When “Self-Harm” Means “Suicide”: Design Lessons from Adolescents’ Posts on a Peer Support Platform

• In Event: How to Design Just and Equitable Digital Experiences to Support Adolescent Wellbeing

Abstract

Background: Alongside significant increases in adolescent suicide, the last decade has also introduced numerous free, online mental health resources, including information sites (e.g., Psychology Today), message boards (e.g., the subreddit /r/depression), text-based crisis services (e.g., 7 Cups), and dedicated mental health peer support platforms. One such mental health peer support platform, herein referred to as “the Platform,” had close to 500,000 users as of 2018, mostly in their mid-to-late teens. Self-harm is a common topic of posts on the Platform and merits special attention because of its potential lethality. We investigated the content of self-harm posts using topic modeling to (1) characterize adolescents’ online support-seeking about self-harm, (2) provide the foundation for future analysis of peer support via comments, and (3) inform design considerations for mental health support platforms. This is a timely issue because the pandemic has increased both stress and reliance on online sources of support in adolescence.

Methods: Users are generally in their mid-to-late teens when they join the Platform, and 65% percent identify their gender as female, 28% as male, and 7% as “other.” We filtered the dataset to include posts (1) tagged as “Self-Harm” by the user and (2) posted by users aged 13-24. We further filtered the dataset to exclude posts (1) that had subsequently been deleted by the user or (2) by accounts that had subsequently been deleted. This filtering resulted in a dataset of 491,446 posts by 83,390 users. We created three topic models from the posts, with 8, 10, and 18 topics respectively.

Results: Each of the three models was rated for overall interpretability. The model judged to have the highest interpretability was the 8-topic model. Based on probabilities from the 8-topic model, 485,382 posts were categorized by their primary topic. Over half of the self-harm posts (251,504) belonged to the two topics most strongly characterized by suicidal language. Other topics, in descending order by number of posts, included discussion of urges to self-harm (57,219), time “clean” from self-harm (48,547), positive communication with family and friends (43,912), blood and cutting (31,408), requests to talk off the platform (28,640), and self-criticism related to appearance (24,152). The average number of comments on each post was 2 (SD = 2.5). 140,866 posts (28.7%) received zero comments.

Discussion: These findings provide important insight into the online expressions of support-seeking by adolescents discussing self-harm. Although mental health clinicians are accustomed to associating “Self-Harm” with non-suicidal self-injury, these results indicate that users may use the “Self-Harm” label for content related to suicide as well. This would make sense because there is no “Suicide” label built into the Platform. Furthermore, these topics provide an important foundation for the next step in our research: using machine learning to measure the strength of social support offered in comments depending on the topic of the post. Finally, these findings can inform the design of digital spaces that support adolescent mental health.

Authors

• Monika Neff Lind, University of Oregon
  Presenting Author

• Afsaneh Razi, University of Central Florida
  Non-Presenting Author

• Hanneke Scholten, University of Twente
  Non-Presenting Author

• Nicholas Allen, University of Oregon
  Non-Presenting Author

• Munmun De Choudhury, Georgia Institute of Technology
  Non-Presenting Author

• Madeleine George, RTI International
  Non-Presenting Author

• Isabela Granic, Radboud University
  Non-Presenting Author

• Shalini Lal, University of Montreal
  Non-Presenting Author

• Pamela Wisniewski, University of Central Florida
  Non-Presenting Author