Evidence map›Paper›PMID 42311843›Full record

ArticleDigital health

Exploring the preference of devices that can measure movement among people who have been hospitalised: A discrete choice experiment.

Eliza Becker, Richard Norman, Carol Watson, Meg Harrold, Kylie Hill

Abstract read
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Article in Digital health. 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
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0citing papers in PubMed
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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

5 authors.

Eliza BeckerCurtin School of Allied Health, Curtin University, Perth, WA, Australia.ORCID https://orcid.org/0000-0002-8817-3533
Richard NormanCurtin School of Population Health, Curtin University, Perth, WA, Australia.
Carol WatsonPhysiotherapy Department, Royal Perth Hospital, Perth, WA, Australia.
Meg HarroldCurtin School of Allied Health, Curtin University, Perth, WA, Australia.
Kylie HillCurtin School of Allied Health, Curtin University, Perth, WA, Australia.ORCID https://orcid.org/0000-0002-6082-6352

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Monitoring bodily movement in people admitted to hospital is important for assessing clinical status and preventing complications associated with immobility. Movement sensor systems offer a mechanism to support human assessment by enabling continuous monitoring. Adoption will depend on consumer values and preferences. Objective: To explore consumer preferences for a hospital-based movement sensor system using a discrete choice experiment (DCE). Design Setting and Participants: A DCE survey evaluating seven attributes (time and complexity to set up, accuracy, sensor type, attachment, reusability and number) was completed by 1,040 health consumers in Perth, Western Australia. Results: Respondents prefer devices that are accurate (only inaccurate 1 in 100 cases versus 1 in 5 cases β = 0.711, p < 0.001) and can be set up quickly (2min versus 15min, β = 0.253, p < 0.001) and independently (versus with support of a professional β = 0.186, p < 0.001). Camera presence in a movement sensor system was less concerning to participants than anticipated. Participants had a small preference for systems without a camera (versus with a camera β = 0.153, p < 0.001) and when a camera was included, had no preference for how footage was displayed to a healthcare professional (identifiable versus non-identifiable footage β = 0.025, p = 0.374). Conclusion and Relevance: Consumers prioritised accuracy and independence and appear indifferent towards the inclusion of a camera in a movement monitoring system. These findings support a hybrid approach integrating wearable sensors with cameras to achieve high precision without compromising acceptance.

Indexed as

consumershospitalmovementsensortechnology

Identifiers

PMID42311843
PMCPMC13269976

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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.