Evidence map›Paper›PMID 31486408›Full record

ArticleJMIR mHealth and uHealth2019

Mobile Apps for the Care Management of Chronic Kidney and End-Stage Renal Diseases: Systematic Search in App Stores and Evaluation.

Abu Bakkar Siddique, Mary Krebs, Sarai Alvarez, Iris Greenspan, Amit Patel, Julianna Kinsolving, Naoru Koizumi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 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

33 citing papers in PubMed, 1 synthesis or guideline 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.

Abu Bakkar Siddique *Schar School of Policy and Government, George Mason University, Arlington, VA, United States.ORCID 0000-0002-9964-7511
Mary Krebs *University of Massachusetts Boston, Boston, MA, United States.ORCID 0000-0002-2919-3323
Sarai Alvarez *Schar School of Policy and Government, George Mason University, Arlington, VA, United States.ORCID 0000-0002-8725-6767
Iris Greenspan *Schar School of Policy and Government, George Mason University, Arlington, VA, United States.ORCID 0000-0002-7318-5582
Amit Patel *University of Massachusetts Boston, Boston, MA, United States.ORCID 0000-0001-9058-6890
Julianna Kinsolving *Schar School of Policy and Government, George Mason University, Arlington, VA, United States.ORCID 0000-0001-6939-7024
Naoru Koizumi *Schar School of Policy and Government, George Mason University, Arlington, VA, United States.ORCID 0000-0001-8722-0898

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNumerous free and low-cost mobile apps for the care management of kidney disease have become available in recent years. Although these appear to be promising tools, they have not been evaluated comparatively based on standard mobile app metrics, and thus, limited evidence is available regarding their efficacy. This study systematically cataloged and assessed mobile apps designed to assist medication compliance and nutrition tracking that are useful to the chronic kidney disease (CKD) and the end-stage renal disease (ESRD) patients who are on dialysis.

objectiveThe objective of this study was to comprehensively evaluate mobile apps used for medication compliance and nutrition tracking for possible use by CKD and ESRD patients.

methodsA systematic review framework was applied to the search, screening, and assessment of apps identified and downloaded from the iOS and Android app stores. We selected apps using 13 relevant search terms, narrowed down based on a set of inclusion and exclusion criteria, and then used the Mobile App Rating Scale (MARS), a widely adopted app evaluation tool to assess the effectiveness of apps. The internal consistency and interrater reliability were tested using Cronbach alpha and interclass correlation coefficients (ICCs), respectively.

resultsThe MARS total score had excellent internal consistency (Cronbach alpha=.90) and a moderate level of interrater reliability (2-way mixed ICC 0.65). Overall, 11 out of the 12 reviewed apps met the minimum acceptable score of 3.0 in MARS rating. The 3 apps with the highest combined scores were My Kidneys, My Health Handbook (MARS=4.68); My Food Coach (MARS=4.48); and National Kidney Foundation Malaysia (MARS=4.20). The study identified 2 general weaknesses in the existing apps: the apps fell short of accommodating advanced interactive features such as providing motivational feedback and promoting family member and caregiver participations in the app utilization.

conclusionsThe MARS rating system performed well in the app evaluation. The 3 highest ranked apps scored consistently high across the 5 dimensions specified in MARS. These apps were developed in collaboration with reputable organizations and field experts, demonstrating the importance of expert guidance in developing medical apps.

Indexed as

HumansInformation ServicesKidney Failure, ChronicMobile ApplicationsRenal Insufficiency, Chronicdigital healthkidney patientmhealthMobile App Rating Scalemobile appsnutrition trackingsystematic assessment

Identifiers

PMID31486408
PMCPMC6753688

What OpenQuestion holds

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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.