MedFit App, a Behavior-Changing, Theoretically Informed Mobile App for Patient Self-Management of Cardiovascular Disease: User-Centered Development

Duff, Orlaith; Walsh, Deirdre; Malone, Shauna; McDermott, Lauri; Furlong, Bróna; O’Connor, Noel E.; Moran, Kieran; Woods, Catherine

doi:10.2196/preprints.9550

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…Fourth, evidence of enhanced impact was found among digital interventions that reported involvement of end users in the design process. This involvement is a key component of user-centered design, an approach that prioritizes user needs and experiences to maximize functionality and increase engagement and relevance to the target population [ 82 - 84 ]. User involvement is particularly important when developing digital interventions tailored to specific target populations to ensure that such interventions appropriately reflect group priorities, preferences, and culture [ 83 ].…”

Section: Discussionmentioning

confidence: 99%

Using Digital Communication Technology to Increase HIV Testing Among Men Who Have Sex With Men and Transgender Women: Systematic Review and Meta-Analysis

Veronese¹,

Ryan²,

Hughes³

et al. 2020

J Med Internet Res

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Background HIV continues to disproportionately affect men who have sex with men (MSM) and transgender women (TW). Undiagnosed HIV is a major driver of HIV transmission rates, and increasing the uptake of regular HIV testing and facilitating timely initiation of HIV treatment is a global HIV prevention priority. However, MSM and TW experience a range of barriers that limit their access to testing and other prevention services. Given their growing ubiquity, digital communication technologies are increasingly being used to support HIV prevention efforts, and a growing number of studies have trialed the use of digital technology to promote HIV testing among MSM and TW. Objective We undertook a systematic review and meta-analysis to assess the impact of digital communication technology on HIV testing uptake among MSM and TW. Subanalyses aimed to identify the features and characteristics of digital interventions associated with greater impact. Methods A systematic literature review was undertaken using select databases and conference repositories. Studies describing the use of a digital technology—internet-enabled devices, including phones, tablets, and computers—to increase HIV testing uptake among MSM or TW using either randomized or observational cohort design with measurement of HIV testing rates measured pre- and postintervention, and published in English between 2010 and 2018 were included. Pooled effect estimates were calculated using a random effects meta-analysis. Subanalyses calculated effect estimates grouped by selected features of digital interventions. Results A total of 13 randomized or observational studies were included in the final review. Digital interventions most commonly used mainstream, existing social media platforms (n=7) or promotion through online peer educators (n=5). Most interventions (n=8) were categorized as interactive and allowed user engagement and most directly facilitated testing (n=7) either by providing self-testing kits or referral to testing services. A total of 1930 participants were included across the 13 studies. HIV testing uptake among MSM and TW exposed to digital interventions was 1.5 times higher than that of unexposed MSM and TW (risk ratio [RR] 1.5; 95% CI 1.3-1.7). Subanalyses suggested an increased impact on HIV testing uptake among interventions that were delivered through mainstream social media–based platforms (RR 1.7; 95% CI 1.3-2.1), included direct facilitation of HIV testing (RR 1.6; 95% CI 1.4-1.9), were interactive (RR 1.6; 95% CI 1.4-1.8), and involved end users in the design process (RR 1.6; 95% CI 1.3-2.0). Conclusions These findings provide broad support for the integration of technology with existing approaches to promote and facilitate HIV testing among MSM and TW. Our findings identified key features that may be associated with greater impact on HIV testing uptake and can be used to inform future development efforts given the growing interest and application of digital technologies in HIV prevention. Trial Registration PROSPERO International Prospective Register of Systematic Reviews CRD42017070055; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42017070055.

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Section: Discussionmentioning

confidence: 99%

Using Digital Communication Technology to Increase HIV Testing Among Men Who Have Sex With Men and Transgender Women: Systematic Review and Meta-Analysis

Veronese¹,

Ryan²,

Hughes³

et al. 2020

J Med Internet Res

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“…Duff et al, ( 20 ) present an application called MedFit. This app is designed to facilitate the participation of people with cardiovascular disease (CVD) in an exercise-based rehabilitation program remotely.…”

Section: Resultsmentioning

confidence: 99%

Evaluation of mHealth Applications Related to Cardiovascular Diseases: a Systematic Review

