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This paper explores how genomic screening researchers redefine diagnostic uncertainty as prospective informativity, reshaping the aims and practices of population screening. I argue that the “meantime” of uncertain genomic information is here reconstituted as an argument for advancing screening.

Paper long abstract

Population screening programmes are notoriously susceptible to uncertain outcomes. Classic scholarship describes how screening unsettles diagnostic categories, producing “patients-in-waiting” suspended in a liminal space between disease and health (Timmermans and Buchbinder 2010). Where an extensive critical literature has explored the reoccurrence and consequences of diagnostic uncertainty in screening (Gillespie 2015; Gaspar et al 2020; Pienaar and Petersen 2021), this paper takes an alternative approach, examining how an influential group of genomics experts are redefining diagnostic uncertainty as prospective informativity. Drawing on interviews with leaders of a US-based genomic population screening initiative, and an analysis of guidance published by the American College of Medical Genetics and the Centers for Disease Control, I describe how experts are recharacterizing uncertain and negative genomic findings as eventual health insights, situating present-day genomic information as necessarily unstable and subject to revision. I argue that this anticipated future informativity structures genomic screening research in three ways: first, by demanding the adaptability of screening pipelines, such that targeted genomic variants can be updated and expanded; second, by transforming the communication of screening results, such that a nonfinding is re-articulated as not currently informative; and third, by encouraging primary care providers to view genomic information as routinely and progressively useful. By elucidating how the unstable nature of genomic knowledge is proactively and positively anticipated, I demonstrate how genomic screening researchers reframe the “meantime” of uncertain data as argument for advancing screening. I conclude by discussing the consequences of this reframing for patients and for public health.

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Genomic medicine often produces uncertain results whose clinical meaning remains unresolved. Drawing on an ethnography of medical genetics in India, this paper examines how clinicians manage such data, sustaining possibilities of diagnosis through practices of waiting, reinterpretation, and care.

Paper long abstract

Genomic medicine is often framed as a data-driven revolution promising precise diagnosis and personalised care. Yet in everyday clinical practice, genomic data frequently generate uncertainties by producing results whose clinical significance remains unclear or provisional. A large proportion of genetic tests produce Variants of Uncertain Significance (VUS), findings whose clinical significance cannot yet be confidently classified as either pathogenic or benign. Rather than delivering definite answers, these results place clinicians, laboratory scientists, and families in a suspended reality of prolonged waiting.

In Indian clinical settings, this uncertainty is intensified by structural conditions shaping genomic knowledge production in the region. Global genomic databases on which variant interpretation heavily relies remain disproportionately populated with Euro-American genomic data, while South Asian populations are significantly underrepresented. As a result, clinicians and laboratory scientists frequently encounter variants whose significance cannot be determined using existing reference datasets.

Drawing on a multi-sited ethnographic fieldwork in clinical genetics laboratories, medical conferences and hospitals in India, this paper examines how uncertain genomic variants are managed within the everyday practice of genomic medicine. By approaching VUS not simply as gaps in knowledge but as forms of data held in the “meantime”, this paper attempts to make sense of clinical decision-making in contexts where genomic evidence remains provisional and open to future reinterpretation.

Keywords: Uncertainty, VUS, genomic medicine, suspended time

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This presentation examines data breach victims’ experiences through a digital hauntology lens. The victims are bound to ‘data meantimes’ as their data may circulate online indefinitely, and waiting for new harms and crimes is key to their enduring suffering.

Paper long abstract

This presentation draws upon a study that examines the experiences of data breach victims through a lens provided by the digital hauntology framework. The private psychotherapy provider Vastaamo’s database was the target of a data breach, with the leak of both personal identification information and notes from therapy sessions. While the leak was in many ways a result of the datafication of health care, the platformisation of psychotherapy – the business model of Vastaamo relied on a digital platform – enabled this breach to occur on a massive scale. From the victims’ viewpoint, data generated in the past may continue to haunt the victims in future. I discuss and analyse the leaked data, in all their liveliness and with their own multitemporal (after)lives, as both haunted and haunting. The data consist of anonymous written stories by victims (N=100). The breach left victims more vulnerable to new harms and injuries, especially since their personal information having been made accessible on the dark web. Thus, the danger cannot be said to be over, and the victims are bound to ‘data meantimes’ as their data is potentially endlessly circulating, and waiting for new harms and crimes is key to their enduring suffering. The victims’ stories speak of the uncanny intimacies generated by displaced and misplaced data and the various modes of (in)attention in data-driven health care. Data assumed to be privatised and fossilised has been made widely available, holding open not only their multitemporal (after)lives but also the future horizons of the victims.

