Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. The primary keyword for this post is epistemic agency in self-tracking, because understanding who controls questions and interpretation determines whether self-tracking is mere measurement or true personal science. According to the Frontiers in Public Health review (Sara Riggare et al., published 18 August 2026), an agency-based framework distinguishes low, mixed, and high agency across four inquiry phases, and that distinction has direct consequences for how qualitative researchers should treat self-tracked data.
Key Takeaways
According to the Frontiers in Public Health review (Sara Riggare et al., 18 August 2026), epistemic agency in self-tracking depends on who owns the question: when individuals define, measure, analyze, and share findings, self-tracking becomes personal science rather than only data production. The Frontiers review searched literature in April–May 2025 and used a four-phase framework (Questioning, Observing, Reasoning, Discovering) to classify studies by agency.
- In April–May 2025, the literature search returned 721 records and after screening the authors retained 241 full papers for analysis, according to the Frontiers review (Riggare et al., 18 August 2026).
- Of those 241 papers, 46 used self-tracking as the data-collection method and were classified by agency: 17 low-agency, 10 mixed-agency, and 19 high-agency (Riggare et al., 18 August 2026).
- The Frontiers review found a publication peak in 2018 with 38 articles and an uptick in 2024 with 13 articles, suggesting shifting terminology and renewed academic interest (Riggare et al., 18 August 2026).
- The review’s conservative coding process produced reviewer disagreement rates of 13% at abstract screening (n = 80) and 17% at full-paper categorization in contested cases (n = 8), which the authors resolved collectively (Riggare et al., 18 August 2026).
- The review emphasizes (quoting the paper) that the key test is “who owns the question, ” and that high-agency work often features the self-tracker as co-author (Riggare et al., 18 August 2026).
What Happened: The four-phase agency review and how it was measured
Answer: The Frontiers review applied a four-phase personal science framework to classify how much epistemic agency individuals exercised in self-tracking studies, and it reported concrete counts and dates to support its conclusions.
According to the Frontiers in Public Health review (Riggare et al., 18 August 2026), the authors adapted the personal science cycle into four phases: Questioning, Observing, Reasoning, and Discovering, with three agency levels: low, mixed, and high.
According to the Frontiers review (search conducted April–May 2025), the screening workflow began with 721 records, 241 full papers were retained after exclusion criteria, and 46 papers used self-tracking as the data-collection method eligible for agency coding (Riggare et al., 18 August 2026).
According to the Frontiers review (Riggare et al., 18 August 2026), low-agency studies treated participants primarily as data sources, mixed-agency studies showed partial participant involvement, and high-agency studies displayed the full self-directed cycle often with the self-tracker as co-author.
According to the Frontiers review (Riggare et al., 18 August 2026), methodological decisions included conservative coding rules, dual independent review, and conflict resolution by group discussion to avoid overstating agency.
Findings Snapshot
| Date / Period | Metric | Value | Implication |
|---|---|---|---|
| April–May 2025 | Records returned by search for "quantified self" | 721 | Large, heterogeneous literature that required narrowing to empirical self-tracking studies (Riggare et al., 18 Aug 2026). |
| April–May 2025 | Full papers retained after screening | 241 | Corpus used to analyze how QS appears in scientific literature (Riggare et al., 18 Aug 2026). |
| April–May 2025 | Papers using self-tracking as data-collection | 46 | Subset eligible for agency-level coding with the four-phase framework (Riggare et al., 18 Aug 2026). |
| , | Agency distribution (of 46) | 17 low / 10 mixed / 19 high | Evidence that high-agency personal science is present but not dominant in the QS-labeled literature (Riggare et al., 18 Aug 2026). |
| 2018 and 2024 (publication years) | Peak and recent uptick | 2018: 38; 2024: 13 | Temporal trend shows a 2018 peak and renewed activity by 2024, possibly due to changing terminology (Riggare et al., 18 Aug 2026). |
Implications for qualitative researchers and citizen-science practitioners
Answer: Qualitative researchers should code agency explicitly, treat self-tracked data as hybrid evidence, and design methods that respect who initiated the question, according to the Frontiers review (Riggare et al., 18 August 2026).
According to the Frontiers in Public Health review (Riggare et al., 18 August 2026), the practical distinction is whether the individual or the researcher owns the question, because ownership determines whether self-tracking supports personal science or only supplies data.
According to the Frontiers review (Riggare et al., 18 August 2026), low-agency projects typically require different consent, analysis, and reporting practices than high-agency personal science, which often integrates subjective context as core evidence.
According to the Frontiers review (Riggare et al., 18 August 2026), researchers should document Questioning, Observing, Reasoning, and Discovering phases when analyzing self-tracked datasets to surface participant agency and ethical implications.
