Adoption of Mobile Apps for Depression and Anxiety: Cross-Sectional Survey Study on Patient Interest and Barriers to Engagement.
anxiety
depression
mHealth
mobile apps
patient preference
Journal
JMIR mental health
ISSN: 2368-7959
Titre abrégé: JMIR Ment Health
Pays: Canada
ID NLM: 101658926
Informations de publication
Date de publication:
25 Jan 2019
25 Jan 2019
Historique:
received:
18
06
2018
accepted:
08
09
2018
revised:
21
08
2018
entrez:
26
1
2019
pubmed:
27
1
2019
medline:
27
1
2019
Statut:
epublish
Résumé
Emerging research suggests that mobile apps can be used to effectively treat common mental illnesses like depression and anxiety. Despite promising efficacy results and ease of access to these interventions, adoption of mobile health (mHealth; mobile device-delivered) interventions for mental illness has been limited. More insight into patients' perspectives on mHealth interventions is required to create effective implementation strategies and to adapt existing interventions to facilitate higher rates of adoption. The aim of this study was to examine, from the patient perspective, current use and factors that may impact the use of mHealth interventions for mental illness. This was a cross-sectional survey study of veterans who had attended an appointment at a single Veterans Health Administration facility in early 2016 that was associated with one of the following mental health concerns: unipolar depression, any anxiety disorder, or posttraumatic stress disorder. We used the Veteran Affairs Corporate Data Warehouse to create subsets of eligible participants demographically stratified by gender (male or female) and minority status (white or nonwhite). From each subset, 100 participants were selected at random and mailed a paper survey with items addressing the demographics, overall health, mental health, technology ownership or use, interest in mobile app interventions for mental illness, reasons for use or nonuse, and interest in specific features of mobile apps for mental illness. Of the 400 potential participants, 149 (37.3%, 149/400) completed and returned a survey. Most participants (79.9%, 119/149) reported that they owned a smart device and that they use apps in general (71.1%, 106/149). Most participants (73.1%, 87/149) reported interest in using an app for mental illness, but only 10.7% (16/149) had done so. Paired samples t tests indicated that ratings of interest in using an app recommended by a clinician were significantly greater than general interest ratings and even greater when the recommending clinician was a specialty mental health provider. The most frequent concerns related to using an app for mental illness were lacking proof of efficacy (71.8%, 107/149), concerns about data privacy (59.1%, 88/149), and not knowing where to find such an app (51.0%, 76/149). Participants expressed interest in a number of app features with particularly high-interest ratings for context-sensitive apps (85.2%, 127/149), and apps focused on the following areas: increasing exercise (75.8%, 113/149), improving sleep (73.2%, 109/149), changing negative thinking (70.5%, 105/149), and increasing involvement in activities (67.1%, 100/149). Most respondents had access to devices to use mobile apps for mental illness, already used apps for other purposes, and were interested in mobile apps for mental illness. Key factors that may improve adoption include provider endorsement, greater publicity of efficacious apps, and clear messaging about efficacy and privacy of information. Finally, multifaceted apps that address a range of concerns, from sleep to negative thought patterns, may be best received.
Sections du résumé
BACKGROUND
BACKGROUND
Emerging research suggests that mobile apps can be used to effectively treat common mental illnesses like depression and anxiety. Despite promising efficacy results and ease of access to these interventions, adoption of mobile health (mHealth; mobile device-delivered) interventions for mental illness has been limited. More insight into patients' perspectives on mHealth interventions is required to create effective implementation strategies and to adapt existing interventions to facilitate higher rates of adoption.
OBJECTIVE
OBJECTIVE
The aim of this study was to examine, from the patient perspective, current use and factors that may impact the use of mHealth interventions for mental illness.
METHODS
METHODS
This was a cross-sectional survey study of veterans who had attended an appointment at a single Veterans Health Administration facility in early 2016 that was associated with one of the following mental health concerns: unipolar depression, any anxiety disorder, or posttraumatic stress disorder. We used the Veteran Affairs Corporate Data Warehouse to create subsets of eligible participants demographically stratified by gender (male or female) and minority status (white or nonwhite). From each subset, 100 participants were selected at random and mailed a paper survey with items addressing the demographics, overall health, mental health, technology ownership or use, interest in mobile app interventions for mental illness, reasons for use or nonuse, and interest in specific features of mobile apps for mental illness.
