Personalized Intervention: N-of-1 Trials Using Wearable Devices

Personalized clinical research is gaining momentum as the limitations of population-based studies in guiding individual patient care become more apparent. Traditional clinical trials primarily aim to determine treatment effects at the cohort level, often producing results that best fit the "average" participant. However, this population-optimized approach can fall short when applied to single patients whose responses to treatments might differ significantly from group averages. As healthcare moves toward individualized medicine, the need for methodologies that generate actionable knowledge at the level of the single person is increasingly recognized.

Recent advances in digital health have positioned N-of-1 trials—individualized, single-case experimental designs—as a promising solution to this challenge. The emergence and widespread availability of wearable devices enable continuous, real-time collection of objective clinical data outside traditional medical environments. These devices facilitate high-frequency measurement of outcomes such as activity levels, physiological signals, and symptoms, providing a rich and granular dataset ideal for N-of-1 trial methodologies. Current investigations demonstrate that such integration can uncover individual treatment responses more precisely, but the field must further address how best to design, implement, and interpret these personalized studies.

This Research Topic aims to explore innovative applications, methodological frameworks, and evidence generated from N-of-1 trials that incorporate wearable device data, with the overarching objective of advancing individualized medical decision-making. The focus is on identifying best practices, addressing current methodological limitations, and evaluating the clinical relevance and practical utility of digitally supported N-of-1 designs.

To gather further insights into the intersection of N-of-1 trial methodology and wearable health technologies, we welcome articles addressing, but not limited to, the following themes:

- Design and statistical methods for N-of-1 trials using wearable data.
- Case studies and real-world implementations of digitally supported N-of-1 trials.
- Integration of wearable devices into clinical and remote research settings.
- Challenges in data quality, privacy, and adherence in wearable-based trials.
- Translational impact of N-of-1 evidence on clinical decision-making and patient outcomes.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: N-of-1 trial, single patient, within patient, wearable device, wearable sensor, digital biomarker, digital health, remote monitor, continuous monitor, high frequency measurement, treatment effect, personalized medicine, precision medicine

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.