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Using Passive Sensing to Predict Psychosis Relapse: An In-Depth Qualitative Study Exploring Perspectives of People

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People with psychosis have mixed feelings about passive sensing for relapse prevention. Ensuring privacy, user choice, and perceived benefits are crucial for engagement with digital remote monitoring (DRM) systems.

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Area of Science:

  • Digital mental health
  • Psychosis research
  • Human-computer interaction

Background:

  • Relapses in psychosis lead to adverse outcomes and high healthcare costs.
  • Digital remote monitoring (DRM) with passive sensing offers potential for early relapse detection.
  • Passive sensing collects sensor data via smartphones and wearables for low-burden monitoring.

Purpose of the Study:

  • To explore perspectives of individuals with psychosis on using passive sensing for relapse monitoring.
  • To understand user concerns and preferences regarding passive sensing technologies.

Main Methods:

  • Qualitative interviews with 58 participants diagnosed with schizophrenia-spectrum psychosis.
  • Reflexive thematic analysis of interview data.
  • Involvement of a lived experience advisory group throughout the study.

Main Results:

  • Participants expressed polarized views on passive sensing, with significant privacy concerns, particularly regarding location data.
  • Fears of clinician judgment and loss of autonomy were identified, leading to pressure to alter behavior.
  • Valued solutions included user control over data sharing and perceived benefits like ease of use and early relapse detection.

Conclusions:

  • User engagement with passive sensing hinges on perceived personal benefits and addressing privacy concerns.
  • Emphasizing informed consent, user choice, and autonomy is vital for successful DRM implementation.
  • Clear communication regarding data collection, costs, and benefits is essential for prospective users.