Evidence map›Paper›PMID 36322112›Full record

ArticleJMIR cardio2022

Characteristics of Smart Health Ecosystems That Support Self-care Among People With Heart Failure: Scoping Review.

Rebecca Nourse, Elton Lobo, Jenna McVicar, Finn Kensing, Sheikh Mohammed Shariful Islam, Lars Kayser, Ralph Maddison

Open access · goldAbstract readScoping Review
In one paragraph

Article in JMIR cardio, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
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 at 2 institutions in 2 countries.

Rebecca NourseInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.ORCID https://orcid.org/0000-0002-6410-7064
Elton LoboInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.ORCID https://orcid.org/0000-0003-0096-6318
Jenna McVicarInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.ORCID https://orcid.org/0000-0001-5007-7223
Finn KensingDepartment of Computer Science, Faculty of Science, University of Copenhagen, Copenhagen, Denmark.ORCID https://orcid.org/0000-0002-1392-5999
Sheikh Mohammed Shariful IslamInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.ORCID https://orcid.org/0000-0001-7926-9368
Lars KayserDepartment of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.ORCID https://orcid.org/0000-0002-0909-4088
Ralph MaddisonInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.ORCID https://orcid.org/0000-0001-8564-5518
Deakin University · AUUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe management of heart failure is complex. Innovative solutions are required to support health care providers and people with heart failure with decision-making and self-care behaviors. In recent years, more sophisticated technologies have enabled new health care models, such as smart health ecosystems. Smart health ecosystems use data collection, intelligent data processing, and communication to support the diagnosis, management, and primary and secondary prevention of chronic conditions. Currently, there is little information on the characteristics of smart health ecosystems for people with heart failure.

objectiveWe aimed to identify and describe the characteristics of smart health ecosystems that support heart failure self-care.

methodsWe conducted a scoping review using the Joanna Briggs Institute methodology. The MEDLINE, Embase, CINAHL, PsycINFO, IEEE Xplore, and ACM Digital Library databases were searched from January 2008 to September 2021. The search strategy focused on identifying articles describing smart health ecosystems that support heart failure self-care. A total of 2 reviewers screened the articles and extracted relevant data from the included full texts.

resultsAfter removing duplicates, 1543 articles were screened, and 34 articles representing 13 interventions were included in this review. To support self-care, the interventions used sensors and questionnaires to collect data and used tailoring methods to provide personalized support. The interventions used a total of 34 behavior change techniques, which were facilitated by a combination of 8 features for people with heart failure: automated feedback, monitoring (integrated and manual input), presentation of data, education, reminders, communication with a health care provider, and psychological support. Furthermore, features to support health care providers included data presentation, alarms, alerts, communication tools, remote care plan modification, and health record integration.

conclusionsThis scoping review identified that there are few reports of smart health ecosystems that support heart failure self-care, and those that have been reported do not provide comprehensive support across all domains of self-care. This review describes the technical and behavioral components of the identified interventions, providing information that can be used as a starting point for designing and testing future smart health ecosystems.

Indexed as

cardiovascular diseasechronic diseasesdigital healthdigital technologyinformation technologymobile phonereviewself-management

Identifiers

PMID36322112
PMCPMC9669885
OpenAlexW4302365074

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.