Expert Involvement Predicts mHealth App Downloads: Multivariate Regression Analysis of Urology Apps
Urological mobile medical (mHealth) apps are gaining popularity with both clinicians and patients. mHealth is a rapidly evolving and heterogeneous field, with some urology apps being downloaded over 10,000 times and others not at all. The factors that contribute to medical app downloads have yet to...
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Veröffentlicht in: | JMIR mHealth and uHealth 2016-07, Vol.4 (3), p.e86-e86 |
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Zusammenfassung: | Urological mobile medical (mHealth) apps are gaining popularity with both clinicians and patients. mHealth is a rapidly evolving and heterogeneous field, with some urology apps being downloaded over 10,000 times and others not at all. The factors that contribute to medical app downloads have yet to be identified, including the hypothetical influence of expert involvement in app development.
The objective of our study was to identify predictors of the number of urology app downloads.
We reviewed urology apps available in the Google Play Store and collected publicly available data. Multivariate ordinal logistic regression evaluated the effect of publicly available app variables on the number of apps being downloaded.
Of 129 urology apps eligible for study, only 2 (1.6%) had >10,000 downloads, with half having ≤100 downloads and 4 (3.1%) having none at all. Apps developed with expert urologist involvement (P=.003), optional in-app purchases (P=.01), higher user rating (P |
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ISSN: | 2291-5222 2291-5222 |
DOI: | 10.2196/mhealth.5738 |