Evidence map›Paper›PMID 30409767›Full record

ArticleJMIR mHealth and uHealth2018

Usability Study of Mainstream Wearable Fitness Devices: Feature Analysis and System Usability Scale Evaluation.

Jun Liang, Deqiang Xian, Xingyu Liu, Jing Fu, Xingting Zhang, Buzhou Tang, Jianbo Lei

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 2 pooled it
–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

52 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

7 authors.

Jun LiangIT Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.ORCID http://orcid.org/0000-0002-0551-6706
Deqiang XianSichuan College of Traditional Chinese Medicine, Mianyang, China.ORCID http://orcid.org/0000-0002-3426-1482
Xingyu LiuAffiliated Hospital of Stomatology, Southwest Medical University, Luzhou, China.ORCID http://orcid.org/0000-0001-6597-6336
Jing FuInternational School, Southwest Medical University, Luzhou, China.ORCID http://orcid.org/0000-0001-5616-8791
Xingting ZhangPeking University Third Hospital, Beijing, China.ORCID http://orcid.org/0000-0003-1190-5422
Buzhou TangShenzhen HIT Campus, Harbin Institute of Technology, Shenzhen, China.ORCID http://orcid.org/0000-0003-0271-8246
Jianbo LeiCenter for Medical Informatics, Peking University, Beijing, China.ORCID http://orcid.org/0000-0002-1744-0235

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWearable devices have the potential to promote a healthy lifestyle because of their real-time data monitoring capabilities. However, device usability is a critical factor that determines whether they will be adopted on a large scale. Usability studies on wearable devices are still scarce.

objectiveThis study aims to compare the functions and attributes of seven mainstream wearable devices and to evaluate their usability.

methodsThe wearable devices selected were the Apple Watch, Samsung Gear S, Fitbit Surge, Jawbone Up3, Mi Band, Huawei Honor B2, and Misfit Shine. A mixed method of feature comparison and a System Usability Scale (SUS) evaluation based on 388 participants was applied; the higher the SUS score, the better the usability of the product.

resultsFor features, all devices had step counting, an activity timer, and distance recording functions. The Samsung Gear S had a unique sports track recording feature and the Huawei Honor B2 had a unique wireless earphone. The Apple Watch, Samsung Gear S, Jawbone Up3, and Fitbit Surge could measure heart rate. All the devices were able to monitor sleep, except the Apple Watch. For product characteristics, including attributes such as weight, battery life, price, and 22 functions such as step counting, activity time, activity type identification, sleep monitoring, and expandable new features, we found a very weak negative correlation between the SUS scores and price (r=-.10, P=.03) and devices that support expandable new features (r=-.11, P=.02), and a very weak positive correlation between the SUS scores and devices that support the activity type identification function (r=.11, P=.02). The Huawei Honor B2 received the highest score of mean 67.6 (SD 16.1); the lowest Apple Watch score was only 61.4 (SD 14.7). No significant difference was observed among brands. The SUS score had a moderate positive correlation with the user's experience (length of time the device was used) (r=.32, P<.001); participants in the medical and health care industries gave a significantly higher score (mean 61.1, SD 17.9 vs mean 68.7, SD 14.5, P=.03).

conclusionsThe functions of wearable devices tend to be homogeneous and usability is similar across various brands. Overall, Mi Band had the lowest price and the lightest weight. Misfit Shine had the longest battery life and most functions, and participants in the medical and health care industries had the best evaluation of wearable devices. The perceived usability of mainstream wearable devices is unsatisfactory and customer loyalty is not high. A consumer's SUS rating for a wearable device is related to their personal situation instead of the device brand. Device manufacturers should put more effort into developing innovative functions and improving the usability of their products by integrating more cognitive behavior change techniques.

Indexed as

fitnessfunction comparisonSystem Usability Scaleusabilitywearable devices

Identifiers

PMID30409767
PMCPMC6250954

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LicenceCC BY
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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.