Public Opinions on Using Social Media Content to Identify Users With Depression and Target Mental Health Care Advertising: Mixed Methods Survey.
depression
machine learning
mental health
public opinion
social license
social media
survey
Journal
JMIR mental health
ISSN: 2368-7959
Titre abrégé: JMIR Ment Health
Pays: Canada
ID NLM: 101658926
Informations de publication
Date de publication:
13 Nov 2019
13 Nov 2019
Historique:
received:
27
11
2018
accepted:
21
08
2019
revised:
17
05
2019
entrez:
14
11
2019
pubmed:
14
11
2019
medline:
14
11
2019
Statut:
epublish
Résumé
Depression is a common disorder that still remains underdiagnosed and undertreated in the UK National Health Service. Charities and voluntary organizations offer mental health services, but they are still struggling to promote these services to the individuals who need them. By analyzing social media (SM) content using machine learning techniques, it may be possible to identify which SM users are currently experiencing low mood, thus enabling the targeted advertising of mental health services to the individuals who would benefit from them. This study aimed to understand SM users' opinions of analysis of SM content for depression and targeted advertising on SM for mental health services. A Web-based, mixed methods, cross-sectional survey was administered to SM users aged 16 years or older within the United Kingdom. It asked participants about their demographics, their usage of SM, and their history of depression and presented structured and open-ended questions on views of SM content being analyzed for depression and views on receiving targeted advertising for mental health services. A total of 183 participants completed the survey, and 114 (62.3%) of them had previously experienced depression. Participants indicated that they posted less during low moods, and they believed that their SM content would not reflect their depression. They could see the possible benefits of identifying depression from SM content but did not believe that the risks to privacy outweighed these benefits. A majority of the participants would not provide consent for such analysis to be conducted on their data and considered it to be intrusive and exposing. In a climate of distrust of SM platforms' usage of personal data, participants in this survey did not perceive that the benefits of targeting advertisements for mental health services to individuals analyzed as having depression would outweigh the risks to privacy. Future work in this area should proceed with caution and should engage stakeholders at all stages to maximize the transparency and trustworthiness of such research endeavors.
Sections du résumé
BACKGROUND
BACKGROUND
Depression is a common disorder that still remains underdiagnosed and undertreated in the UK National Health Service. Charities and voluntary organizations offer mental health services, but they are still struggling to promote these services to the individuals who need them. By analyzing social media (SM) content using machine learning techniques, it may be possible to identify which SM users are currently experiencing low mood, thus enabling the targeted advertising of mental health services to the individuals who would benefit from them.
OBJECTIVE
OBJECTIVE
This study aimed to understand SM users' opinions of analysis of SM content for depression and targeted advertising on SM for mental health services.
METHODS
METHODS
A Web-based, mixed methods, cross-sectional survey was administered to SM users aged 16 years or older within the United Kingdom. It asked participants about their demographics, their usage of SM, and their history of depression and presented structured and open-ended questions on views of SM content being analyzed for depression and views on receiving targeted advertising for mental health services.
RESULTS
RESULTS
A total of 183 participants completed the survey, and 114 (62.3%) of them had previously experienced depression. Participants indicated that they posted less during low moods, and they believed that their SM content would not reflect their depression. They could see the possible benefits of identifying depression from SM content but did not believe that the risks to privacy outweighed these benefits. A majority of the participants would not provide consent for such analysis to be conducted on their data and considered it to be intrusive and exposing.
CONCLUSIONS
CONCLUSIONS
In a climate of distrust of SM platforms' usage of personal data, participants in this survey did not perceive that the benefits of targeting advertisements for mental health services to individuals analyzed as having depression would outweigh the risks to privacy. Future work in this area should proceed with caution and should engage stakeholders at all stages to maximize the transparency and trustworthiness of such research endeavors.
Identifiants
pubmed: 31719022
pii: v6i11e12942
doi: 10.2196/12942
pmc: PMC6881781
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e12942Informations de copyright
©Elizabeth Ford, Keegan Curlewis, Akkapon Wongkoblap, Vasa Curcin. Originally published in JMIR Mental Health (http://mental.jmir.org), 13.11.2019.
Références
AMIA Jt Summits Transl Sci Proc. 2019 May 06;2019:44-53
pubmed: 31258955
Ann Fam Med. 2011 Jul-Aug;9(4):305-11
pubmed: 21747101
BMC Med Inform Decis Mak. 2018 Jun 14;18(1):38
pubmed: 29898743
Aust N Z J Psychiatry. 2014 Jun;48(6):571-8
pubmed: 24413807
Curr Opin Psychol. 2016 Jun;9:77-82
pubmed: 27042689
Ann Fam Med. 2011 Sep-Oct;9(5):439-46
pubmed: 21911763
J Psychiatry Neurosci. 2015 Jul;40(4):219-21
pubmed: 26107348
J Med Internet Res. 2017 Jun 29;19(6):e228
pubmed: 28663166
Lancet. 2018 Feb 17;391(10121):679-686
pubmed: 29224931
Annu Rev Clin Psychol. 2017 May 8;13:23-47
pubmed: 28375728
Int J Ment Health Syst. 2015 Aug 30;9:34
pubmed: 26322123
Lancet Psychiatry. 2016 Nov;3(11):1087-1090
pubmed: 27794373
J Med Internet Res. 2014 Dec 22;16(12):e290
pubmed: 25533619
Hum Psychopharmacol. 2002 Jun;17 Suppl 1:S1-11
pubmed: 12404663
J Med Ethics. 2015 May;41(5):404-9
pubmed: 25617016
Ment Health Fam Med. 2008 Jun;5(2):121-3
pubmed: 22477857
Dialogues Clin Neurosci. 2008;10(3):271-7
pubmed: 18979940
Am J Psychiatry. 2003 Aug;160(8):1494-500
pubmed: 12900313
BMJ. 2002 Nov 2;325(7371):1016-7
pubmed: 12411363
Prim Care Companion J Clin Psychiatry. 2005;7(4):167-76
pubmed: 16163400
Qual Health Res. 2016 Nov;26(13):1753-1760
pubmed: 26613970
Depress Anxiety. 2011 Jun;28(6):447-55
pubmed: 21400639