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AI in healthcare is widely promised to transform clinical work, yet systems often break. Based on an ethnography of speech recognition, we analyze how AI systems are kept in a state where imaginaries of a future “under repair” stabilize a present “beyond repair,” leaving staff to absorb errors.

Paper long abstract

The promise of data and automation in healthcare is unbroken (Watson & Wozniak‐O’Connor, 2025). At the same time, we know that, in practice, automated, data-intensive systems constantly break, requiring extra care that most often goes unnoticed (Hertzum et al., 2025; Hoeyer, 2023). This paper examines the dynamic interplay between future-oriented promises about AI and the precarious maintenance of AI systems in the present, focusing on automatic speech recognition (ASR) in Danish hospitals. Based on an ethnographic study of both IT managers and frontline workers, we analyze a peculiar state in which, on the managerial level, current issues with ASR are neglected while deferring their ‘solution’ to future upgrades of those systems. At the same time, this leaves healthcare staff to absorb system shortcomings as clinicians internalize errors and secretaries become data validators.

We theorize this state as “meantime maintenance”. In doing so, we bridge scholarship on data work and maintenance (Bossen et al., 2019; Denis & Pontille, 2025) with the sociology of expectations (Borup et al., 2006) to analyze how digital systems are kept in a state where imaginaries of a future “under repair” stabilize a present “beyond repair.” While “meantime” has been described as a space of indeterminate possibility (Masquelier & Durham, 2023), our findings suggest that in contemporary healthcare data infrastructures, it is tightly structured by future-oriented regimes. Prospective efficiency narratives function as governance devices: expectations of imminent technological improvement stabilize present shortcomings, defer accountability, and redirect organizational attention away from maintenance needs in the here and now.

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Automated pain assessment systems use machine learning to infer pain from behavioural and biometric proxies. Based on an ethnography of APA, this paper shows how chronic pain emerges as a constitutive problem for this field, revealing the data practices that sustain the promises of computable pain.

Paper long abstract

Recent advances in machine learning have produced a striking promise in digital health: that pain, long treated as an irreducibly subjective experience, might be detected and quantified through biometric proxies. Automated pain assessment (APA) systems analyse facial micro-expressions, behavioural cues, and physiological signals with machine learning models to generate algorithmic pain indicators. These systems promise objective, data-driven pain measurement and form part of a growing frontier of automated pain management (Lipp and Hilgartner 2025).

This paper examines how this promise is assembled in practice despite the absence of a stable ground truth for pain. Clinical pain assessment continues to rely on patients’ subjective reports on numeric rating scales, which paradoxically also serve as training labels for machine learning models designed to detect pain without relying on self-report. Drawing on ethnography within APA research settings, mapping the field’s emergence, and historical analysis of pain measurement technologies (Tousignant 2011), the paper treats APA as an epistemic community (Knorr-Cetina 1999) organised around shared methodological problems in rendering pain computable and negotiating what counts as valid datafication.

Across these sites, the temporal unruliness of chronic pain emerges as a central application challenge for APA systems. Its fluctuating trajectories and shifting behavioural expressions disrupt the experimentally bounded temporal conditions required for algorithmic recognition. Attending to these tensions, the paper responds to this panel’s invitation by examining APA as a project of data work in the meantime, sustained through provisional proxies and experimental adjustments that keep the possibility of computable pain open (Ruckenstein and Trifuljesko 2022).

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This paper explores the overlapping temporalities involved in home-based clinical trials for paediatric rare disease. It employs the meantime to make visible relational complexities around data and care, and opens up questions around trial ethics, participation and responsibility.

Paper long abstract

This paper explores the multiple and overlapping temporalities of data and care practices in the context of home-based clinical trials for paediatric rare disease. Trial temporalities are oriented towards improving care for future patients through forming better understandings of a condition, trialling new interventions, or piloting technologies for further data production in the home. Participants’ temporalities revolve around the demands of trail participation, the rhythms of everyday life, and the ongoing management of a rare disease. Drawing from an ethnography of home-based trials and paediatric rare disease, this paper employs the ‘meantime’ to apprehend the entanglements between these distinct yet co-existing temporalities. The episodic nature of a trial protocol (eligibility screening; consent and enrolment; site visits; at-home measurements; follow-up) is juxtaposed with practices that are fundamental for the participants but peripheral to the trial: daily negotiations of a rare disease, worries of future deterioration, and hopes for possible treatments. In a meantime between the commencement of the trial and a time when the trial’s benefits might be realised for others, families do their own sense-making of data produced during their child’s trial participation, sometimes incorporating this data into the ways they navigate disease and provide care. The meantime makes visible nuances and complexities that may not have been apparent within other temporal understandings. In doing so, the meantime opens up important questions around the temporal limits of a trial, the ways in which a trial can seep into daily life, research ethics, and the responsibility of trialists around patient care.

