Description
Consumer mobile health applications (mHealth apps) have potential to improve patient outcomes and increase access to support, but a systematic review on the quality and functionality of apps for depression has not been completed. The purpose of this review was to examine the quality of consumer-oriented mobile apps targeting individuals living with depression using a standardized methodology. We completed a systematic review of mobile apps for depression self-management by entering six relevant search terms in the Apple, Android, and Amazon app marketplaces. We selected apps using four rounds of ad hoc inclusion and exclusion criteria. Of 1198 potentially relevant apps searched, 31 apps met inclusion criteria. Mobile health apps for depression exhibit a wide range of quality, but more than half of the apps included in this review had acceptable quality. The MARS scores correlated with IMS Functionality Scores, but not with the amount of available features for depression self-management. The high scoring apps found in this review show that mobile health interventions can potentially increase access to support, help manage symptoms of depression, and improve quality of life.
Learning Objective: After participating in this session, the learner should be better able to:
Understand the current state of consumer oriented mobile apps for depression.
Understand what kind of apps are available right now and the features associated with high quality apps.
Formulate an approach to searching for and selecting appropriate mobile apps for depression.
Authors:
Lewis Chesebrough (Presenter)
Weill Cornell Graduate School of Medical Sciences
Annie Myers, Weill Cornell Graduate School of Medical Sciences
Lingchen Lou, Weill Cornell Graduate School of Medical Sciences
Ruixuan Hu, Weill Cornell Graduate School of Medical Sciences
Meghan Reading Turchioe, Weill Cornell Graduate School of Medical Sciences
Ruth Creber, Weill Cornell Graduate School of Medical Sciences
Presentation Materials: