Epistemic agency in self-tracking is the degree to which people who track themselves control the questions, methods, analysis, and dissemination of findings, and the primary audience for this post is qualitative researchers and research teams working with participant-generated health data. Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. According to the Frontiersin.org conceptual review by Sara Riggare (published 18 August 2026), the literature on the Quantified Self was searched in April–May 2025 and a working corpus was selected to evaluate whether self-tracking functions as mere measurement or as self-directed knowledge production. This post explains the review's methods and numbers, extracts practical implications for qualitative researchers, and maps common problems in analyzing personal science to specific AI-enabled qualitative research solutions, so teams can adopt workflows that preserve participant epistemic agency.
Key Takeaways
According to the Frontiersin.org review by Sara Riggare (published 18 August 2026), self-tracking in health spans a spectrum from low agency to high agency, hinging on "who owns the question." Frontiersin.org.
- The review searched Web of Science and PubMed in April–May 2025 and retrieved 721 records, of which 241 full papers were retained for analysis, according to the Frontiersin.org article (18 August 2026).
- Among the 241 retained papers, 46 used self-tracking as the data-collection method and were classified by agency level: 17 low-agency, 10 mixed-agency, and 19 high-agency studies, as reported by Riggare (Frontiersin.org, 18 August 2026).
- The review's conceptual framework adapts personal science into four phases (Questioning, Observing, Reasoning, Discovering) so that high-agency work shows the full cycle owned by the individual (Riggare, Frontiersin.org, 18 August 2026).
- The review emphasizes epistemic risk when participants are treated as data suppliers: "epistemic agency" matters because, as the article puts it, the difference between measurement and knowledge production turns on "who owns the question." (Riggare, Frontiersin.org, 18 August 2026).
What happened and how the review measures agency
The Frontiersin.org review classified quantified self papers by who performed each step of inquiry, answering how the literature represents self-tracking: Questioning, Observing, Reasoning, Discovering (Riggare, Frontiersin.org, 18 August 2026).
The review used Jaakkola’s theory-synthesis approach and an adapted four-phase personal science framework to treat agency as a three-level variable (low, mixed, high), as described in the Methods section of the Frontiersin.org article (Riggare, 18 August 2026).
Key methodological details from the Frontiersin.org review include a search in Web of Science and PubMed in April–May 2025 yielding 721 unique records, screening down to 241 full papers, and a final analytic subset of 46 papers that actually used self-tracking as a data-collection method (Riggare, Frontiersin.org, 18 August 2026).
The review resolved reviewer disagreements by discussion and author consultation and adopted a conservative coding rule: where attribution was ambiguous, the lower agency level was assigned (Riggare, Frontiersin.org, 18 August 2026).
Findings snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| April–May 2025 | Search results (Web of Science + PubMed) | 721 records | Large, heterogeneous literature using the keyword "quantified self" (Frontiersin.org, 18 Aug 2026). |
| April–May 2025 | Full papers retained | 241 papers | Corpus for conceptual analysis after exclusions (Frontiersin.org, 18 Aug 2026). |
| April–May 2025 | Papers using self-tracking as data collection | 46 papers | Subset eligible for agency coding using the four-phase framework (Riggare, Frontiersin.org, 18 Aug 2026). |
| As coded in 2026 | Agency breakdown among 46 papers | 17 low / 10 mixed / 19 high | Self-tracking appears across the full agency spectrum with 19 high-agency examples (Riggare, Frontiersin.org, 18 Aug 2026). |
| 2018 vs 2024 | Publication peak & recent trend | 2018: 38 papers; 2024: 13 papers | Keyword usage peaked in 2018; a 2024 uptick suggests renewed or relabeled activity (Riggare, Frontiersin.org, 18 Aug 2026). |
Implications for qualitative researchers and study teams
Qualitative researchers should use the agency framework to decide whether a project treats participants as data providers or as co-investigators, because the Frontiersin.org review shows that the substantive difference between measurement and knowledge production lies in question ownership (Riggare, Frontiersin.org, 18 August 2026).
Practical implication 1: If your goal is participant-led insight, design consent, data access, and analytic workflows that let participants pose the Questioning phase and participate in Reasoning and Discovering, mirroring the high-agency cases documented in the review (Riggare, Frontiersin.org, 18 Aug 2026).
Practical implication 2: When reusing self-tracked data from low-agency studies, document origin and limits: the review found low-agency work commonly treats people as "sensor platforms" and centralizes analysis with researchers, a pattern that affects interpretability (Riggare, Frontiersin.org, 18 August 2026).
