Literature DB >> 30353814

Smartphone Applications to Support Sleep Self-Management: Review and Evaluation.

Yong K Choi1, George Demiris2, Shih-Yin Lin1, Sarah J Iribarren1, Carol A Landis1, Hilaire J Thompson1, Susan M McCurry1, Margaret M Heitkemper1, Teresa M Ward1.   

Abstract

STUDY
OBJECTIVES: Mobile health (mHealth) tools such as smartphone applications (apps) have potential to support sleep self-management. The objective of this review was to identify the status of available consumer mHealth apps targeted toward supporting sleep self-management and assess their functionalities.
METHODS: We searched four mobile app stores (iTunes Appstore, Android Google Play, Amazon Appstore, and Microsoft Appstore) using the terms "sleep", "sleep management," "sleep monitoring," and "sleep tracking." Apps were evaluated using the Mobile Application Rating Scale (MARS) and the IMS Institute for Healthcare Informatics functionality scores.
RESULTS: We identified 2,431 potentially relevant apps, of which 73 met inclusion criteria. Most apps were excluded because they were unrelated to sleep self-management, simply provided alarm service, or solely played relaxation sounds in an attempt to improve sleep. The median overall MARS score was 3.1 out of 5, and more than half of apps (42/73, 58%) had a minimum acceptability score of 3.0. The apps had on average 7 functions based on the IMS functionality criteria (range 2 to 11). A record function was present in all apps but only eight had the function to intervene. About half of the apps (33/73, 45%) collected data automatically using embedded sensors, 27 apps allowed the user to manually enter sleep data, and 14 apps supported both types of data recording.
CONCLUSIONS: The findings suggest that few apps meet prespecified criteria for quality, content, and functionality for sleep self-management. Despite the rapid evolution of sleep self-management apps, lack of validation studies is a significant concern that limits the clinical value of these apps.
© 2018 American Academy of Sleep Medicine.

Keywords:  consumer health informatics; mHealth; self-management; sleep

Mesh:

Year:  2018        PMID: 30353814      PMCID: PMC6175783          DOI: 10.5664/jcsm.7396

Source DB:  PubMed          Journal:  J Clin Sleep Med        ISSN: 1550-9389            Impact factor:   4.062


  22 in total

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2.  Weaving the Internet of Sleep: The Future of Patient-Centric Collaborative Sleep Health Management Using Web-Based Platforms.

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4.  Consumer Sleep Technology: An American Academy of Sleep Medicine Position Statement.

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Journal:  J Clin Sleep Med       Date:  2018-05-15       Impact factor: 4.062

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2.  Converting and expanding a mobile support intervention: Focus group and field-testing findings from individuals in active tuberculosis treatment.

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Authors:  Ignacio Perez-Pozuelo; Bing Zhai; Joao Palotti; Raghvendra Mall; Michaël Aupetit; Juan M Garcia-Gomez; Shahrad Taheri; Yu Guan; Luis Fernandez-Luque
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5.  Sensitivity, specificity, and tolerability of the BACTrack Skyn compared to other alcohol monitoring approaches among young adults in a field-based setting.

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7.  Usability Experience of a Personal Sleep Monitoring Device to Self-manage Sleep Among Persons 65 Years or Older With Self-reported Sleep Disturbances.

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8.  Assessment of the Predictive Value of Outpatient Smartphone Videos for Diagnosis of Epileptic Seizures.

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9.  Human-centered approaches that integrate sensor technology across the lifespan: Opportunities and challenges.

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10.  Sleep apps: current limitations and challenges.

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