Villarreal¹,

Berbey-Alvarez²

2020

Acta Inform Med

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Introduction: Currently, with the widespread penetration of mobile devices with Internet access, including smartphones, they can allow specific and/or complementary activities in the health field as well as in other commercial sectors. Aim: This systematic review examined the impact of mHealth-based for cardiovascular research. The specific aims of the systematic review are to ( 1 ) classification of the studies according to the type of research (scientific articles and master’s and doctoral theses) and ( 2 ) relationship of studies with topics associated with cardiovascular diseases. Results: This review corresponds to information in scientific journals of high impact. This review intends to respond to the following question: How these research works have evaluated the performance of health mobile applications, with a special interest in cardiac issues? This review of these searches corresponds to an analysis by 14 categories, being these: 1) Scientific paper; 2) Doctoral Thesis; 3) Master thesis; 4) Telemedicine; 5) m-sssshealth, e-health; 6) cardiovascular, coronary diseases, heart failures, cardiopulmonary, cardiac rehabilitation; 7) rural health; 8) prevention and control, protection; 9) wearables; 10) mobile, web applications, app, smartphone, software, platform; 11) mhealth education, training, promotion, formative process; 12) self-management; 13) Multiple Vital Sign Monitoring, medical device, heart rate measurement, health care information systems; 14) health regulatory. It provides evidence of how some apps have been evaluated, and in some cases, the effectiveness of the estimated accuracy is not in line with the real situation. Conclusion: The analysis of these studies allows us to locate the sources of the development of mobile health projects. It also guides us to discover some needs that require new technology implementations.

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“…As most of the included frameworks (n=15, 65%) discussed design, development and evaluation, a pivotal, final phase entailed evaluating a prototype through, pilot testing of usability, feasibility, and acceptability. This helped identify any bugs or necessary changes that needed to be made to improve the conversational agent before testing it in a larger randomized trial [206,215].…”

Section: Smartphone Appmentioning

confidence: 99%

Exploring the use of conversational agents in healthcare: an overview, conceptual analysis and case study

Dhinagaran¹

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This chapter addresses the first aim to "map and analyze the current uses of conversational agents in healthcare and identify knowledge gaps by performing a scoping review." Section 4.1 provides some background information on existing reviews on healthcare CAs, what is missing from the literature, and the specific objectives of this review. The methodology is described in section 4.2 and the results are presented in section 4.3 both narratively and diagrammatically.The implications of the findings, strengths, and limitations of this review as well as suggestions for future research are outlined in section 4.4. This scoping review was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist [123] and the updated Arksey and O'Malley framework [124]. To address the research questions presented in 4.1.1, a broad literature search needed to be conducted to identify the various usage applications of CAs. This required a comprehensive search of several databases using a multitude of synonyms. A broad literature search was conducted in April 2019 in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central. Given the novelty of the field, and to increase comprehensiveness, gray literature was also searched for in the OCLC WorldCat database, ResearchGate, Google Scholar, OpenGrey, and the first 10 pages of Google. There was an extensive list of 63 search terms, which were various iterations of the term "conversational agents" (Appendix 4.1). These synonyms were generated using a web-based search and by identifying specific terms or phrases used in the titles of articles discussing health care conversational agents. Snowball searching of relevant articles and systematic reviews was also done to identity more articles related to the review. The PRISMA checklist for scoping reviews was completed and is presented in Appendix 4.2. Inclusion and Exclusion CriteriaPrimary research studies that had evaluated a CA implemented for healthcare were included.Articles that just presented a proposal for CA development, articles that mentioned conversational agents briefly or as an insignificant part of a review, as well as opinion pieces and articles where primary research was not conducted, were excluded. A further point of exclusion was articles with poorly reported data on CA assessments where there was minimal or no evaluation data. In addition, articles concerning ECAs, relational agents, animated conversational agents, or other conversational agents with a visual or animated component were excluded. ECAs are computer-generated virtual avatars that interact with users with both verbal and non-verbal communication [125]. Relational agents are a type of ECA designed to create long-term deep and meaningful relationships with individuals [126]. As the user's interaction may be affected by nonverbal behaviors, graphics, and layout of the program, it was decided th...

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MedFit App, a Behavior-Changing, Theoretically Informed Mobile App for Patient Self-Management of Cardiovascular Disease: User-Centered Development

Cited by 3 publications

References 8 publications

Using Digital Communication Technology to Increase HIV Testing Among Men Who Have Sex With Men and Transgender Women: Systematic Review and Meta-Analysis

Using Digital Communication Technology to Increase HIV Testing Among Men Who Have Sex With Men and Transgender Women: Systematic Review and Meta-Analysis

Evaluation of mHealth Applications Related to Cardiovascular Diseases: a Systematic Review

Exploring the use of conversational agents in healthcare: an overview, conceptual analysis and case study

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