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This ethnography follows nurses who transition from bedside to remote digital care at the home monitoring centre of a Dutch hospital. Working within an emergent profession, we trace the data work they perform to co-construct the promise of distant and digital healthcare.

Paper long abstract

Digitalising care and providing care at a distance are often presented as means towards a more efficient healthcare system in the face of looming workforce shortages. However, empirical work shows that a digital transition of care is a complex, open-ended process involving shifting responsibilities, new modes of working, changing professional identities and evolving relationships between actors (Moore et al., 2023). Between the aspirational digital future and the actual, laborious reorganisation of healthcare systems arise professionals ‘in the making’, filling the (technological) gaps.

Through interviews and ethnographic observations at the home monitoring centre of a Dutch hospital, we trace the reorganization of care surrounding nurses who monitor chronic patients at a distance. Previously working at the bedside, the materiality of care changed from hands-on labour to remote computer work based on quantified metrics of health and illness. In the absence of interoperable computer systems or a clearly delineated job description, telenurses - additionally tasked with the expansion of the centre - must continuously improvise.

Our analysis focuses on the ‘meantime’ practices these nurses engage in as they fundamentally reconfigure their profession, including digital repair work and affective telecommunication to ensure patients feel ‘close’ while dealing with a technologically-mediated distance. We show how they are building and mending the unstable in-between of new technogeographies and responsibilities. Situating our findings in the theoretical notions of data work and data promises (Hoeyer, 2019; 2023), we illustrate how remote care is enacted in the open space of a profession under construction.

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Menstrual cycle tracking apps show how the promises of data-driven healthcare unfold in the meantime. Ethnography reveals how researchers, designers and users navigate messy, incomplete datasets, shaping possible outcomes through everyday data practices such as cleaning, storing, and classifying.

Paper long abstract

Menstrual cycle tracking apps (MCTAs) have become everyday technologies in the lives of millions, placing private digital technoservices at the center of contemporary women’s health innovation. Promoted by developers as tools for democratizing gynecological knowledge through self-tracking and data science, MCTAs are embedded in promissory narratives of data-driven healthcare.

Our research began with a seemingly straightforward question: how do MCTAs contribute to the production of knowledge? Through an ethnography of menstrual data infrastructures, focusing on invisible forms of data work—such as cleaning, maintenance, and interpretation—this inquiry evolved into an STS-informed analysis of the co-production of apps and scientific knowledge as an ongoing process rather than a stabilized outcome. This shift highlights the heterogeneous assemblage of actors—human and non-human—through which knowledge is produced, including academic researchers, designers, algorithms, datasets, and users whose everyday practices sustain data systems that remain perpetually incomplete.

This presentation examines how MCTAs function as sociotechnical infrastructures mediating the production of knowledge about women’s health in real time. We draw on interviews with academic researchers and in-house scientists whose work relies on proprietary MCTA datasets (n = 31), as well as interviews with MCTA designers (n = 23). Rather than focusing on the outcomes of their work, we emphasize the gap between the promised futures of personalized care through data science and the unfinished realities of everyday practices, where scientists navigate data that is “useful,” “messy,” “non-existent,” “incomplete,” or “broken.”

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“Pilotitis” is a state of being stuck in ceaseless preparation, implying a meantime that is provisional and instrumental. Ethnographic investigation of digital health and care innovation in Scotland reveals the meantime as a teeming space where local realities intercept a national imaginary.

Paper long abstract

Digital health and care innovation in Scotland is characterised by an ecosystem of public, private, and third sector organisations pursuing powerful data imaginaries: Scotland’s Digital Health and Care Strategy envisions seamless interaction across services in a system where citizens have access to and control over their data, where staff can access and share information system-wide, and where data-driven service-design increases efficiency. Those frustrated at the pace of progress towards this future have diagnosed the sector as being in a state of “pilotitis”, where promising smaller-scale initiatives are piloted but not rolled-out and scaled-up nationally.

By setting the present only against this idealised future, the accusation of “pilotitis” consigns much innovation work to a meantime that is deemed partial and provisional because it is not national. Yet ethnographic investigation of that work suggests that it is exactly within this meantime – or, indeed, these meantimes – that there is space and time to attend carefully to Scotland’s multiple local needs and affordances, and to undertake the kinds of participatory design work that fulfil the ‘person-centred’ vision of its Digital Health and Care Strategy.

Thus tensions are exposed between local meantimes and the national meantime, the plural and the singular, meantimes as they unfold and the future as it is imagined; and “pilotitis” (in its assumption that small-scale work is merely preparatory) emerges as a misapprehension. Local projects have value beyond their instrumentality in relation to the national future, and raise questions about what (if anything) is to be rolled-out or scaled-up.

