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dc.contributor.authorSingh, Karandeep
dc.contributor.authorDrouin, Kaitlin
dc.contributor.authorNewmark, Lisa P.
dc.contributor.authorFilkins, Malina
dc.contributor.authorSilvers, Elizabeth
dc.contributor.authorBain, Paul A.
dc.contributor.authorZulman, Donna M.
dc.contributor.authorLee, Jae-Ho
dc.contributor.authorRozenblum, Ronen
dc.contributor.authorPabo, Erika
dc.contributor.authorLandman, Adam
dc.contributor.authorKlinger, Elissa V.
dc.contributor.authorBates, David W.
dc.date2022-08-11T08:09:46.000
dc.date.accessioned2022-08-23T16:43:06Z
dc.date.available2022-08-23T16:43:06Z
dc.date.issued2016-12-19
dc.date.submitted2017-05-16
dc.identifier.citationJMIR Mhealth Uhealth. 2016 Dec 19;4(4):e136. <a href="https://doi.org/10.2196/mhealth.6445">Link to article on publisher's site</a>
dc.identifier.issn2291-5222 (Linking)
dc.identifier.doi10.2196/mhealth.6445
dc.identifier.pmid27993761
dc.identifier.urihttp://hdl.handle.net/20.500.14038/40225
dc.description.abstractBACKGROUND: Self-management is essential to caring for high-need, high-cost (HNHC) populations. Advances in mobile phone technology coupled with increased availability and adoption of health-focused mobile apps have made self-management more achievable, but the extent and quality of the literature supporting their use is not well defined. OBJECTIVE: The purpose of this review was to assess the breadth, quality, bias, and types of outcomes measured in the literature supporting the use of apps targeting HNHC populations. METHODS: Data sources included articles in PubMed and MEDLINE (National Center for Biotechnology Information), EMBASE (Elsevier), the Cochrane Central Register of Controlled Trials (EBSCO), Web of Science (Thomson Reuters), and the NTIS (National Technical Information Service) Bibliographic Database (EBSCO) published since 2008. We selected studies involving use of patient-facing iOS or Android mobile health apps. Extraction was performed by 1 reviewer; 40 randomly selected articles were evaluated by 2 reviewers to assess agreement. RESULTS: Our final analysis included 175 studies. The populations most commonly targeted by apps included patients with obesity, physical handicaps, diabetes, older age, and dementia. Only 30.3% (53/175) of the apps studied in the reviewed literature were identifiable and available to the public through app stores. Many of the studies were cross-sectional analyses (42.9%, 75/175), small (median number of participants=31, interquartile range 11.0-207.2, maximum 11,690), or performed by an app's developers (61.1%, 107/175). Of the 175 studies, only 36 (20.6%, 36/175) studies evaluated a clinical outcome. CONCLUSIONS: Most apps described in the literature could not be located on the iOS or Android app stores, and existing research does not robustly evaluate the potential of mobile apps. Whereas apps may be useful in patients with chronic conditions, data do not support this yet. Although we had 2-3 reviewers to screen and assess abstract eligibility, only 1 reviewer abstracted the data. This is one limitation of our study. With respect to the 40 articles (22.9%, 40/175) that were assigned to 2 reviewers (of which 3 articles were excluded), inter-rater agreement was significant on the majority of items (17 of 30) but fair-to-moderate on others.
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=27993761&dopt=Abstract">Link to Article in PubMed</a>
dc.rights© Karandeep Singh, Kaitlin Drouin, Lisa P Newmark, Malina Filkins, Elizabeth Silvers, Paul A Bain, Donna M Zulman, Jae-Ho Lee, Ronen Rozenblum, Erika Pabo, Adam Landman, Elissa V Klinger, David W Bates. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. JMIR Mhealth Uhealth. 2016 Dec 19;4(4):e136. <a href="https://doi.org/10.2196/mhealth.6445">Link to article on publisher's site</a>
dc.subjectchronic disease
dc.subjectmHealth
dc.subjectmobile apps
dc.subjectreview
dc.subjectself-management
dc.subjectHealth Services Administration
dc.subjectTelemedicine
dc.titlePatient-Facing Mobile Apps to Treat High-Need, High-Cost Populations: A Scoping Review
dc.typeJournal Article
dc.source.journaltitleJMIR mHealth and uHealth
dc.source.volume4
dc.source.issue4
dc.identifier.legacyfulltexthttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=4024&amp;context=oapubs&amp;unstamped=1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/oapubs/3019
dc.identifier.contextkey10171425
refterms.dateFOA2022-08-23T16:43:07Z
html.description.abstract<p>BACKGROUND: Self-management is essential to caring for high-need, high-cost (HNHC) populations. Advances in mobile phone technology coupled with increased availability and adoption of health-focused mobile apps have made self-management more achievable, but the extent and quality of the literature supporting their use is not well defined.</p> <p>OBJECTIVE: The purpose of this review was to assess the breadth, quality, bias, and types of outcomes measured in the literature supporting the use of apps targeting HNHC populations.</p> <p>METHODS: Data sources included articles in PubMed and MEDLINE (National Center for Biotechnology Information), EMBASE (Elsevier), the Cochrane Central Register of Controlled Trials (EBSCO), Web of Science (Thomson Reuters), and the NTIS (National Technical Information Service) Bibliographic Database (EBSCO) published since 2008. We selected studies involving use of patient-facing iOS or Android mobile health apps. Extraction was performed by 1 reviewer; 40 randomly selected articles were evaluated by 2 reviewers to assess agreement.</p> <p>RESULTS: Our final analysis included 175 studies. The populations most commonly targeted by apps included patients with obesity, physical handicaps, diabetes, older age, and dementia. Only 30.3% (53/175) of the apps studied in the reviewed literature were identifiable and available to the public through app stores. Many of the studies were cross-sectional analyses (42.9%, 75/175), small (median number of participants=31, interquartile range 11.0-207.2, maximum 11,690), or performed by an app's developers (61.1%, 107/175). Of the 175 studies, only 36 (20.6%, 36/175) studies evaluated a clinical outcome.</p> <p>CONCLUSIONS: Most apps described in the literature could not be located on the iOS or Android app stores, and existing research does not robustly evaluate the potential of mobile apps. Whereas apps may be useful in patients with chronic conditions, data do not support this yet. Although we had 2-3 reviewers to screen and assess abstract eligibility, only 1 reviewer abstracted the data. This is one limitation of our study. With respect to the 40 articles (22.9%, 40/175) that were assigned to 2 reviewers (of which 3 articles were excluded), inter-rater agreement was significant on the majority of items (17 of 30) but fair-to-moderate on others.</p>
dc.identifier.submissionpathoapubs/3019
dc.contributor.departmentSchool of Medicine
dc.source.pagese136


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