Abstract
This essay conceptualizes the transformation of ethnography in the health field through a three-wave model and systematically maps the methodological and epistemological opportunities that digital health ethnography has produced for health research in the post-2020 period. A hierarchical filtering protocol applied to 964 records retrieved from a Web of Science search on “digital ethnography” yielded a health-specific subset of 74 primary studies, on which bibliometric and thematic analysis was performed. Four distinct fields were identified: (1) patient-led collective knowledge production; (2) digital socialization of health workers; (3) health markets oscillating between the legal and the illegal; and (4) the platformization of the end of life. Eighty-nine percent of the corpus was produced in 2020 or later, suggesting that the COVID-19 pandemic functioned as a methodological catalyst. The central argument is that digital health ethnography is not an auxiliary tool for health management research but a fifth data type—a knowledge layer that must be added alongside administrative, clinical, survey, and epidemiological records.
Keywords: digital ethnography, health management, qualitative research method, patient experience, health policy
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1. Introduction: When the Field Becomes a Flow
Ethnography, whose roots lie in the anthropological tradition of the early twentieth century, has long required the researcher to physically enter a “field,” remain there for extended periods, and grasp local meanings from within through observation and participation (Hammersley & Atkinson, 2019). In health research, this classical template stayed for decades within the walls of hospital wards, operating rooms, nursing homes, and clinical consultations.
Yet over the past fifteen years, the locations where health is produced, shared, and negotiated have shifted decisively. Patient communities now organize in online forums, health workers construct their professional identities on Twitter and TikTok, pharmaceuticals and performance-enhancing substances circulate through cryptomarkets, and even death and grief are performed on the liquid terrain of social media (Chretien et al., 2015; Taylor & Pagliari, 2018; Moeller et al., 2021). The “field” is no longer a single physical site; it is plural, mobile, and hybrid (Pink et al., 2016).
The COVID-19 pandemic accelerated this transformation at unprecedented speed. What had long developed at the margins moved, almost overnight, to the center of health ethnography (Karhapää et al., 2025; Nam et al., 2022). In the post-pandemic period, the digital field has ceased to be a temporary substitute and become a permanent research infrastructure within the platformized ecosystem of health.
Despite this, the literature still lacks a systematic map of digital health ethnography as a research tradition. Methodological reviews tend to draw examples from non-health disciplines (Pink et al., 2016; Hine, 2015), while health-specific studies remain confined to single cases or methodological reflections (Seligmann & Estes, 2020). This essay seeks to fill that gap. It conceptualizes the historical evolution of health ethnography through a three-wave model, maps the four distinctive fields of the third wave on the basis of 74 primary studies, and derives four concrete epistemological opportunities for health management.
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2. A Three-Wave Model of Health Ethnography
The history of health ethnography is not a linear story of progress but the overlapping of three waves that complement, and at times tension, one another. The three-wave model proposed here is not intended to draw sharp boundaries between periods but to make visible the shifts in dominant research questions and ontological assumptions.
2.1 First Wave: Institutional Ethnography (c. 1960s–1990s)
The first wave took the institution itself as its object. Erving Goffman’s observations in psychiatric hospitals and the resulting concept of the total institution; David Sudnow’s (1967) ethnography of death in the hospital; and Anselm Strauss’s theory of the negotiated order in health organizations are the foundational texts of this wave. The researcher entered the ward in a white coat, sat at the nurses’ station, bore witness to the sterilized language of the operating room. The aim was to surface the invisible routines and symbolic orders of institutional practice.
Two defining features mark this wave. First, the field is single-sited: the hospital or clinic is treated as a closed microcosm. Second, the researcher–participant asymmetry is pronounced; the patient is usually the one “studied” rather than the one heard. The approach produced powerful insights into the organizational logic of health services, but it left a second epistemological move necessary to reach the patient’s experience.
2.2 Second Wave: Patient Experience Ethnography (1990s–2010s)
From the 1990s to the early 2010s, the second wave carried the field out of institutional walls and into the patient’s life world. Living with chronic illness, meaning-making in palliative care, disability and social stigma, and power asymmetries in patient–physician encounters became dominant themes (Atkinson et al., 2017). The researcher now went not only to the hospital but also to the patient’s home, support groups, and disease-specific associations. In-depth interviewing, life-history narration, and prolonged participant observation took methodological centre stage.
The fundamental shift was this: the patient was no longer the object of research but a producer of knowledge. The philosophical foundation of patient-centered care was laid here; “patient experience” became a category of data in its own right. Yet the second wave still rested on the assumption of face-to-face interaction—researcher and participant co-present in the same room, in the same temporality. This assumption began to crack with the rise of internet-based patient communities in the mid-2000s.
