Literature DB >> 33595441

Framework for the Design Engineering and Clinical Implementation and Evaluation of mHealth Apps for Sleep Disturbance: Systematic Review.

Melissa Aji1, Christopher Gordon2,3, Elizabeth Stratton1, Rafael A Calvo4, Delwyn Bartlett1,2, Ronald Grunstein2,5, Nick Glozier6.   

Abstract

BACKGROUND: Mobile health (mHealth) apps offer a scalable option for treating sleep disturbances at a population level. However, there is a lack of clarity about the development and evaluation of evidence-based mHealth apps.
OBJECTIVE: The aim of this systematic review was to provide evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance.
METHODS: A systematic search of studies published from the inception of databases through February 2020 was conducted using 5 databases (MEDLINE, Embase, Cochrane Library, PsycINFO, and CINAHL).
RESULTS: A total of 6015 papers were identified using the search strategy. After screening, 15 papers were identified that examined the design engineering and clinical implementation and evaluation of 8 different mHealth apps for sleep disturbance. Most of these apps delivered cognitive behavioral therapy for insomnia (CBT-I, n=4) or modified CBT-I (n=2). Half of the apps (n=4) identified adopting user-centered design or multidisciplinary teams in their design approach. Only 3 papers described user and data privacy. End-user acceptability and engagement were the most frequently assessed implementation metrics. Only 1 app had available evidence assessing all 4 implementation metrics (ie, acceptability, engagement, usability, and adherence). Most apps were prototype versions (n=5), with few matured apps. A total of 6 apps had supporting papers that provided a quantitative evaluation of clinical outcomes, but only 1 app had a supporting, adequately powered randomized controlled trial.
CONCLUSIONS: This is the first systematic review to synthesize and examine evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance. The minimal number of apps with published evidence for design engineering and clinical implementation and evaluation contrasts starkly with the number of commercial sleep apps available. Moreover, there appears to be no standardization and consistency in the use of best practice design approaches and implementation assessments, along with very few rigorous efficacy evaluations. To facilitate the development of successful and evidence-based apps for sleep disturbance, we developed a high-level framework to guide researchers and app developers in the end-to-end process of app development and evaluation. ©Melissa Aji, Christopher Gordon, Elizabeth Stratton, Rafael A Calvo, Delwyn Bartlett, Ronald Grunstein, Nick Glozier. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.02.2021.

Entities:  

Keywords:  insomnia; internet-based intervention; mHealth; mobile applications; mobile health; sleep; systematic review

Year:  2021        PMID: 33595441      PMCID: PMC7929739          DOI: 10.2196/24607

Source DB:  PubMed          Journal:  J Med Internet Res        ISSN: 1438-8871            Impact factor:   5.428


  64 in total

1.  Cognitive behavioral therapy alone and with medication for persistent insomnia.

Authors:  Ripu D Jindal
Journal:  JAMA       Date:  2009-09-09       Impact factor: 56.272

2.  Criteria for assessing the quality of mHealth apps: a systematic review.

Authors:  Rasool Nouri; Sharareh R Niakan Kalhori; Marjan Ghazisaeedi; Guillaume Marchand; Mobin Yasini
Journal:  J Am Med Inform Assoc       Date:  2018-08-01       Impact factor: 4.497

3.  Effective? Engaging? Secure? Applying the ORCHA-24 framework to evaluate apps for chronic insomnia disorder.

Authors:  Simon Leigh; Jing Ouyang; Chris Mimnagh
Journal:  Evid Based Ment Health       Date:  2017-09-25

4.  Clinician Perceptions Related to the Use of the CBT-I Coach Mobile App.

Authors:  Katherine E Miller; Eric Kuhn; Jason E Owen; Katherine Taylor; Jessica S Yu; Brandon J Weiss; Jill J Crowley; Mickey Trockel
Journal:  Behav Sleep Med       Date:  2017-12-01       Impact factor: 2.964

5.  Epidemiology of insomnia, depression, and anxiety.

Authors:  Daniel J Taylor; Kenneth L Lichstein; H Heith Durrence; Brant W Reidel; Andrew J Bush
Journal:  Sleep       Date:  2005-11       Impact factor: 5.849

Review 6.  Insomnia as a predictor of depression: a meta-analytic evaluation of longitudinal epidemiological studies.

Authors:  Chiara Baglioni; Gemma Battagliese; Bernd Feige; Kai Spiegelhalder; Christoph Nissen; Ulrich Voderholzer; Caterina Lombardo; Dieter Riemann
Journal:  J Affect Disord       Date:  2011-02-05       Impact factor: 4.839

7.  Smartphone apps for insomnia: examining existing apps' usability and adherence to evidence-based principles for insomnia management.

Authors:  Jessica S Yu; Eric Kuhn; Katherine E Miller; Katherine Taylor
Journal:  Transl Behav Med       Date:  2019-01-01       Impact factor: 3.046

8.  Review and Analysis of Existing Mobile Phone Apps to Support Heart Failure Symptom Monitoring and Self-Care Management Using the Mobile Application Rating Scale (MARS).

Authors:  Ruth M Masterson Creber; Mathew S Maurer; Meghan Reading; Grenny Hiraldo; Kathleen T Hickey; Sarah Iribarren
Journal:  JMIR Mhealth Uhealth       Date:  2016-06-14       Impact factor: 4.773

9.  Sleep apps and behavioral constructs: A content analysis.

Authors:  Diana S Grigsby-Toussaint; Jong Cheol Shin; Dayanna M Reeves; Ariana Beattie; Evan Auguste; Girardin Jean-Louis
Journal:  Prev Med Rep       Date:  2017-02-21

10.  Reviewing the data security and privacy policies of mobile apps for depression.

Authors:  Kristen O'Loughlin; Martha Neary; Elizabeth C Adkins; Stephen M Schueller
Journal:  Internet Interv       Date:  2018-12-20
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  4 in total

1.  The Effects of Objective Push-Type Sleep Feedback on Habitual Sleep Behavior and Momentary Symptoms in Daily Life: mHealth Intervention Trial Using a Health Care Internet of Things System.

Authors:  Hiroki Takeuchi; Kaori Suwa; Akifumi Kishi; Toru Nakamura; Kazuhiro Yoshiuchi; Yoshiharu Yamamoto
Journal:  JMIR Mhealth Uhealth       Date:  2022-10-06       Impact factor: 4.947

2.  Towards Understanding the Usability Attributes of AI-Enabled eHealth Mobile Applications.

Authors:  Adel Saeed Alzahrani; Valerie Gay; Ryan Alturki; Mohammad J AlGhamdi
Journal:  J Healthc Eng       Date:  2021-12-21       Impact factor: 2.682

3.  Differential effects of COVID-related lockdown on sleep-wake rhythms in adults with autism spectrum disorder compared to the general population.

Authors:  Eve Reynaud; Julien Pottelette; Juliette Rabot; Julie Rolling; Sylvie Royant-Parola; Sarah Hartley; Romain Coutelle; Carmen M Schröder
Journal:  Autism Res       Date:  2022-03-02       Impact factor: 4.633

Review 4.  The Implementation of Behavior Change Techniques in mHealth Apps for Sleep: Systematic Review.

Authors:  Amber Carmen Arroyo; Matthew J Zawadzki
Journal:  JMIR Mhealth Uhealth       Date:  2022-04-04       Impact factor: 4.947

  4 in total

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