How Evidano Helps
Problem: Invisible agency in self-tracked datasets → Solution: explicit phase coding
Answer: Evidano helps teams tag who performed each phase (Questioning, Observing, Reasoning, Discovering) so agency becomes a searchable attribute in qualitative analyses.
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents, and it can ingest self-tracking logs and associated narratives for thematic coding.
Evidano’s thematic and cross-segment analysis surfaces whether questions were participant-initiated or researcher-defined, which directly addresses the Frontiers review’s central test of “who owns the question” (Riggare et al., 18 Aug 2026).
Learn more about relevant features on the Evidano features page.
Problem: Laborious n-of-1 synthesis → Solution: automated AIdriven n-of-1 pipelines
Answer: Evidano automates within-person (n-of-1) synthesis across time series, logs, and interview text so researchers and self-trackers can move from raw traces to interpretable findings faster.
Evidano’s cross-segment and frequency analyses let teams quantify how often a self-tracker performed Reasoning or Discovering steps, turning qualitative practice into reproducible analytic outputs for publication or peer review.
Problem: Privacy and ethics questions in personal science → Solution: secure workflows
Answer: Evidano supports encrypted data storage and PII redaction workflows so teams can analyze sensitive self-tracked data while respecting participant control over sharing and publication.
Evidano’s document ingestion and redaction options help teams follow the Frontiers review recommendation that personal science needs ethical infrastructure and documentation (Riggare et al., 18 Aug 2026).
FAQ: epistemic agency in self-tracking
What is epistemic agency in self-tracking?
Answer: Epistemic agency is the capacity of an individual to act as a producer of knowledge rather than only a source of data.
According to the Frontiers in Public Health review (Riggare et al., 18 August 2026), epistemic agency means a person poses questions, collects and analyzes evidence, reaches conclusions, and is recognized as a credible knower.
According to Catherine Elgin as cited in the review, "Epistemic agents should think of themselves as, and act as, legislating members of a realm of epistemic ends" which the authors invoke to justify the agency framework (Elgin quoted in Riggare et al., 18 Aug 2026).
How did the Frontiers review measure levels of agency?
Answer: The review used a four-phase framework (Questioning, Observing, Reasoning, Discovering) and coded whether each phase was performed by the individual or researchers.
According to the Frontiers review (Riggare et al., 18 August 2026), coding was conservative: when a phase could be ambiguously attributed, the lower agency level was assigned unless clear textual evidence indicated participant control.
Do high-agency personal science studies generalize beyond the individual?
Answer: Personal science primarily produces actionable self-knowledge, but documented n-of-1 findings can inform general hypotheses and methods.
According to the Frontiers review (Riggare et al., 18 August 2026), high-agency projects often appear in peer-reviewed outlets and are shared within communities, enabling methods and insights to be transferred even if the primary aim is individual understanding.
How can AI improve qualitative analysis of personal science?
Answer: AI accelerates thematic coding, links time-series logs to textual reflections, and quantifies cross-segment patterns so researchers can evaluate agency at scale.
According to the Frontiers review (Riggare et al., 18 August 2026), assessing epistemic agency requires tracing Questioning through Discovering, a workflow that AI-enabled platforms can streamline by extracting who initiated queries and who interpreted results across documents.
Conclusion & Next Steps
Answer: The Frontiers in Public Health review (Riggare et al., 18 August 2026) shows that classifying epistemic agency clarifies when self-tracking is personal science and when it is only data production, and AI-enabled qualitative tools can make that classification practical at scale.
According to the Frontiers review (Riggare et al., 18 August 2026), researchers should record who owns the question and preserve the phases of inquiry when publishing self-tracked studies so that epistemic agency is transparent.
If you want to operationalize the four-phase framework in your qualitative workflows, use AI to tag Questioning–Observing–Reasoning–Discovering, synthesize n-of-1 narratives, and produce reproducible codebooks.
Try Evidano for free to pilot AI-enabled thematic, frequency, and cross-segment analyses on self-tracked datasets and participant narratives: Try Evidano for free.
Topics
- epistemic agency in self-tracking
- personal science qualitative analysis
- AI qualitative research
- quantified self citizen science
Keep reading
- Commentary on NewsResearch Guide: Epistemic Agency in Self-TrackingHow to measure epistemic agency in self-tracking for AI-enabled qualitative research. Framework, numbers from Frontiers (Aug 18, 2026), and practical Evidano workflows.
- Commentary on NewsAgency Lens: Epistemic Agency in Self-TrackingTranslate a Frontiers review into AI-enabled qualitative research practice for personal science and epistemic agency. Learn practical steps and tools.
- Commentary on NewsAI-Driven Personal Science Qualitative AnalysisHow AI accelerates qualitative analysis of personal science. Learn key stats from the Frontiersin.org review and practical AI workflows to analyze self-tracking data.