Student Perspectives on Digital Phenotyping

Abstract

There is a mental health crisis facing universities internationally. A growing body of interdisciplinary research has successfully demonstrated that using sensor and interaction data from students' smartphones can give insight into stress, depression, mood, suicide risk and more. The approach, which is sometimes termed Digital Phenotyping, has potential to transform how mental health and wellbeing can be monitored and understood. The approach could also transform how interventions are designed, delivered and evaluated. To date, little work has addressed the human and ethical side of digital phenotyping, including how students feel about being monitored. In this paper we report findings from in-depth focus groups, prototyping and interviews with students. We find they are positive about mental health technology, but also that there are multi-layered issues to address if digital phenotyping is to become acceptable. Using an acceptability framework, we set out the key design challenges that need to be addressed. CCS CONCEPTS • Human-centered computing → Empirical studies in ubiquitous and mobile computing;

Exploring the Effects of Technological Writing Assistance for Support Providers in Online Mental Health Community

“…Six of them are undergraduates, and the rest are postgraduates majoring in a variety of fields (e.g., computer science, economics). Previous research suggests that the majority of college students experience some forms of mental distress [8,46,63]. The self-assessments on the severity of depression (measure: PHQ-9 [45]) in prescreening show that our participants could have at least moderate depression: seven moderate (score 10-14), 18 moderately severe (15)(16)(17)(18)(19), and five severe (20-27) [53].…”

Beyond self-reflection: introducing the concept of rumination in personal informatics

“…In the HCI community, there is a larger discussion around using computational approaches to identify and label potentially sensitive human experiences like mental health (e.g., [70]). Researchers have sought to identify and classify mental health experiences from social media data [71][72][73] as well as wearables and app data [74,75]. As researchers, we recognize the potential of these approaches (i.e., early detection and intervention).…”

“…However, we also acknowledge the downsides and risks. For example, researchers studying the use of a digital phenotyping app to assess mental health found students had concerns about their autonomy, control, and dignity [75]. Others studying what can be inferred from social media and online communities have discussed privacy issues, unintended harm, and mislabeling, to name a few [70].…”

Entangled Ethnography: Towards a collective future understanding

“…We have taken several measures in order to increase the acceptability of the research process, as discussed by Rooksby et al [35].…”

“…Practically, a more concrete framework is useful, and the Theoretical Framework for Acceptability can be brought to bear [38]. While intended to make sense of health interventions, it has been applied to personal data [35] and identifies a set of concerns that underpin many interventions into people's lives. Distinct from working with ethical issues, this considers more broadly how acceptable a process is to users, and works on several dimensions.…”