Evidence map›Paper›PMID 26283290›Full record

SynthesisJournal of medical Internet research2015

Mobile Apps for Bipolar Disorder: A Systematic Review of Features and Content Quality.

Jennifer Nicholas, Mark Erik Larsen, Judith Proudfoot, Helen Christensen

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 194 papers, 21 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
194citing papers in PubMed, 21 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

194 citing papers in PubMed, 21 syntheses or guidelines pooled it.

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  14. Evaluating Commercially Available Mobile Apps for Depression Self-Management.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020
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  15. Digital biomarkers from geolocation data in bipolar disorder and schizophrenia: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2019
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  18. Mobile App-Based Health Promotion Programs: A Systematic Review of the Literature.International journal of environmental research and public health · 2018
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134 more citing papers are in PubMed but not listed here.

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

4 authors.

Jennifer NicholasBlack Dog Institute, University of New South Wales, Sydney, Australia. j.nicholas@blackdog.org.au.ORCID http://orcid.org/0000-0003-1889-1107

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith continued increases in smartphone ownership, researchers and clinicians are investigating the use of this technology to enhance the management of chronic illnesses such as bipolar disorder (BD). Smartphones can be used to deliver interventions and psychoeducation, supplement treatment, and enhance therapeutic reach in BD, as apps are cost-effective, accessible, anonymous, and convenient. While the evidence-based development of BD apps is in its infancy, there has been an explosion of publicly available apps. However, the opportunity for mHealth to assist in the self-management of BD is only feasible if apps are of appropriate quality.

objectiveOur aim was to identify the types of apps currently available for BD in the Google Play and iOS stores and to assess their features and the quality of their content.

methodsA systematic review framework was applied to the search, screening, and assessment of apps. We searched the Australian Google Play and iOS stores for English-language apps developed for people with BD. The comprehensiveness and quality of information was assessed against core psychoeducation principles and current BD treatment guidelines. Management tools were evaluated with reference to the best-practice resources for the specific area. General app features, and privacy and security were also assessed.

resultsOf the 571 apps identified, 82 were included in the review. Of these, 32 apps provided information and the remaining 50 were management tools including screening and assessment (n=10), symptom monitoring (n=35), community support (n=4), and treatment (n=1). Not even a quarter of apps (18/82, 22%) addressed privacy and security by providing a privacy policy. Overall, apps providing information covered a third (4/11, 36%) of the core psychoeducation principles and even fewer (2/13, 15%) best-practice guidelines. Only a third (10/32, 31%) cited their information source. Neither comprehensiveness of psychoeducation information (r=-.11, P=.80) nor adherence to best-practice guidelines (r=-.02, P=.96) were significantly correlated with average user ratings. Symptom monitoring apps generally failed to monitor critical information such as medication (20/35, 57%) and sleep (18/35, 51%), and the majority of self-assessment apps did not use validated screening measures (6/10, 60%).

conclusionsIn general, the content of currently available apps for BD is not in line with practice guidelines or established self-management principles. Apps also fail to provide important information to help users assess their quality, with most lacking source citation and a privacy policy. Therefore, both consumers and clinicians should exercise caution with app selection. While mHealth offers great opportunities for the development of quality evidence-based mobile interventions, new frameworks for mobile mental health research are needed to ensure the timely availability of evidence-based apps to the public.

Indexed as

Bipolar DisorderMobile ApplicationsTelemedicineAustraliaDisease ManagementHumansPatient Education as TopicPrivacySelf CareSmartphonebipolar disordermobile applicationsreviewtelemedicine

Identifiers

PMID26283290
PMCPMC4642376

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.