Practical implication 3: Reporting norms should include explicit statements about who formulated the question, who performed analyses, and whether participants were authors, because the review used co-authorship as a practical signal of Discovering-phase agency (Riggare, Frontiersin.org, 18 August 2026).
How Evidano helps researchers preserve and measure epistemic agency
Problem: Participants used as data suppliers without analytic voice
Solution: Use Evidano to ingest transcripts, self-tracking logs, and open-ended survey responses and run thematic and cross-segment analyses so participant-originated questions and interpretations are visible in the analytic output.
Rationale: The Frontiersin.org review identifies low-agency studies by their separation of Questioning and Reasoning; Evidano surfaces participant-authored questions as coded themes and links them to supporting data to demonstrate who owned each phase.
Problem: Manual, slow synthesis of n-of-1 reasoning and mixed qualitative-quantitative logs
Solution: Evidano automates thematic, frequency, and co-occurrence analyses across interview transcripts and time-series logs, and provides visualizations (word clouds, co-occurrence networks, hierarchical codes→subcodes) to accelerate Reasoning.
Rationale: The Frontiersin.org review describes personal science Reasoning as often using spreadsheets and ad hoc tools; Evidano replaces disjointed workflows with reproducible AI-assisted analyses to preserve the individual's analytic choices.
Problem: Need to document who owned the question for publication or ethics review
Solution: Evidano captures provenance metadata and allows you to tag phases of inquiry (Questioning, Observing, Reasoning, Discovering) aligned with the review's framework so you can report agency clearly.
Rationale: According to Riggare (Frontiersin.org, 18 August 2026), co-authorship and explicit description of participant roles were indicators of high agency; Evidano's provenance aids transparent reporting and reproducibility.
Relevant Evidano features and links
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
If you need transcription and PII redaction for participant audio, see Evidano speech-to-text.
If your work includes multilingual participants, Evidano supports translation workflows and custom dictionaries: Evidano translation.
For security and governance details that matter in participant-led research, see Evidano data security.
For a feature overview relevant to agency-preserving workflows, see Evidano features.
FAQ: epistemic agency in self-tracking
What is epistemic agency in self-tracking?
Epistemic agency in self-tracking means the individual does more than supply data: they pose the question, collect the data, analyze it, and articulate discoveries, as defined in the Frontiersin.org review (Riggare, 18 August 2026).
Supporting detail: The review operationalizes this as four phases (Questioning, Observing, Reasoning, Discovering) and classifies articles as low, mixed, or high agency based on who performed each phase.
How can I tell if a self-tracking study is high-agency or low-agency?
Check who formulated the research question and who authored the analysis: the Frontiersin.org review used participant-originated questions and participant co-authorship as indicators of high agency (Riggare, 18 August 2026).
Supporting detail: In high-agency cases described in the review, the person doing the tracking often appears as a co-author and the project reports iterative self-directed methods and individual-focused analysis.
Can AI help preserve participant epistemic agency during analysis?
Yes, AI-enabled qualitative tools can accelerate synthesis while preserving participant voice by indexing transcripts, linking analytic claims to participant-originated data, and producing auditable provenance, a workflow recommended by the Frontiersin.org review for supporting personal science.
Supporting detail: The review highlights the need for infrastructure and documentation to make personal science visible; AI tools like Evidano can automate thematic coding, create reproducible reports, and surface participant-authored questions as first-class artifacts.
Are personal science results generalizable?
Direct answer: Personal science prioritizes actionable self-knowledge over population-level generalization, and the Frontiersin.org review describes it as producing "knowledge-in-the-making" for the individual (Riggare, 18 August 2026).
Supporting detail: The review contrasts personal science with qualitative research aimed at conceptual transfer; personal science mixes subjective context with objective logs to answer the question "what works for me."
Conclusion & Next Steps
The Frontiersin.org review (Sara Riggare, 18 August 2026) shows that quantified self work sits on a continuum from data supply to participant-led knowledge production, and determining "who owns the question" is central to preserving epistemic agency.
Qualitative researchers can adopt the four-phase framework (Questioning, Observing, Reasoning, Discovering) to design consent, analysis, and reporting that make participant agency explicit, as recommended by the review (Riggare, Frontiersin.org, 18 Aug 2026).
If you want to operationalize those recommendations, Evidano can ingest transcripts, self-tracking logs, and survey text, run reproducible thematic and cross-segment analyses, and export provenance-rich reports to document who performed each phase.
Start a trial workflow that preserves participant voice and delivers auditable qualitative outputs: Try Evidano for free.
Topics
- epistemic agency in self-tracking
- personal science qualitative analysis
- quantified self agency
- AI-enabled qualitative research
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