Evidence map›Paper›PMID 34081020›Full record

SynthesisJMIR mHealth and uHealth2021

Older Adults' Experiences With Using Wearable Devices: Qualitative Systematic Review and Meta-synthesis.

Kevin Moore, Emma O'Shea, Lorna Kenny, John Barton, Salvatore Tedesco, Marco Sica, Colum Crowe, Antti Alamäki, Joan Condell, Anna Nordström and 1 more

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in JMIR mHealth and uHealth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 132 papers, 12 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
132citing papers in PubMed, 12 pooled it
63.5field-weighted citation impact, top 1% of its field
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

132 citing papers in PubMed, 12 syntheses or guidelines pooled it, 237 citations in OpenAlex.

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  9. Determinants of physical activity in community-dwelling older adults: an umbrella review.The international journal of behavioral nutrition and physical activity · 2023
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72 more citing papers are in PubMed but not listed here.

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

11 authors at 4 institutions in 5 countries.

Kevin MooreCentre for Gerontology and Rehabilitation, University College Cork, Cork, Ireland.ORCID 0000-0003-0712-2222
Emma O'SheaCentre for Gerontology and Rehabilitation, University College Cork, Cork, Ireland.ORCID 0000-0002-1148-0471
Lorna KennyCentre for Gerontology and Rehabilitation, University College Cork, Cork, Ireland.ORCID 0000-0002-5351-3091
John BartonTyndall Institute, Cork, Ireland.ORCID 0000-0002-0671-5678
Salvatore TedescoTyndall Institute, Cork, Ireland.ORCID 0000-0002-7752-2240
Marco SicaTyndall Institute, Cork, Ireland.ORCID 0000-0003-4188-4482
Colum CroweTyndall Institute, Cork, Ireland.ORCID 0000-0002-7479-9922
Antti AlamäkiResearch, Development and Innovation Activities & Physiotherapy Education, Karelia University of Applied Sciences, Karelia, Finland.ORCID 0000-0001-6293-6232
Joan CondellSchool of Computing, Engineering and Intelligent Systems, Faculty of Computing, Engineering and the Built Environment, Ulster University, Coleraine, United Kingdom.ORCID 0000-0002-3517-2182
Anna NordströmDepartment of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.ORCID 0000-0003-3534-456X
Suzanne TimmonsCentre for Gerontology and Rehabilitation, University College Cork, Cork, Ireland.ORCID 0000-0001-7790-9552
University College Cork · IEKarelia University of Applied Sciences · FIUiT The Arctic University of Norway · NOUniversity of Ulster · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOlder adults may use wearable devices for various reasons, ranging from monitoring clinically relevant health metrics or detecting falls to monitoring physical activity. Little is known about how this population engages with wearable devices, and no qualitative synthesis exists to describe their shared experiences with long-term use.

objectiveThis study aims to synthesize qualitative studies of user experience after a multi-day trial with a wearable device to understand user experience and the factors that contribute to the acceptance and use of wearable devices.

methodsWe conducted a systematic search in CINAHL, APA PsycINFO, PubMed, and Embase (2015-2020; English) with fixed search terms relating to older adults and wearable devices. A meta-synthesis methodology was used. We extracted themes from primary studies, identified key concepts, and applied reciprocal and refutational translation techniques; findings were synthesized into third-order interpretations, and finally, a "line-of-argument" was developed. Our overall goal was theory development, higher-level abstraction, and generalizability for making this group of qualitative findings more accessible.

resultsIn total, we reviewed 20 papers; 2 evaluated fall detection devices, 1 tested an ankle-worn step counter, and the remaining 17 tested activity trackers. The duration of wearing ranged from 3 days to 24 months. The views of 349 participants (age: range 51-94 years) were synthesized. Four key concepts were identified and outlined: motivation for device use, user characteristics (openness to engage and functional ability), integration into daily life, and device features. Motivation for device use is intrinsic and extrinsic, encompassing many aspects of the user experience, and appears to be as, if not more, important than the actual device features. To overcome usability barriers, an older adult must be motivated by the useful purpose of the device. A device that serves its intended purpose adds value to the user's life. The user's needs and the support structure around the device-aspects that are often overlooked-seem to play a crucial role in long-term adoption. Our "line-of-argument" model describes how motivation, ease of use, and device purpose determine whether a device is perceived to add value to the user's life, which subsequently predicts whether the device will be integrated into the user's life.

conclusionsThe added value of a wearable device is the resulting balance of motivators (or lack thereof), device features (and their accuracy), ease of use, device purpose, and user experience. The added value contributes to the successful integration of the device into the daily life of the user. Useful device features alone do not lead to continued use. A support structure should be placed around the user to foster motivation, encourage peer engagement, and adapt to the user's preferences.

Indexed as

Fitness TrackersWearable Electronic DevicesAgedAged, 80 and overExerciseHumansMiddle AgedMotivationQualitative Researchacceptanceadherencedigital healthmeta-synthesismobile phoneolder adultqualitative reviewwearable device

Identifiers

PMID34081020
PMCPMC8212622
OpenAlexW3150750468

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.