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Mobile health applications for atrial fibrillation: A readability and quality assessment.

ABSTRACT: BACKGROUND:Mobile health applications may improve patient education and self-care for a complex condition such as atrial fibrillation (AF). Little is known about the accessibility of mobile health applications ("apps") and their readability. We evaluated the readability and quality of available apps for AF. METHODS:We searched the Apple and Google Play app stores with the terms "atrial fibrillation" and "afib." We downloaded English-language apps (up to n?=?100 for each term) and categorized them by name, App store, cost, content, uploading agency (heath care associated [HCA] versus non-HCA), target audience (health care professional [HCP] versus non-HCP), scientific validity (i.e., citation of peer-reviewed or validated medical information), and user ratings. We analyzed the text of apps intended for a non-HCP target audience for readability with 10 established measures. RESULTS:Of the 206 downloaded apps, 50.5% were excluded as unrelated to AF, inaccessible, or non-English language. The majority of apps contained information about AF (63.2% Apple, 52.2% Google Play) and AF detection (52.6% Apple, 56.5% Google Play). A minority of non-HCP apps contained scientifically validated content (Apple, 15.8%; Google Play, 13.0%; P?=?NS). App mean readability was grade 12.1?±?2.6. CONCLUSIONS:Most AF apps lacked scientific validation and were written at excessively high reading-grade levels. Our results suggest caution with mobile health apps, particularly for users with limited health literacy. There is potential opportunity for a multi-disciplinary effort by regulatory agencies, healthcare organizations, and app stores to improve relevance, scientific validity, and readability of AF apps for patients with this complex and morbid disease.

SUBMITTER: Ayyaswami V

PROVIDER: S-EPMC6710110 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Mobile health applications for atrial fibrillation: A readability and quality assessment.

Ayyaswami Varun V Padmanabhan Divya L DL Crihalmeanu Tudor T Thelmo Franklin F Prabhu Arpan V AV Magnani Jared W JW

International journal of cardiology 20190710

<h4>Background</h4>Mobile health applications may improve patient education and self-care for a complex condition such as atrial fibrillation (AF). Little is known about the accessibility of mobile health applications ("apps") and their readability. We evaluated the readability and quality of available apps for AF.<h4>Methods</h4>We searched the Apple and Google Play app stores with the terms "atrial fibrillation" and "afib." We downloaded English-language apps (up to n = 100 for each term) and ...[more]

PMID: 31327518

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Project description:BackgroundAtrial fibrillation (AF) is a common arrhythmia that adversely affects health-related quality of life (HRQoL). We conducted a pilot trial of individuals with AF using a smartphone to provide a relational agent as well as rhythm monitoring. We employed our pilot to measure acceptability and adherence and to assess its effectiveness in improving HRQoL and adherence.ObjectiveThis study aims to measure acceptability and adherence and to assess its effectiveness to improve HRQoL and adherence.MethodsParticipants were recruited from ambulatory clinics and randomized to a 30-day intervention or usual care. We collected baseline characteristics and conducted baseline and 30-day assessments of HRQoL using the Atrial Fibrillation Effect on Quality of Life (AFEQT) measure and self-reported adherence to anticoagulation. The intervention consisted of a smartphone-based relational agent, which simulates face-to-face counseling and delivered content on AF education, adherence, and symptom monitoring with prompted rhythm monitoring. We compared differences in AFEQT and adherence at 30 days, adjusted for baseline values. We quantified participants' use and acceptability of the intervention.ResultsA total of 120 participants were recruited and randomized (59 to control and 61 to intervention) to the pilot trial (mean age 72.1 years, SD 9.10; 62/120, 51.7% women). The control group had a 95% follow-up, and the intervention group had a 93% follow-up. The intervention group demonstrated significantly higher improvement in total AFEQT scores (adjusted mean difference 4.5; 95% CI 0.6-8.3; P=.03) and in daily activity (adjusted mean difference 7.1; 95% CI 1.8-12.4; P=.009) compared with the control between baseline and 30 days. The intervention group showed significantly improved self-reported adherence to anticoagulation therapy at 30 days (intervention 3.5%; control 23.2%; adjusted difference 16.6%; 95% CI 2.8%-30.4%; P<.001). Qualitative assessments of acceptability identified that participants found the relational agent useful, informative, and trustworthy.ConclusionsIndividuals randomized to a 30-day smartphone intervention with a relational agent and rhythm monitoring showed significant improvement in HRQoL and adherence. Participants had favorable acceptability of the intervention with both objective use and qualitative assessments of acceptability.