RESULTS
RESULTS
Of the 400 potential participants, 149 (37.3%, 149/400) completed and returned a survey. Most participants (79.9%, 119/149) reported that they owned a smart device and that they use apps in general (71.1%, 106/149). Most participants (73.1%, 87/149) reported interest in using an app for mental illness, but only 10.7% (16/149) had done so. Paired samples t tests indicated that ratings of interest in using an app recommended by a clinician were significantly greater than general interest ratings and even greater when the recommending clinician was a specialty mental health provider. The most frequent concerns related to using an app for mental illness were lacking proof of efficacy (71.8%, 107/149), concerns about data privacy (59.1%, 88/149), and not knowing where to find such an app (51.0%, 76/149). Participants expressed interest in a number of app features with particularly high-interest ratings for context-sensitive apps (85.2%, 127/149), and apps focused on the following areas: increasing exercise (75.8%, 113/149), improving sleep (73.2%, 109/149), changing negative thinking (70.5%, 105/149), and increasing involvement in activities (67.1%, 100/149).
CONCLUSIONS
CONCLUSIONS
Most respondents had access to devices to use mobile apps for mental illness, already used apps for other purposes, and were interested in mobile apps for mental illness. Key factors that may improve adoption include provider endorsement, greater publicity of efficacious apps, and clear messaging about efficacy and privacy of information. Finally, multifaceted apps that address a range of concerns, from sleep to negative thought patterns, may be best received.
Identifiants
pubmed: 30681968
pii: v6i1e11334
doi: 10.2196/11334
pmc: PMC6367667
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e11334Informations de copyright
©Jessica Lipschitz, Christopher J Miller, Timothy P Hogan, Katherine E Burdick, Rachel Lippin-Foster, Steven R Simon, James Burgess. Originally published in JMIR Mental Health (http://mental.jmir.org), 25.01.2019.
Références
Eff Clin Pract. 1999 Mar-Apr;2(2):56-62
pubmed: 10538477
J Gen Intern Med. 2001 Sep;16(9):606-13
pubmed: 11556941
Compr Psychiatry. 2004 Mar-Apr;45(2):129-37
pubmed: 14999664
Prim Care Companion J Clin Psychiatry. 2000 Jun;2(3):71-79
pubmed: 15014652
Arch Gen Psychiatry. 2005 Jun;62(6):617-27
pubmed: 15939839
Arch Intern Med. 2006 May 22;166(10):1092-7
pubmed: 16717171
Ann Intern Med. 2007 Mar 6;146(5):317-25
pubmed: 17339617
Med Care. 2008 Mar;46(3):266-74
pubmed: 18388841
J Affect Disord. 2009 Apr;114(1-3):163-73
pubmed: 18752852
Diabet Med. 2011 Apr;28(4):455-63
pubmed: 21392066
J Med Internet Res. 2011 Mar 10;13(1):e30
pubmed: 21393123
Cogn Behav Ther. 2011;40(4):251-66
pubmed: 22060248
CMAJ. 2012 Feb 21;184(3):E191-6
pubmed: 22184363
J Med Internet Res. 2013 Apr 04;15(4):e70
pubmed: 23557596
J Med Internet Res. 2013 Apr 18;15(4):e86
pubmed: 23598614
World Psychiatry. 2013 Jun;12(2):137-48
pubmed: 23737423
PLoS One. 2014 Jan 17;9(1):e84323
pubmed: 24465404
Mil Med. 2014 Nov;179(11):1218-22
pubmed: 25373044
JMIR Mhealth Uhealth. 2015 Nov 04;3(4):e101
pubmed: 26537656
JMIR Ment Health. 2015 Mar 24;2(1):e8
pubmed: 26543914
BMJ. 2015 Nov 11;351:h5627
pubmed: 26559241
J Rehabil Res Dev. 2015;52(6):725-38
pubmed: 26562090
JMIR Ment Health. 2016 Mar 01;3(1):e7
pubmed: 26932350
Telemed J E Health. 2016 Oct;22(10):847-854
pubmed: 26982279
PLoS One. 2016 May 02;11(5):e0154248
pubmed: 27135410
J Med Internet Res. 2017 Jan 05;19(1):e10
pubmed: 28057609
J Affect Disord. 2017 Aug 15;218:15-22
pubmed: 28456072
World Psychiatry. 2017 Oct;16(3):287-298
pubmed: 28941113
JMIR Mhealth Uhealth. 2018 Jan 17;6(1):e23
pubmed: 29343463
Telemed J E Health. 2018 Nov;24(11):870-878
pubmed: 29480752
Psychol Serv. 2018 May 21;:null
pubmed: 29781656
J Med Internet Res. 2018 Jun 11;20(6):e10141
pubmed: 29891468
Digit Health. 2017 Jun 08;3:2055207617713827
pubmed: 29942605
J Gerontol. 1994 May;49(3):M109-15
pubmed: 8169332
Am J Psychiatry. 1996 Oct;153(10):1293-300
pubmed: 8831437