Investigating patient attitudes towards the use of social media data to augment depression diagnosis and treatment: A qualitative study

Jude Mikal; Samantha Hurst; Mike Conway

Investigating patient attitudes towards the use of social media data to augment depression diagnosis and treatment: A qualitative study

Jude Mikal, Samantha Hurst, Mike Conway

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we use qualitative research methods to investigate the attitudes of social media users towards the (opt-in) integration of social media data with routine mental health care and diagnosis. Our investigation was based on secondary analysis of a series of five focus groups with Twitter users, including three groups consisting of participants with a self-reported history of depression, and two groups consisting of participants without a self-reported history of depression. Our results indicate that, overall, research participants were enthusiastic about the possibility of using social media (in conjunction with automated Natural Language Processing algorithms) for mood tracking under the supervision of a mental health practitioner. However, for at least some participants, there was skepticism related to how well social media represents the mental health of users, and hence its usefulness in the clinical context.

Original language	English (US)
Title of host publication	Proceedings of the 4th Workshop on Computational Linguistics and Clinical Psychology - From Linguistic Signal to Clinical Reality, CLPsych 2017 at the Annual Meeting of the Association for Computational Linguistics, ACL 2017
Editors	Kristy Hollingshead, Molly E. Ireland, Kate Loveys
Publisher	Association for Computational Linguistics (ACL)
Pages	41-47
Number of pages	7
ISBN (Electronic)	9781945626678
State	Published - 2017
Event	4th Workshop on Computational Linguistics and Clinical Psychology - From Linguistic Signal to Clinical Reality, CLPsych 2017 at the Annual Meeting of the Association for Computational Linguistics, ACL 2017 - Vancouver, Canada Duration: Aug 3 2017 → …

Publication series

Name	Proceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)	0736-587X

Conference

Conference	4th Workshop on Computational Linguistics and Clinical Psychology - From Linguistic Signal to Clinical Reality, CLPsych 2017 at the Annual Meeting of the Association for Computational Linguistics, ACL 2017
Country/Territory	Canada
City	Vancouver
Period	8/3/17 → …

Bibliographical note

Publisher Copyright:
© 2017 Association for Computational Linguistics.

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Mikal, J., Hurst, S., & Conway, M. (2017). Investigating patient attitudes towards the use of social media data to augment depression diagnosis and treatment: A qualitative study. In K. Hollingshead, M. E. Ireland, & K. Loveys (Eds.), Proceedings of the 4th Workshop on Computational Linguistics and Clinical Psychology - From Linguistic Signal to Clinical Reality, CLPsych 2017 at the Annual Meeting of the Association for Computational Linguistics, ACL 2017 (pp. 41-47). (Proceedings of the Annual Meeting of the Association for Computational Linguistics). Association for Computational Linguistics (ACL).

Investigating patient attitudes towards the use of social media data to augment depression diagnosis and treatment: A qualitative study. / Mikal, Jude; Hurst, Samantha; Conway, Mike.
Proceedings of the 4th Workshop on Computational Linguistics and Clinical Psychology - From Linguistic Signal to Clinical Reality, CLPsych 2017 at the Annual Meeting of the Association for Computational Linguistics, ACL 2017. ed. / Kristy Hollingshead; Molly E. Ireland; Kate Loveys. Association for Computational Linguistics (ACL), 2017. p. 41-47 (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mikal, J, Hurst, S & Conway, M 2017, Investigating patient attitudes towards the use of social media data to augment depression diagnosis and treatment: A qualitative study. in K Hollingshead, ME Ireland & K Loveys (eds), Proceedings of the 4th Workshop on Computational Linguistics and Clinical Psychology - From Linguistic Signal to Clinical Reality, CLPsych 2017 at the Annual Meeting of the Association for Computational Linguistics, ACL 2017. Proceedings of the Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics (ACL), pp. 41-47, 4th Workshop on Computational Linguistics and Clinical Psychology - From Linguistic Signal to Clinical Reality, CLPsych 2017 at the Annual Meeting of the Association for Computational Linguistics, ACL 2017, Vancouver, Canada, 8/3/17.

Mikal J, Hurst S, Conway M. Investigating patient attitudes towards the use of social media data to augment depression diagnosis and treatment: A qualitative study. In Hollingshead K, Ireland ME, Loveys K, editors, Proceedings of the 4th Workshop on Computational Linguistics and Clinical Psychology - From Linguistic Signal to Clinical Reality, CLPsych 2017 at the Annual Meeting of the Association for Computational Linguistics, ACL 2017. Association for Computational Linguistics (ACL). 2017. p. 41-47. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

Mikal, Jude ; Hurst, Samantha ; Conway, Mike. / Investigating patient attitudes towards the use of social media data to augment depression diagnosis and treatment : A qualitative study. Proceedings of the 4th Workshop on Computational Linguistics and Clinical Psychology - From Linguistic Signal to Clinical Reality, CLPsych 2017 at the Annual Meeting of the Association for Computational Linguistics, ACL 2017. editor / Kristy Hollingshead ; Molly E. Ireland ; Kate Loveys. Association for Computational Linguistics (ACL), 2017. pp. 41-47 (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

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abstract = "In this paper, we use qualitative research methods to investigate the attitudes of social media users towards the (opt-in) integration of social media data with routine mental health care and diagnosis. Our investigation was based on secondary analysis of a series of five focus groups with Twitter users, including three groups consisting of participants with a self-reported history of depression, and two groups consisting of participants without a self-reported history of depression. Our results indicate that, overall, research participants were enthusiastic about the possibility of using social media (in conjunction with automated Natural Language Processing algorithms) for mood tracking under the supervision of a mental health practitioner. However, for at least some participants, there was skepticism related to how well social media represents the mental health of users, and hence its usefulness in the clinical context.",

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Investigating patient attitudes towards the use of social media data to augment depression diagnosis and treatment: A qualitative study

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