Project description:BackgroundAtrial fibrillation (AF) is a highly prevalent heart rhythm condition that has significant associated morbidity and requires chronic treatment. Mobile health (mHealth) technologies have the potential to enhance multiple aspects of AF care, including education, monitoring of symptoms, and encouraging and tracking medication adherence. We have previously implemented and tested relational agents to improve outcomes in chronic disease and sought to develop a smartphone-based relational agent for improving patient-centered outcomes in AF.ObjectiveThe objective of this study was to pilot a smartphone-based relational agent as preparation for a randomized clinical trial, the Atrial Fibrillation Health Literacy Information Technology Trial (AF-LITT).MethodsWe developed the relational agent for use by a smartphone consistent with our prior approaches. We programmed the relational agent as a computer-animated agent to simulate a face-to-face conversation and to serve as a health counselor or coach specific to AF. Relational agent's dialogue content, informed by a review of literature, focused on patient-centered domains and qualitative interviews with patients with AF, encompassed AF education, common symptoms, adherence challenges, and patient activation. We established that the content was accessible to individuals with limited health or computer literacy. Relational agent content coordinated with use of the smartphone AliveCor Kardia heart rate and rhythm monitor. Participants (N=31) were recruited as a convenience cohort from ambulatory clinical sites and instructed to use the relational agent and Kardia for 30 days. We collected demographic, social, and clinical characteristics and conducted baseline and 30-day assessments of health-related quality of life (HRQoL) with the Atrial Fibrillation Effect on Quality of life (AFEQT) measure; self-reported medication adherence with the Morisky 8-item Medication Adherence Scale (MMAS-8); and patient activation with the Patient Activation Measure (PAM).ResultsParticipants (mean age 68 [SD 11]; 39% [12/31] women) used the relational agent for an average 17.8 (SD 10.0) days. The mean number of independent log-ins was 19.6 (SD 10.7), with a median of 20 times over 30 days. The mean number of Kardia uses was 26.5 (SD 5.9), and participants using Kardia were in AF for 14.3 (SD 11.0) days. AFEQT scores improved significantly from 64.5 (SD 22.9) at baseline to 76.3 (SD 19.4) units at 30 days (P<.01). We observed marginal but statistically significant improvement in self-reported medication adherence (baseline: 7.3 [SD 0.9], 30 days: 7.7 [SD 0.5]; P=.01). Assessments of acceptability identified that most of the participants found the relational agent useful, informative, and trustworthy.ConclusionsWe piloted a 30-day smartphone-based intervention that combined a relational agent with dedicated content for AF alongside Kardia heart rate and rhythm monitoring. Pilot participants had favorable improvements in HRQoL and self-reported medication adherence, as well as positive responses to the intervention. These data will guide a larger, enhanced randomized trial implementing the smartphone relational agent and the Kardia monitor system.

Project description:BackgroundAtrial fibrillation (AF) is the most common arrhythmia, and its prevalence is increasing. Early diagnosis is important to reduce the risk of stroke. Mobile health (mHealth) devices, such as single-lead electrocardiogram (ECG) devices, have been introduced to the worldwide consumer market over the past decade. Recent studies have assessed the usability of these devices for detection of AF, but it remains unclear if the use of mHealth devices leads to a higher AF detection rate.ObjectiveThe goal of the research was to conduct a systematic review of the diagnostic detection rate of AF by mHealth devices compared with traditional outpatient follow-up. Study participants were aged 16 years or older and had an increased risk for an arrhythmia and an indication for ECG follow-up-for instance, after catheter ablation or presentation to the emergency department with palpitations or (near) syncope. The intervention was the use of an mHealth device, defined as a novel device for the diagnosis of rhythm disturbances, either a handheld electronic device or a patch-like device worn on the patient's chest. Control was standard (traditional) outpatient care, defined as follow-up via general practitioner or regular outpatient clinic visits with a standard 12-lead ECG or Holter monitoring. The main outcome measures were the odds ratio (OR) of AF detection rates.MethodsTwo reviewers screened the search results, extracted data, and performed a risk of bias assessment. A heterogeneity analysis was performed, forest plot made to summarize the results of the individual studies, and albatross plot made to allow the P values to be interpreted in the context of the study sample size.ResultsA total of 3384 articles were identified after a database search, and 14 studies with a 4617 study participants were selected. All studies but one showed a higher AF detection rate in the mHealth group compared with the control group (OR 1.00-35.71), with all RCTs showing statistically significant increases of AF detection (OR 1.54-19.16). Statistical heterogeneity between studies was considerable, with a Q of 34.1 and an I2 of 61.9, and therefore it was decided to not pool the results into a meta-analysis.ConclusionsAlthough the results of 13 of 14 studies support the effectiveness of mHealth interventions compared with standard care, study results could not be pooled due to considerable clinical and statistical heterogeneity. However, smartphone-connectable ECG devices provide patients with the ability to document a rhythm disturbance more easily than with standard care, which may increase empowerment and engagement with regard to their illness. Clinicians must beware of overdiagnosis of AF, as it is not yet clear when an mHealth-detected episode of AF must be deemed significant.

Dataset Information

Mobile health applications for atrial fibrillation: A readability and quality assessment.

Publications

Mobile health applications for atrial fibrillation: A readability and quality assessment.

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