Evidence map›Paper›PMID 34898449›Full record

ArticleJMIR mHealth and uHealth2021

An Intelligent Individualized Cardiovascular App for Risk Elimination (iCARE) for Individuals With Coronary Heart Disease: Development and Usability Testing Analysis.

Yuling Chen, Meihua Ji, Ying Wu, Qingyu Wang, Ying Deng, Yong Liu, Fangqin Wu, Mingxuan Liu, Yiqiang Guo, Ziyuan Fu and 1 more

Open access · goldAbstract read
In one paragraph

Article 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 28% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

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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

11 authors at 2 institutions in 1 country.

Yuling Chen *School of Nursing, Capital Medical University, Beijing, China.ORCID 0000-0001-8273-0442
Meihua Ji *School of Nursing, Capital Medical University, Beijing, China.ORCID 0000-0002-9421-6077
Ying WuSchool of Nursing, Capital Medical University, Beijing, China.ORCID 0000-0002-8633-5404
Qingyu WangSchool of Nursing, Capital Medical University, Beijing, China.ORCID 0000-0002-3776-9118
Ying DengSchool of Nursing, Capital Medical University, Beijing, China.ORCID 0000-0003-1204-2753
Yong LiuAlong Technology Inc, Beijing, China.ORCID 0000-0003-3736-7757
Fangqin WuSchool of Nursing, Capital Medical University, Beijing, China.ORCID 0000-0002-0904-2667
Mingxuan LiuSchool of Nursing, Capital Medical University, Beijing, China.ORCID 0000-0003-3691-7315
Yiqiang GuoSchool of Nursing, Capital Medical University, Beijing, China.ORCID 0000-0003-4066-2052
Ziyuan FuSchool of Nursing, Capital Medical University, Beijing, China.ORCID 0000-0001-9242-7834
Xiaoying ZhengThe Asia-Pacific Economic Cooperation Health Science Academy, Peking University, Beijing, China.ORCID 0000-0003-1966-044X
Capital Medical University · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDeath and disability from coronary heart disease (CHD) can be largely reduced by improving risk factor management. However, adhering to evidence-based recommendations is challenging and requires interventions at the level of the patient, provider, and health system.

objectiveThe aim of this study was to develop an Intelligent Individualized Cardiovascular App for Risk Elimination (iCARE) to facilitate adherence to health behaviors and preventive medications, and to test the usability of iCARE.

methodsWe developed iCARE based on a user-centered design approach, which included 4 phases: (1) function design, (2) iterative design, (3) expert inspections and walkthroughs of the prototypes, and (4) usability testing with end users. The usability testing of iCARE included 2 stages: stage I, which included a task analysis and a usability evaluation (January to March 2019) of the iCARE patient app using the modified Health Information Technology Usability Survey (Health-ITUES); and stage II (June 2020), which used the Health-ITUES among end users who used the app for 6 months. The end users were individuals with a confirmed diagnosis of CHD from 2 university-affiliated hospitals in Beijing, China.

resultsiCARE consists of a patient app, a care provider app, and a cloud platform. It has a set of algorithms that trigger tailored feedback and can send individualized interventions based on data from initial assessment and health monitoring via manual entry or wearable devices. For stage I usability testing, 88 hospitalized patients (72% [63/88] male; mean age 60 [SD 9.9] years) with CHD were included in the study. The mean score of the usability testing was 90.1 (interquartile range 83.3-99.0). Among enrolled participants, 90% (79/88) were satisfied with iCARE; 94% (83/88) and 82% (72/88) reported that iCARE was useful and easy to use, respectively. For stage II usability testing, 61 individuals with CHD (85% [52/61] male; mean age 53 [SD 8.2] years) who were from an intervention arm and used iCARE for at least six months were included. The mean total score on usability testing based on the questionnaire was 89.0 (interquartile distance: 77.0-99.5). Among enrolled participants, 89% (54/61) were satisfied with the use of iCARE, 93% (57/61) perceived it as useful, and 70% (43/61) as easy to use.

conclusionsThis study developed an intelligent, individualized, evidence-based, and theory-driven app (iCARE) to improve patients' adherence to health behaviors and medication management. iCARE was identified to be highly acceptable, useful, and easy to use among individuals with a diagnosis of CHD.

trial registrationChinese Clinical Trial Registry ChiCTR-INR-16010242; https://tinyurl.com/2p8bkrew.

Indexed as

Coronary DiseaseMobile ApplicationsWearable Electronic DevicesHumansMaleMiddle AgedUser-Centered DesignUser-Computer Interfacecoronary heart diseasedevelopmenthealth behaviormobile healthsystemusability

Identifiers

PMID34898449
PMCPMC8713096
OpenAlexW4200447731

What OpenQuestion 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 OpenQuestion graph.