Public Opinions on Using Social Media Content to Identify Users With Depression and Target Mental Health Care Advertising: Mixed Methods Survey

Abstract

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 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 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 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 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.

Privacy considerations when predicting mental health using social media

“…It is clear that many actions taken by social media services are considered an invasion of user privacy, specifically regarding information about their mental health, with most of those actions falling under the category of intrusion . For example, a previous study mentioned that some social media users feel that it is intrusive their mental health status is profiled on social media forums (Ford et al, 2019). It may be difficult to find a balance between protecting every user's privacy on social media and using social media data for physicians to help individuals for their mental illnesses.…”

Human-Computer Interaction, Ethics, and Biomedical Informatics

“…The presence of both missing information and misinformation generated by both individuals and automated bots emphasizes the need to design systems that use clear communication of potential risks to mitigate adverse consequences [38,39]. The use of social media for targeted advertising, particularly for sensitive topics such as mental health services, presents additional questions as to which applications of these data are considered to be acceptable [40]. A final concern relates to patient understanding of privacy risks as communicated by complex, evolving, and opaque terms and conditions on social media platforms [36,39].…”

Views on social media and its linkage to longitudinal data from two generations of a UK cohort study

“…The use of social media data for research has also had its own ethical challenges concerning privacy and informed consent 15,16 , as well as difficulty defining what mediums are included in the definition of social media at all 17 . A systematic review by Golder et al 18 in 2017 found that social media users and researchers tended to be conflicted about whether informed consent was necessary for data collected from public social media sites and, similarly to data linkage issues, this debate tended to rest on the nature of the content, which source the data came from and how the data would be used 14,[19][20][21] . Subsequent ethical guidelines developed for the field have placed special consideration on the reporting of social media research to ensure user's privacy 22,23 , and reflects participant's views that increased sensitivity and personal identifiability of the subject matter should increase the level of anonymity with which it is reported 15,19,24 .…”

“…Within the UK the failure of the care.data program is cited as a reminder that even where data science initiatives are legal and technically feasible they can still fail if they lack the ‘social licence’ needed for public and key stakeholder support 10 . Existing research in the field of record linkage, outside of social media linkage, has found that there is a general acceptance of this work from the public 11 – 13 , even when conducted without consent if data is appropriately anonymised 13 , but that these decisions are ultimately complex and conditional on the situation 9 , 11 – 14 . Therefore, it is essential that any novel data linkage activity, or a novel use of existing data, is informed by exploring participant views towards its acceptability, as well as researchers exploring the participants understanding of the data and how it will be used.…”