2.3 Third Wave: Digital and Hybrid Ethnography (2010s onward)
The third wave redefines the field not as a place but as a flow. Christine Hine’s (2000, 2015) virtual ethnography, the digital ethnography synthesis of Sarah Pink and colleagues (2016), and John Postill’s conceptual writings on digital anthropology established the methodological foundations. The field is now multi-sited, mobile, and hybrid: the same participant can be observed simultaneously in a WhatsApp group, on a Facebook page, and in a hospital corridor. A phygital—physical and digital interwoven—conception of the field is the signature of the third wave (Karhapää et al., 2025).
Eighty-nine percent of the 74 studies analyzed in this essay were published in 2020 or later. COVID-19 did not merely accelerate the third wave; it carried it into the mainstream of health ethnography. When face-to-face fieldwork became impossible, digital ethnography moved from substitute to primary method (Nam et al., 2022). In the post-pandemic phase, the digital field has emerged not as a backup but as an original research object: a site in which health information, patient solidarity, drug markets, and professional identities are produced.
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3. Method: How the Map Was Drawn
This essay draws on 964 records retrieved from the Web of Science (WoS) Core Collection using a “digital ethnography” core search, covering articles, reviews, book chapters, and conference proceedings without language restriction. The publication year range observed was 2015–2026. WoS was chosen because its records arrive with interdisciplinary category tags that permit health subfields—Health Care Sciences & Services, Nursing, Psychiatry, Public Health, Substance Abuse, and others—to be cleanly separated.
A four-step hierarchical filter reduced the 964 records to a health-specific subset:
1. WoS category filter — a record with a health-related WoS category in WoS Categories or Research Areas was included. This step alone captured 64 records (86 percent of the final set).
2. Health-journal signature — a record whose journal name carried a health-specific signature (JMIR, Lancet, BMJ, BMC, Social Science & Medicine) and whose content included health terminology.
3. Dense abstract signal — at least one health term in the title or keywords plus at least three health terms in the abstract.
4. Multiple title-term filter — at least two distinct health terms co-occurring in title and keywords.
Generic pandemic-era terms (“pandemic,” “covid”) were deliberately not used as standalone inclusion criteria, since they appear in much of the 2020–2023 ethnographic methodology literature regardless of health relevance. Their unfiltered inclusion would have falsely admitted many non-health methodological reflection pieces.
The filtering produced 74 primary studies, with a total of 619 citations and an average of 8.4 citations per study. These were then subjected to open and axial coding of titles, abstracts, and keywords; recurrent thematic clusters were consolidated into the four “upper fields” presented in Section 4.
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4. Findings: Four Distinctive Fields of Digital Health Ethnography
The four subsections below discuss the third wave’s distinctive research fields through their anchor studies, moving from methodological practice toward conceptual contribution. The fields are not mutually exclusive but observed centers of gravity; a given study may contribute to more than one.
4.1 Field 1 — Patient Communities and Collective Knowledge Production
This field represents the most striking epistemological shift in the corpus. Kempner and Bailey (2019), in Social Science & Medicine, demonstrated that online patient communities produce not only mutual support but actual patient-led research: individuals living with rare diseases conduct collective self-experimentation on their own bodies, opening knowledge spaces that the formal medical apparatus never reaches. This finding unsettles a core assumption of second-wave patient-experience ethnography—that experience belongs to the patient while knowledge production belongs to the expert.
Gonzalez and colleagues (2022), in the Journal of Medical Internet Research, applied a digital-ethnographic lens to thousands of social-media posts by users with urinary tract infections, surfacing symptom dynamics that almost never appear in clinical consultations. The same team’s 2021 work on overactive bladder produced a parallel finding: in urogynecological domains where intimacy and embarrassment are high, the data patients withhold from clinicians but share online can directly enrich clinical decision-making.
Nunes and colleagues (2019), in Health Informatics Journal, ethnographically documented the agency patients and carers develop through medical and self-care technologies in their interactions with physicians. Strand (2022) examined attitudes toward disordered eating in the rock-climbing community, illustrating how digital ethnography can capture normalized risk practices that fall outside conventional disease categories. Wong and colleagues (2025) analyzed bladder-cancer patients’ smoking-cessation struggles on online forums, making visible the gap between clinical advice and lived effort.
The structural contribution of this field is this: the patient is no longer merely a data source but a co-administrator of the digital field. For health management, the implication is that “patient voice” can be operationalized as an empirical category in service design.
