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Title: Digital Self-Harm: Implications of Eating Disordered Behaviors Online
Jessica Pater
Human Centered Computing PhD Candidate
School of Interactive Computing
College of Computing
Georgia Institute of Technology
Date: Friday, Spetember 20, 2019
Time: 3:00 PM EDT
Location: GVU Cafe (TSRB 2nd Floor)
Committee:
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Dr. Elizabeth Mynatt, School of Interactive Computing (Advisor)
Dr. Amy Bruckman, School of Interactive Computing
Dr. Rebecca Grinter, School of Interactive Computing
Dr. Tammy Toscos, Health Services and Informatics, Parkview Research Center
Dr. John Torous, Digital Psychiatry, Harvard Medical School
Abstract:
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The access to social technologies is ubiquitous - one in four millennials report being continuously connected to the Internet. With this level of connectivity, there has also been an increase in behavioral and mental health issues associated with the unhealthy use of these technologies. The social computing field has many promising ways to assess shifts in mental health states using social media data. These approaches utilize public data sets. While critical in the development of the computational approaches, they are limited in that they are unable to validate the mental health status of the individual’s posting the data.
In my thesis, I expanded the definition of digital self-harm to include any online communication and activity that leads to, supports, or exacerbates, non-suicidal yet intentional harm or impairment of an individual’s physical well-being. I use an exemplar of the pro-eating disorder community to characterize how this set of diseases are presented across social media platforms. Through the partnership with a regional healthcare system, I assessed the perceptions of digital self-harm with both healthcare providers and patients with a clinically diagnosed eating disorder. An evaluation of patient’s use of technology leading up to the start of their recovery journey provides key insights into how technology amplified the physical manifestation of the patient’s disease and the challenges of using digital traces to identify their mental health state.
