Literature DB >> 29250238

Feasibility and Usability of a Mobile Application to Assess Symptoms and Affect in Patients with Atrial Fibrillation: A Pilot Study.

Hamid Ghanbari1, Sardar Ansari2, Michael Ghannam1, Sangeeta Lathkar-Pradhan1, Anna Kratz3, Hakan Oral1, Kayvan Najarian2, Daniel Clauw4, Brahmajee Nallamothu1.   

Abstract

BACKGROUND: Atrial fibrillation (AF) is the most prevalent arrhythmia leading to hospital admissions. The majority of patients with AF report symptoms that are believed to be associated with the arrhythmia. The symptoms related to AF traditionally are collected during a clinic visit that is influenced by biases associated with recalling the experience over a limited period of time.
PURPOSE: We designed this pilot study to assess the usability and feasibility of a mobile application to assess symptoms in patients with AF.
METHODS: We designed a mobile application (miAfib) to assess symptoms (chest pain, palpitation, shortness of breath, fatigue, dizziness/lightheadedness), positive affect (happy, excited, content) and negative affect (worried, angry, sad) on multiple occasions throughout the day based on iOS platform. We performed a four-week feasibility trial to examine user adherence, acceptance and experiences with the mobile application. We administered questionnaires to assess factors affecting usage and self-reported acceptance of the application based on a five-point Likert scale with zero representing strongly disagree and 5 representing strongly disagree with.
RESULTS: We included ten patients with paroxysmal and persistent AF. The mean number of completed assessments each day was 2.81 ± 1.59 with 94.7% of days with at least one assessment. The users found the application easy to use (4.75±0.46), intended to use it in the future (4.37±1.06) and found it easy to integrate into daily routine (4.5±1.07).
CONCLUSION: In this pilot study, we found participants in this four-week trial reliably used the application and were able to use the app to report their daily symptoms and affect regularly. Participants reported that they found the application easy to use and would consider using the application in the future.

Entities:  

Keywords:  Atrial Fibrillation; Feasibility Study; Mobile Application

Year:  2017        PMID: 29250238      PMCID: PMC5673297          DOI: 10.4022/jafib.1672

Source DB:  PubMed          Journal:  J Atr Fibrillation        ISSN: 1941-6911


  14 in total

Review 1.  Symptoms and functional status of patients with atrial fibrillation: state of the art and future research opportunities.

Authors:  Michiel Rienstra; Steven A Lubitz; Saagar Mahida; Jared W Magnani; João D Fontes; Moritz F Sinner; Isabelle C Van Gelder; Patrick T Ellinor; Emelia J Benjamin
Journal:  Circulation       Date:  2012-06-12       Impact factor: 29.690

2.  Secular trends in incidence of atrial fibrillation in Olmsted County, Minnesota, 1980 to 2000, and implications on the projections for future prevalence.

Authors:  Yoko Miyasaka; Marion E Barnes; Bernard J Gersh; Stephen S Cha; Kent R Bailey; Walter P Abhayaratna; James B Seward; Teresa S M Tsang
Journal:  Circulation       Date:  2006-07-03       Impact factor: 29.690

3.  Drivers of hospitalization for patients with atrial fibrillation: Results from the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF).

Authors:  Benjamin A Steinberg; Sunghee Kim; Gregg C Fonarow; Laine Thomas; Jack Ansell; Peter R Kowey; Kenneth W Mahaffey; Bernard J Gersh; Elaine Hylek; Gerald Naccarelli; Alan S Go; James Reiffel; Paul Chang; Eric D Peterson; Jonathan P Piccini
Journal:  Am Heart J       Date:  2014-02-17       Impact factor: 4.749

4.  Symptoms, functional status and quality of life in patients with controlled and uncontrolled atrial fibrillation: data from the RealiseAF cross-sectional international registry.

Authors:  P Gabriel Steg; Samir Alam; Chern-En Chiang; Habib Gamra; Marnix Goethals; Hiroshi Inoue; Laura Krapf; Thorsten Lewalter; Ihsen Merioua; Jan Murin; Lisa Naditch-Brûlé; Piotr Ponikowski; Mårten Rosenqvist; José Silva-Cardoso; Oleg Zharinov; Sandrine Brette; James O Neill
Journal:  Heart       Date:  2011-09-22       Impact factor: 5.994

5.  Estimation of total incremental health care costs in patients with atrial fibrillation in the United States.

Authors:  Michael H Kim; Stephen S Johnston; Bong-Chul Chu; Mehul R Dalal; Kathy L Schulman
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2011-05-03

6.  Depression as an aetiologic and prognostic factor in coronary heart disease: a meta-analysis of 6362 events among 146 538 participants in 54 observational studies.

Authors:  Amanda Nicholson; Hannah Kuper; Harry Hemingway
Journal:  Eur Heart J       Date:  2006-11-02       Impact factor: 29.983

7.  Influence of age, sex, and atrial fibrillation recurrence on quality of life outcomes in a population of patients with new-onset atrial fibrillation: the Fibrillation Registry Assessing Costs, Therapies, Adverse events and Lifestyle (FRACTAL) study.

Authors:  Matthew R Reynolds; Tara Lavelle; Vidal Essebag; David J Cohen; Peter Zimetbaum
Journal:  Am Heart J       Date:  2006-12       Impact factor: 4.749

8.  The effect of anxiety and depression on symptoms attributed to atrial fibrillation.

Authors:  Tiffany S Thompson; Debra J Barksdale; Samuel F Sears; John Paul Mounsey; Irion Pursell; Anil K Gehi
Journal:  Pacing Clin Electrophysiol       Date:  2013-11-11       Impact factor: 1.976

9.  Temporal relations of atrial fibrillation and congestive heart failure and their joint influence on mortality: the Framingham Heart Study.

Authors:  Thomas J Wang; Martin G Larson; Daniel Levy; Ramachandran S Vasan; Eric P Leip; Philip A Wolf; Ralph B D'Agostino; Joanne M Murabito; William B Kannel; Emelia J Benjamin
Journal:  Circulation       Date:  2003-05-27       Impact factor: 29.690

10.  Development and feasibility testing of a smart phone based attentive eating intervention.

Authors:  Eric Robinson; Suzanne Higgs; Amanda J Daley; Kate Jolly; Deborah Lycett; Amanda Lewis; Paul Aveyard
Journal:  BMC Public Health       Date:  2013-07-09       Impact factor: 3.295

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  2 in total

Review 1.  Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management.

Authors:  Chayakrit Krittanawong; Albert J Rogers; Kipp W Johnson; Zhen Wang; Mintu P Turakhia; Jonathan L Halperin; Sanjiv M Narayan
Journal:  Nat Rev Cardiol       Date:  2020-10-09       Impact factor: 32.419

2.  Coordinating Health Care With Artificial Intelligence-Supported Technology for Patients With Atrial Fibrillation: Protocol for a Randomized Controlled Trial.

Authors:  Liliana Laranjo; Tim Shaw; Ritu Trivedi; Stuart Thomas; Emma Charlston; Harry Klimis; Aravinda Thiagalingam; Saurabh Kumar; Timothy C Tan; Tu N Nguyen; Simone Marschner; Clara Chow
Journal:  JMIR Res Protoc       Date:  2022-04-13
  2 in total

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