Evidence map›Paper›PMID 32808939›Full record

ArticleJMIR mHealth and uHealth2020

Smartphone and Mobile Health Apps for Tinnitus: Systematic Identification, Analysis, and Assessment.

Muntazir Mehdi, Michael Stach, Constanze Riha, Patrick Neff, Albi Dode, Rüdiger Pryss, Winfried Schlee, Manfred Reichert, Franz J Hauck

Abstract read
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Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 4 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

23 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  12. Quality assessment of mHealth apps: a scoping review.Frontiers in health services · 2024
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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

9 authors.

Muntazir MehdiInstitute of Distributed Systems, Ulm University, Ulm, Germany.ORCID 0000-0003-1083-6808
Michael StachInstitute of Databases and Information Systems, Ulm University, Ulm, Germany.ORCID 0000-0001-9422-5523
Constanze RihaDepartment of Psychology, University of Zurich, Zurich, Switzerland.ORCID 0000-0002-6006-7018
Patrick NeffClinic and Policlinic for Psychiatry and Psychotherapy, Regensburg, Germany.ORCID 0000-0003-3174-4910
Albi DodeInstitute of Databases and Information Systems, Ulm University, Ulm, Germany.ORCID 0000-0003-1840-0056
Rüdiger PryssInstitute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany.ORCID 0000-0003-1522-785X
Winfried SchleeClinic and Policlinic for Psychiatry and Psychotherapy, Regensburg, Germany.ORCID 0000-0001-7942-1788
Manfred ReichertInstitute of Databases and Information Systems, Ulm University, Ulm, Germany.ORCID 0000-0003-2536-4153
Franz J HauckInstitute of Distributed Systems, Ulm University, Ulm, Germany.ORCID 0000-0002-7480-9617

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundModern smartphones contain sophisticated high-end hardware features, offering high computational capabilities at extremely manageable costs and have undoubtedly become an integral part in users' daily life. Additionally, smartphones offer a well-established ecosystem that is easily discoverable and accessible via the marketplaces of differing mobile platforms, thus encouraging the development of many smartphone apps. Such apps are not exclusively used for entertainment purposes but are also commonplace in health care and medical use. A variety of those health and medical apps exist within the context of tinnitus, a phantom sound perception in the absence of any physical external source.

objectiveIn this paper, we shed light on existing smartphone apps addressing tinnitus by providing an up-to-date overview.

methodsBased on PRISMA guidelines, we systematically searched and identified existing smartphone apps on the most prominent app markets, namely Google Play Store and Apple App Store. In addition, we applied the Mobile App Rating Scale (MARS) to evaluate and assess the apps in terms of their general quality and in-depth user experience.

resultsOur systematic search and screening of smartphone apps yielded a total of 34 apps (34 Android apps, 26 iOS apps). The mean MARS scores (out of 5) ranged between 2.65-4.60. The Tinnitus Peace smartphone app had the lowest score (mean 2.65, SD 0.20), and Sanvello-Stress and Anxiety Help had the highest MARS score (mean 4.60, SD 0.10). The interrater agreement was substantial (Fleiss κ=0.74), the internal consistency was excellent (Cronbach α=.95), and the interrater reliability was found to be both high and excellent-Guttman λ6=0.94 and intraclass correlation, ICC(2,k) 0.94 (95% CI 0.91-0.97), respectively.

conclusionsThis work demonstrated that there exists a plethora of smartphone apps for tinnitus. All of the apps received MARS scores higher than 2, suggesting that they all have some technical functional value. However, nearly all identified apps were lacking in terms of scientific evidence, suggesting the need for stringent clinical validation of smartphone apps in future. To the best of our knowledge, this work is the first to systematically identify and evaluate smartphone apps within the context of tinnitus.

Indexed as

Acceptance and Commitment TherapyMobile ApplicationsSmartphoneTelemedicineTinnitusEcosystemHumansReproducibility of ResultsApp Quality Assessment and EvaluationHealth careMARSMobile AppsMobile HealthSmartphone AppsTinnitus

Identifiers

PMID32808939
PMCPMC7463412

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.