Evidence map›Paper›PMID 39056309›Full record

ArticleJMIR human factors2024

Investigating Users' Attitudes Toward Automated Smartwatch Cardiac Arrest Detection: Cross-Sectional Survey Study.

Wisse M F van den Beuken, Hans van Schuppen, Derya Demirtas, Vokko P van Halm, Patrick van der Geest, Stephan A Loer, Lothar A Schwarte, Patrick Schober

Abstract read
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Article in JMIR human factors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

8 authors.

Wisse M F van den BeukenDepartment of Anesthesiology, Amsterdam UMC, Amsterdam, Netherlands.ORCID 0000-0001-5156-3004
Hans van SchuppenDepartment of Anesthesiology, Amsterdam UMC, Amsterdam, Netherlands.ORCID 0000-0002-3870-4412
Derya DemirtasCenter for Healthcare Operations Improvement and Research, University of Twente, Enschede, Netherlands.ORCID 0000-0003-4064-484X
Vokko P van HalmDepartment of Cardiology, Amsterdam UMC, Amsterdam, Netherlands.ORCID 0000-0002-2176-6406
Patrick van der GeestAmbulance Rotterdam-Rijnmond, Barendrecht, Netherlands.ORCID 0009-0004-9340-6508
Stephan A LoerDepartment of Anesthesiology, Amsterdam UMC, Amsterdam, Netherlands.ORCID 0000-0002-6375-8359
Lothar A SchwarteDepartment of Anesthesiology, Amsterdam UMC, Amsterdam, Netherlands.ORCID 0000-0001-6119-7810
Patrick SchoberDepartment of Anesthesiology, Amsterdam UMC, Amsterdam, Netherlands.ORCID 0000-0003-0814-081X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality in the developed world. Timely detection of cardiac arrest and prompt activation of emergency medical services (EMS) are essential, yet challenging. Automated cardiac arrest detection using sensor signals from smartwatches has the potential to shorten the interval between cardiac arrest and activation of EMS, thereby increasing the likelihood of survival. Objective: This cross-sectional survey study aims to investigate users' perspectives on aspects of continuous monitoring such as privacy and data protection, as well as other implications, and to collect insights into their attitudes toward the technology. Methods: We conducted a cross-sectional web-based survey in the Netherlands among 2 groups of potential users of automated cardiac arrest technology: consumers who already own a smartwatch and patients at risk of cardiac arrest. Surveys primarily consisted of closed-ended questions with some additional open-ended questions to provide supplementary insight. The quantitative data were analyzed descriptively, and a content analysis of the open-ended questions was conducted. Results: In the consumer group (n=1005), 90.2% (n=906; 95% CI 88.1%-91.9%) of participants expressed an interest in the technology, and 89% (n=1196; 95% CI 87.3%-90.7%) of the patient group (n=1344) showed interest. More than 75% (consumer group: n= 756; patient group: n=1004) of the participants in both groups indicated they were willing to use the technology. The main concerns raised by participants regarding the technology included privacy, data protection, reliability, and accessibility. Conclusions: The vast majority of potential users expressed a strong interest in and positive attitude toward automated cardiac arrest detection using smartwatch technology. However, a number of concerns were identified, which should be addressed in the development and implementation process to optimize acceptance and effectiveness of the technology.

Indexed as

Out-of-Hospital Cardiac ArrestAdultAgedCross-Sectional StudiesEmergency Medical ServicesFemaleHumansMaleMiddle AgedNetherlandsSurveys and QuestionnairesWearable Electronic Devicesacceptanceadoptionattitudeattitudesautomated cardiac arrest detectioncardiaccardiologycross sectionaldigital healthemergencyemergency medicineexperienceexperiencesheartintentintentionopinionout-of-hospital cardiac arrestperceptionperceptionsperspectiveperspectivesquestionnairequestionnairessmartwatchsurveysurveyswearablewearableswillingness

Identifiers

PMID39056309
PMCPMC11292589

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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.