Evidence map›Paper›PMID 30459140›Full record

ArticleJMIR mHealth and uHealth2018

Description of Cardiological Apps From the German App Store: Semiautomated Retrospective App Store Analysis.

Urs-Vito Albrecht, Gerd Hasenfuß, Ute von Jan

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 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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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

12 citing papers in PubMed.

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  10. [Digital medicine].Der Internist · 2019
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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

3 authors.

Urs-Vito Albrecht *Peter L Reichertz Institute for Medical Informatics, Hannover Medical School, Hannover, Germany.ORCID http://orcid.org/0000-0002-8989-6696
Gerd Hasenfuß *Department of Cardiology and Pneumology, University Medical Center Göttingen, Göttingen, Germany.ORCID http://orcid.org/0000-0002-5942-361X
Ute von Jan *Peter L Reichertz Institute for Medical Informatics, Hannover Medical School, Hannover, Germany.ORCID http://orcid.org/0000-0001-9225-593X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the app stores of mobile platforms, consumers are confronted with an enormous number of mobile apps. Over the past few years, considerable research has been undertaken into to identifying, characterizing, and evaluating apps, be it in health-related or other contexts. However, many of these projects are restricted to specific areas of application and offer little flexibility in adapting the applied criteria.

objectiveThis paper presents an adaptable method for selecting and characterizing mobile apps listed in a mobile App Store (the Apple App Store). The method is based on filtering processes using predefined criteria, through a semiautomated retrospective App Store analysis (SARASA).

methodsTo illustrate the SARASA process, keyword-based filtering and metadata-based description, review, and ranking steps were applied to a dataset, more specifically, an April 2018 readout of the Medical category of the German App Store, with the aim of obtaining a list of cardiology-related apps.

resultsFrom the original list of 39,427 apps within the "Medical" category of the App Store on April 14, 2018, 34,382 apps with store descriptions in languages other than German were removed. For the remaining 5045 apps, keywords related to cardiology were applied to filter the output, obtaining a final total of 335 subject-specific apps for further analysis and description.

conclusionsSARASA provides an easy to use method for applying filtering processes to identify apps matching predefined, formal criteria from app stores. The criteria can be well adapted to the needs of users. Automatic and manual analyses are easily combined when using SARASA. In the future, additional features, such as algorithmic topic analyses, may supplement the process. Although the area of application is currently limited to Apple's App Store, expansion to other stores is planned. The method stands or falls with the transparency of the app store providers and the manufacturers to make relevant meta-information available. It is up to them to liberalize information and restrict censorship to provide clients, customers, and users truly fair circumstances finding their way around the app market.

Indexed as

cardiologymHealthmobile appsmobile healthretrospective app store analysis

Identifiers

PMID30459140
PMCPMC6280035

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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.