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The European Health Data Space imagines a future where medical prescriptions will be redeemable across Europe with ease. Where do patients’ meantime practices fit in imaginaries of the future?

Paper long abstract

By 2029 the 450m+ citizens of the European Union (EU) and European Economic Area (EEA) are supposed to be able to redeem their electronic prescriptions in any EU or EEA member state—at least that is the future imagined by the European Health Data Space (EHDS), a landmark EU legislation which entered into force in 2025.

Three years to go we are today in the meantime of the EHDS, its promises “neither fully realized nor fully speculative” (Montgomery et al., 2026). Some countries, notably Finland and Estonia, have been offering interoperable prescriptions for over half a decade. Meanwhile, Germany was one of the last countries to roll out electronic prescriptions domestically in 2024 and is yet to implement interoperability with its European peers.

The EHDS promises one prescription redeemable across all its member countries, envisioning pharmacy visits abroad as frictionless and mundane as those at home. Yet these kinds of imaginaries are hardly a substitute for the medications sought out—today—by the mobile European citizenry. Thus, while waiting for the cross-border electronic prescriptions to materialize, patients utilize a myriad of other means to acquire medications (from) abroad; means that often demand additional labour from their prescribers and pharmacists. In this paper, we explore the tension between, on the one hand, the imaginaries of easily accessible medications and, on the other hand, the arguably more laboursome meantime practices patients engage in. In other words, a tension between the possible and desirable, the present and future, the meantime and the imaginary.

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This paper traces how a German care innovation project mobilizes 'lighthouse' imaginaries to guide data-driven futures. Based on ethnographic fieldwork, we argue that practices of active waiting reveal different 'meantimes', making the lighthouse meaningful for some, invisible for others.

Paper long abstract

How do ‘lighthouse’ imaginaries illuminate – and obscure – care futures in the meantime, and who gets to be represented in their beam? Based on ethnographic fieldwork in a large-scale health and elderly care digitalization project, we investigate the multi-layered meanings and ‘meantimes’ of healthcare data practices. The project is situated in Saxony-Anhalt, Germany, a former coal-mining, and GDR region facing a severe care crisis. As part of ‘structural transformation’ initiatives, the project supports start-ups and research groups to co-create technological innovations and data-driven care ‘solutions’ with elderly citizens, scientists, developers, and policymakers. It aims to develop scalable solutions, transforming the region from a crisis site into a future care model.

A central image used to explain and market the project to the public is the lighthouse, which works as temporal and spatial metaphor. Digital tools and data collected in the present shine their light into a nearby future, but also to other regions experiencing similar care crises. However, the lighthouse works temporally in multiple directions: it reframes past hardships as capacity for transformation while shining from an imagined future onto present practices. Yet it remains unclear whose data, experiences, and imaginaries are included in the lighthouse’s beam. In our paper, we analyse how participants’ active waiting for a bright future takes different forms like experimenting with data-driven tools or navigating aging itself. We argue that the divergent temporalities inherent in these practices point to different meantimes altogether, affecting whether and for whom the lighthouse appears real or remains invisible.

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This paper uses Care Opinion as a case to explore how online patient feedback platforms reshape past experiences of care to stabilise possible healthcare futures. It unpacks the platform’s data practices, highlighting them as ‘meantime practices’ used to craft new chronologies for episodes of care.

Paper long abstract

Online platforms are prevalent in many arenas of life, promising to speed up sociality by compressing the space-time dimensions of interactions using the internet. This includes healthcare, with online patient feedback platforms such as Care Opinion (CO) coupling free-text ‘stories’ of care with datapoints – a “classifying, sorting, slotting, and scaling” practice designed to create effective and timely dialogues between citizen and healthcare service (Fourcade 2021, p.161). In this paper, I build on the argument that platforms use tools to reconfigure relations (Plantin et al. 2018), employing a temporal lens to study CO’s management of multiple coexisting temporalities related to an experience of care. Through interviews with CO staff and story authors, alongside participant-observation, I explore how CO manages multiple forms of ‘meantime’ using techniques such as story tagging, response tracking, and the assignment of ‘criticality scores’ (Masquelier and Durham 2023). High-criticality stories beget longer publication timescales to account for uncertainties – including whether the story relates to a formal complaint. This provides space for the construction of future imaginaries as CO staff attempt to map out possible trajectories of a story following publishing, contrasting with the uniform 5-stage timeline presented to story authors, starting from ‘waiting to be published’ through to ‘change made’ in the linked healthcare service. This contrast foregrounds the chronological politics of CO stories (Tonkin 1992), centring a “routinization of waiting” that attempts to stabilise possible healthcare futures by reshaping past care experiences (Masquelier and Durham 2023, p.9).

Keywords: platforms, healthcare feedback, temporalities, care, experience