4.2 Field 2 — Digital Socialization of Health Workers
The second distinctive field concerns how health professionals construct their professional identities on digital platforms. The anchor study is Chretien and colleagues (2015), published in the Journal of General Internal Medicine, on medical students’ use of Twitter for professional development. More than a decade later, this remains the most-cited study in the corpus (n = 57 citations) and the foundational demonstration that the hidden curriculum of medical socialization is reproduced on digital platforms.
Tso (2022), in JMIR Medical Education, reported on social-media use among medical professionals for diagnosis, consultation, training, and case reporting. The observed shift was a softening of traditional professional hierarchies: the boundary between senior and junior physicians becomes more permeable, and the “case narrative” acquires a faster, publicly available, mutually interpretable form. Han and colleagues (2025), in Perspectives on Medical Education, mapped the sociomaterial flow of peer-led learning in digital spaces, sketching the move in health education from a “syllabus” to a “knowledge ecology.”
A related body of work examines the performative visibility of health workers on platforms such as TikTok. “Lip-Syncing and Saving Lives: Healthcare Workers on TikTok” documents the tension between clinical labour and public entertainment, opening a new empirical site for professional-ethics debate. Paciente and colleagues (2026) extend the same line into the TikTok ecology of transgender care, showing how clinical knowledge and solidarity knowledge become intertwined in patient-facing content.
For health management, the implication is that the digital traces of professional socialization—and therefore of organizational culture—are themselves a systematic observation field.
4.3 Field 3 — Health Markets Between the Legal and the Illegal
The third field hosts the corpus’s most methodologically inventive studies. The International Journal of Drug Policy leads the cluster with five publications. Demant and colleagues (2020) examined the social-media markets for prescription drugs, theorizing platforms as “virtual mortars for drug types and dealers” and showing how distinct platform architectures enable distinct illicit trades. Moeller and colleagues (2021) compared illicit-drug prices and quantity discounts across a cryptomarket, social media, and police data—offering a model for integrating digital ethnography with economic analysis.
Paoli and Cox (2024) mapped the market activities of influencers specialized in steroids and other performance- and image-enhancing drugs along a “spectrum of legality,” proposing that the legal–illegal binary itself needs reframing as a continuum. Cox and Piatkowski (2026a, 2026b) deepened this field through studies of anabolic-steroid coaching certification in India and the normalization of clenbuterol use in digital fitness cultures. Stoli and colleagues (2025), in Social Inclusion, examined DIY pharmaceutical production as a political practice, documenting a new form of health citizenship enacted on the digital field.
The most conceptually surprising contribution to this field is Richterich’s (2020) study in Health Sociology Review. The author ethnographically tracked the open-source DIY production of healthcare equipment during the COVID-19 pandemic—ventilators, protective masks, face shields—and theorized it as critical making. Beyond the legal–illegal duality, this points to an informal health supply chain that citizens claim where the institutional system fails.
For health management, the implication is sharp: wherever policy and regulation lag, informal health markets rise. Digital ethnography can detect such gaps before classical epidemiological surveillance systems pick up the first clinical case.
4.4 Field 4 — The Platformization of the End of Life
The fourth and final field is the most embodied and intimate of digital health ethnography’s subdomains: how death, grief, and end-of-life experience are performed on digital platforms. The anchor study is Taylor and Pagliari’s (2018) “Deathbedlive” in BMC Palliative Care. Tracing the Twitter posts of a dying cancer patient, the authors showed how “live-tweeting the deathbed” reconfigures patient subjectivity, the position of the witness, and the temporality of grief work.
Guo (2026) examined “digital thanatography” on the Chinese platform Douyin (the domestic counterpart of TikTok), showing that the platformized presentation of the dying body transforms grief into a shared performance. Oreg and colleagues (2026) read memorial tattoos through terror-management theory, demonstrating how the digital mediation of loss produces new mnemonic practices in which embodied memory is shared. Thompson and colleagues (2022a, 2022b) expanded the locus of end-of-life care beyond the patient–provider dyad to include family as a co-laboring agent, suggesting that palliative care is no longer a strictly clinical category but a collective digital labour.
For health management, the implications are layered: the design of palliative services, the scope of bereavement programmes, and strategies for managing secondary trauma among health workers can all draw on the new data field produced by patients’ post-mortem digital traces.
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5. Discussion: Four Epistemological Opportunities for Health Management
Mapping these four fields suggests that digital health ethnography is not merely a new data-collection technique but an epistemological doorway for health management. The following four opportunities lie beyond it.
5.1 Operationalizing the Patient Voice
Conventional patient-satisfaction instruments structurally compress experience into pre-defined categories; they cannot capture what is not there, what was never put into words, but was nevertheless lived. As Field 1 shows, digital ethnography can render this off-category knowledge systematically visible. For the health management researcher, this means that patient-experience measurement can be redesigned from a Likert scale into a multi-layered observation-and-synthesis exercise.
