Provider perspectives on integrating sensor-captured patient-generated data in mental health care

Ada Ng, Rachel Kornfield, Stephen M. Schueller, Alyson K. Zalta, Michael Brennan, Madhu Reddy

Research output: Contribution to journalEditorialpeer-review

1 Scopus citations

Abstract

The increasing ubiquity of health sensing technology holds promise to enable patients and health care providers to make more informed decisions based on continuously-captured data. The use of sensor-captured patient-generated data (sPGD) has been gaining greater prominence in the assessment of physical health, but we have little understanding of the role that sPGD can play in mental health. To better understand the use of sPGD in mental health, we interviewed care providers in an intensive treatment program (ITP) for veterans with post-traumatic stress disorder. In this program, patients were given Fitbits for their own voluntary use. Providers identified a number of potential benefits from patients’ Fitbit use, such as patient empowerment and opportunities to reinforce therapeutic progress through collaborative data review and interpretation. However, despite the promise of sensor data as offering an “objective” view into patients’ health behavior and symptoms, the relationships between sPGD and therapeutic progress are often ambiguous. Given substantial subjectivity involved in interpreting data from commercial wearables in the context of mental health treatment, providers emphasized potential risks to their patients and were uncertain how to adjust their practice to effectively guide collaborative use of the FitBit and its sPGD. We discuss the implications of these findings for designing systems to leverage sPGD in mental health care.

Original languageEnglish (US)
Article number115
JournalProceedings of the ACM on Human-Computer Interaction
Volume3
Issue numberCSCW
DOIs
StatePublished - Nov 2019

Keywords

  • Mental health
  • Patient-generated data
  • Post-traumatic stress disorder
  • Sensors
  • Wearables

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Human-Computer Interaction
  • Computer Networks and Communications

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