Evidence map›Paper›PMID 30429116›Full record

ArticleJMIR mHealth and uHealth2018

Mobile Apps for Blood Pressure Monitoring: Systematic Search in App Stores and Content Analysis.

Hussein Jamaladin, Tom H van de Belt, Lianda Ch Luijpers, Falco R de Graaff, Sebastian Jh Bredie, Nel Roeleveld, Marleen Mhj van Gelder

Open access · goldAbstract 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 42 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 3 pooled it
22.6field-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

42 citing papers in PubMed, 3 syntheses or guidelines pooled it, 89 citations in OpenAlex.

  1. Smartphone application-based intervention to lower blood pressure: a systematic review and meta-analysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2025
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  12. A tale of two diseases.Journal of human hypertension · 2023
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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 at 1 institution in 1 country.

Hussein JamaladinDepartment for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, Netherlands.ORCID http://orcid.org/0000-0002-0677-1186
Tom H van de BeltRadboud REshape Innovation Center, Radboud University Medical Center, Nijmegen, Netherlands.ORCID http://orcid.org/0000-0002-5401-8973
Lianda Ch LuijpersDepartment for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, Netherlands.ORCID http://orcid.org/0000-0002-8358-6400
Falco R de GraaffDepartment for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, Netherlands.ORCID http://orcid.org/0000-0002-9652-5199
Sebastian Jh BredieRadboud REshape Innovation Center, Radboud University Medical Center, Nijmegen, Netherlands.ORCID http://orcid.org/0000-0002-6973-7540
Nel RoeleveldDepartment for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, Netherlands.ORCID http://orcid.org/0000-0002-3390-4466
Marleen Mhj van GelderDepartment for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, Netherlands.ORCID http://orcid.org/0000-0003-4853-4434
Radboud University Nijmegen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUsing a mobile app for self-management could make it easier for patients to get insight into their blood pressure patterns. However, little is known about the availability, quality, and features of mobile apps targeting blood pressure.

objectiveThe goal of the research was to determine the availability, functionality, and quality of mobile apps that could be used for blood pressure monitoring purposes.

methodsA systematic app search was performed based on the standards for systematic reviews. We searched the Dutch official app stores for Android and iOS platforms using predefined keywords and included all English and Dutch mobile apps targeting blood pressure. Two independent assessors determined eligibility and quality of the apps using the 5-point Mobile App Rating Scale (MARS). Quality scores of the apps with and without 17 a priori selected characteristics were compared using independent sample t tests.

resultsA total of 184 apps (104 Android, 80 iOS) met the inclusion criteria. The mean overall MARS score was 2.63 (95% CI 2.55-2.71) for Android and 2.64 (95% CI 2.56-2.71) for iOS. The apps Bloeddruk (4.1) and AMICOMED BP (3.6) had the highest quality scores on the Android and iOS platforms, respectively. Of the app characteristics recorded, only pricing, in-app advertisements, and local data storage were not associated with the quality scores. In only 3.8% (7/184) of the apps, involvement of medical experts in its development was mentioned, whereas none of the apps was formally evaluated with results published in a peer-reviewed journal.

conclusionsThis study provides an overview of the best apps currently available in the app stores and important key features for self-management that can be used by health care providers and patients with hypertension to identify a suitable app targeting blood pressure monitoring. However, the majority of the apps targeting blood pressure monitoring were of poor quality. Therefore, it is important to involve medical experts in the developmental stage of health-related mobile apps to improve the quality of these apps.

Indexed as

app reviewhigh blood pressuremHealthmobile appmobile phoneself-management

Identifiers

PMID30429116
PMCPMC6262205
OpenAlexW2838688296

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.