Operationalization is possible in three steps: (i) identifying the patient’s natural digital habitats (forums, social-media groups, health platforms); (ii) conducting systematic observation under appropriate ethical approval and participant notification; and (iii) feeding the observational findings back into institutional quality processes—particularly patient-experience indicators—through closed-loop mechanisms.
5.2 Reading the Digital Reflections of Organizational Culture
As Field 2 shows, the way health workers negotiate their professional identities on digital platforms is a mirror of organizational culture. A physician’s case anecdote on Twitter, a nurse’s commentary on a difficult shift on TikTok, a manager’s leadership philosophy on LinkedIn—each of these offers a map of organizational atmosphere that anonymous employee-satisfaction surveys cannot.
The methodological difficulty is also clear: identifying institution-specific digital traces, observing them within ethical boundaries, and interpreting them requires a complex research design. But the approach has unique potential in domains where in-house surveys are typically self-censored: silence cultures, workplace bullying, burnout, and organizational justice.
5.3 Early Detection of Policy Gaps
Field 3 shows that wherever health policy and regulation lag, informal health markets rise. Performance-enhancing drug use, DIY pharmaceuticals, cryptomarket pharmacy, and adolescent influencer-driven cosmetic entrepreneurship are only a few examples. Classical epidemiological surveillance catches such practices only at the point of contact with the health system—usually as side effects, poisonings, or complications. Digital ethnography, by contrast, witnesses such practices in their ordinary state, long before the first clinical case is recorded.
This is a time-buying instrument for health policy. Integrating digital-ethnographic observation with epidemiological surveillance—especially in addiction policy, adolescent health, and public-health emergencies—can yield a substantive structural contribution to early-warning systems.
5.4 Embedding Ethical Reflexivity in Managerial Practice
Perhaps the least-discussed but most consequential contribution of digital health ethnography is that ethical reflexivity is built into the method. The end-of-life sharing observed in Field 4, the rare-disease communities in Field 1, the informal markets in Field 3—each repeatedly reopens the question of “how much may be observed.” Public visibility, expectations of privacy, the continuity of digital consent, and the ethical limits of AI-assisted data collection are core debates of the third wave (Williams, 2025; Davis et al., 2023).
For health management, the implication is that ethics committees and institutional research processes must move from a purely biomedical frame to one that competently addresses the digital field. In the digital era, ethical reflexivity is not an institutional luxury; it is the minimum condition of research governance.
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6. Limitations
Three limitations of this analysis should be acknowledged. First, only the Web of Science Core Collection was used as a data source; Scopus, PubMed, and Turkish academic databases (DergiPark, TR Dizin) could have expanded the thematic clusters. Second, the “digital ethnography” core search does not fully cover adjacent labels such as netnography, online ethnography, or virtual ethnography; some studies at the edges of the third wave may have been excluded. Third, reliance on WoS category assignments for the health filter is a structural weakness: borderline studies—such as those at the intersection of health policy and ethnography—may have been excluded simply because WoS did not tag them under a mainstream health category. Future work should adopt a multi-database protocol with an expanded term dictionary to address these three limitations.
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7. Conclusion: Ethnography as a Fifth Data Type
Ethnography is a research strategy with a seventy-year history in the health field. The three-wave model proposed here shows that this history is not a single trajectory but the overlapping of three ontological shifts: from institution to patient, and from patient to digital ecosystem. The analysis of 74 primary studies has identified the third wave’s four distinctive fields—patient communities and collective knowledge production, the digital socialization of health workers, health markets between the legal and the illegal, and the platformization of the end of life—and from these I have derived four concrete epistemological opportunities for health management.
The article’s central argument can now be stated clearly: digital health ethnography is not an auxiliary method but a fifth data type for health management research. Alongside administrative records (service use), clinical records (medical outcomes), survey records (subjective experience), and epidemiological records (population-level outcomes), it offers a knowledge layer produced by patients and health workers in their own words on the platforms they themselves run. This layer compensates for the structural blind spots of conventional data sources and opens the contemporary ecosystem of health to integrated understanding.
For the Turkish health management literature the implication is two-sided. On the one hand, digital health ethnography offers—alongside the heavily quantitative indicators of accreditation frameworks such as SKS, JCI, and ISQua—a method capable of reading institutional quality along the axis of lived experience. On the other, Türkiye’s rapid public uptake of national digital health applications (e-Nabız, MHRS, Hayat Eve Sığar) provides a uniquely fertile field in which a local research tradition in digital health ethnography can be built. The task before health management researchers, then, is not merely to consume the method but to develop it within their own local practice and contribute findings that the international literature has not yet imagined.
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