Evidence map›Paper›PMID 42359589›Full record

ArticleSociology of health & illness2026

How Algorithmic Technologies 'Constitute' the Older Body: A Study of Fall-Detection Wearables.

Geoffrey Mead, Barbara B Neves, Alex Broom

Abstract read
In one paragraph

Article in Sociology of health & illness, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Geoffrey MeadSydney Centre for Healthy Societies, School of Social and Political Sciences, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0003-3908-8225
Barbara B NevesSydney Centre for Healthy Societies, School of Social and Political Sciences, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-4490-4322
Alex BroomSydney Centre for Healthy Societies, School of Social and Political Sciences, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0003-1258-1140

Funding

The University of Sydney
6 · The paper itself

Abstract

The cultural politics of the 'problematic' ageing body have led to a search for solutions in the form of algorithmic technologies. In this article, we look at one problem associated with the ageing body-unintentional falls-and one proposed algorithmic intervention: wearable fall-detection technology. In dialogue with sociologists concerned with the cultural politics of the older body, we aim to understand what contribution this fledgling technology makes to how the older body is 'constituted'. To do this, we examine a sample of datasets containing measurements of individuals' movements and falls (which researchers have made available to train algorithms for use in fall-detection wearables). In contrast to existing attempts to grasp how older users are scripted into technology, which focus on explicit ideas about them, we trace how individual subjects are formatted in these datasets. We find that these individuals become fragmented in the data, rendered into movements abstracted from the bodies that carry them out and the locations in which they take place. The older body is constituted, then, as a risky, deviant set of movements through space, irreducible to its component parts.

Indexed as

Accidental FallsAgingAlgorithmsMonitoring, AmbulatoryWearable Electronic DevicesAgedAged, 80 and overDigital HealthFemaleHumans

Identifiers

PMID42359589
PMCPMC13306533

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.