |
| <30 (n=18) | 12 (67) | 7 (39) |
| 30-45 (n=31) | 18 (58) | 9 (29) |
| 45-60 (n=23) | 3 (13) | 3 (13) |
| >60 (n=24) | 3 (13) | 7 (29) |
| Total (N=96) | 36 (38) | 26 (27) |
a χ 2 3=24.396, P<.01
b χ 2 3=3.989, P<.26
Interest in using text messages and smartphone applications for mental health (N=98).
| Age (yr) | Percent wanting to receive text messages from MDa | Percent wanting to access general health care information on phoneb | Percent wanting to use a mobile application to track mental health conditionc | Percent wanting to download an application to track conditiond | Percent wanting to use application to track condition on a daily basise |
| n (%) | n (%) | n (%) | n (%) | n (%) | |
| <30 (n=18) | 10 (56) | 15 (83) | 14 (78) | 13 (72) | 13 (72) |
| 30-45 (n=31) | 21 (68) | 27 (87) | 25 (81) | 26 (84) | 26 (84) |
| 45-60 (n=25) | 14 (54) | 16 (63) | 18 (71) | 19 (75) | 16 (63) |
| >60 (n=24) | 15 (63) | 14 (58) | 11 (46) | 11 (46) | 14 (56) |
| Total (N=98) | 60 (61) | 72 (73) | 68 (69) | 69 (70) | 69 (70) |
a χ 2 3=1.307, P<.727
b χ 2 3=8.098, P<.04
c χ 2 3=8.684, P≤.034
d χ 2 3=9.862, P<.02
e χ 2 3=5.151, P=.16
Figure 1Patients' willingness by age to monitor mental health conditions on smartphones.