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

Clinical Snapshot

Key Findings

• P Value: Not applicable — qualitative study

• Effect Size: Not applicable — qualitative study; no quantitative effect sizes reported

• Primary Outcome: Most adolescents and caregivers perceived computer perception (CP) data as highly sensitive and expressed reluctance to share these data beyond their immediate clinical teams

• Nnt Or Sensitivity: Not applicable — qualitative study. Key qualitative finding: participants frequently misunderstood or overestimated the extent of existing legal and institutional protections safeguarding CP data, indicating a significant gap between perceived and actual data protection

• Confidence Interval: Not applicable — qualitative study

Clinical Application

The study's recommendations — including patient education about data protection, dynamic consent models, and improved data traceability — are feasible to implement within existing clinical workflows, though they require institutional investment in consent infrastructure and staff training. Dynamic consent platforms and distributed ledger technologies represent emerging but not yet mainstream solutions requiring further development and regulatory alignment before widespread clinical adoption. In Australia, digital health data governance is regulated under the Privacy Act 1988 (Cth), the My Health Records Act 2012, and the Australian Privacy Principles (APPs). The Australian Digital Health Agency (ADHA) oversees national digital health strategy, and the TGA regulates software as a medical device (SaMD) under the Therapeutic Goods (Medical Devices) Regulations 2002. Digital phenotyping and affective computing tools used in mental health contexts may require TGA SaMD classification depending on their intended purpose. The RACGP's digital health guidelines and the Royal Australian and New Zealand College of Psychiatrists (RANZCP) position statements on digital mental health are relevant frameworks. The finding that patients overestimate existing data protections is particularly pertinent in the Australian context, where public understanding of My Health Record data sharing and secondary use provisions has historically been limited. Medicare-funded mental health services (Better Access initiative) increasingly interface with digital health tools, making informed consent education a priority for GPs and mental health practitioners. The PBS does not currently fund digital therapeutics, but this landscape is evolving with the ADHA's National Digital Health Strategy 2023–2028. Adolescents aged 12–17 years and their caregivers engaged with digital mental health tools that passively collect behavioural, physiological, or affective data; clinicians and health services deploying digital phenotyping or computational behavioural analysis in mental health care

Abstract

BACKGROUND: Digital health tools are increasingly used in mental health care to passively collect patient data and analyze health status outside of clinical settings. While technologies such as digital phenotyping, affective computing, and computational behavioral analysis offer new insights into symptom manifestation in daily life, they generate large volumes of potentially sensitive data that raise significant data privacy concerns, requiring high levels of patient awareness and consent. Empirical research is lacking on stakeholder understandings toward the sensitivity of these data and expectations for data stewardship, perspectives that are critical for developing robust informed consent and data protection policies for digital health data use. OBJECTIVE: This study aimed to explore key stakeholder perspectives on the sensitivity of computer perception (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, multisite study, we conducted qualitative interviews (n=40) via Zoom (Zoom Communications, Inc) 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 identify themes inductively. 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 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 transparency, understanding, and trust, we recommend 5 strategies: educating patients about data protection; studying secondary data exchange and reidentification risks; strengthening transparency regulations; improving data traceability mechanisms, such as distributed ledger technologies, to enhance data traceability and auditability; and adopting dynamic consent models.

References

1. 1.Deeney, C., Sonig, A., Hurley, M. E., Tunç, B., Storch, E. A., Herrington, J. D., Blumenthal-Barby, J., & Kostick-Quenet, K. (2026). Perceived sensitivity of sensor-based digital health data: Qualitative interview study. JMIR mHealth and uHealth. https://doi.org/10.2196/78788