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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Jun 9, 2025
Date Accepted: May 11, 2026

The final, peer-reviewed published version of this preprint can be found here:

Perceived Sensitivity of Sensor-Based Digital Health Data: Qualitative Interview Study

Deeney C, Sonig A, Hurley ME, Tunç B, Storch EA, Herrington JD, Blumenthal-Barby J, Kostick-Quenet K

Perceived Sensitivity of Sensor-Based Digital Health Data: Qualitative Interview Study

JMIR Mhealth Uhealth 2026;14:e78788

DOI: 10.2196/78788

PMID: 42418794

Perceived Sensitivity of Sensor-Based Digital Health Data: A Qualitative Interview Study

  • Christine Deeney; 
  • Anika Sonig; 
  • Meghan E Hurley; 
  • Birkan Tunç; 
  • Eric A Storch; 
  • John D Herrington; 
  • Jennifer Blumenthal-Barby; 
  • Kristin Kostick-Quenet

ABSTRACT

Background:

The integration of digital health tools and algorithms in mental healthcare brings a transformative era where technologies like digital phenotyping, affective computing, and computational behavioral analysis are used to passively collect and analyze data from patients outside clinical settings. These "computer perception" (CP) technologies offer new insights into symptom manifestation in daily life while generating large volumes of potentially sensitive data that raise significant data privacy concerns requiring high levels of patient awareness and consent. Empirical research is lacking into stakeholder understandings and perspective towards the collection, management and protection of these data types.

Objective:

This study aimed to explore key stakeholder perspectives on the sensitivity of CP data, trust in existing data protections, willingness to share CP data externally, and desire for transparency of CP data transactions outside of the clinical space.

Methods:

As part of a larger, multi-site study, we conducted qualitative interviews (n=40) via Zoom with 20 adolescents (aged 12-17 years) familiar with CP tools and their caregivers (n=20). Interviews consisted of a series of open-ended questions regarding stakeholders’ perspectives on privacy, data security, and the use and exchange of CP data. We developed a qualitative codebook to identify and label thematic patterns in responses to questions addressing the topics above, using thematic content analysis to inductively identify themes. Each interview was coded by merging work from at least two separate coders, and several team members contributed to qualitative analysis.

Results:

Most adolescents and caregivers viewed CP data as highly sensitive and expressed a reluctance to share these data beyond their clinical teams. While many participants expressed trust in existing data protections to protect CP data, they often misunderstood or overestimated the extent of protections like HIPAA to safeguard CP data.

Conclusions:

Our findings underscore the critical need for clear and effective patient communication and education about the risks, benefits, and protections associated with CP data through informed consent protocols. To promote greater visibility, understanding, and trust (when justified) in digital tools that have strong promise to promote patient health, we recommend five key strategies, including: (1) educating patients on the limitations of existing data protections; (2) conducting targeted research, including forensic analyses, into secondary data exchanges and to identify privacy breaches or reidentification risks; (3) enacting regulations that mandate greater transparency in health data transactions; (4) implementing computational mechanisms, such as distributed ledger technologies, to enhance data traceability and auditability; and (5) adopting dynamic consent models that allow patients to continuously manage and update their consent preferences.


 Citation

Please cite as:

Deeney C, Sonig A, Hurley ME, Tunç B, Storch EA, Herrington JD, Blumenthal-Barby J, Kostick-Quenet K

Perceived Sensitivity of Sensor-Based Digital Health Data: Qualitative Interview Study

JMIR Mhealth Uhealth 2026;14:e78788

DOI: 10.2196/78788

PMID: 42418794

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