Stoyan Stoyanov

Bio: Stoyan Stoyanov is an academic researcher from Queensland University of Technology. The author has contributed to research in topics: Cronbach's alpha & mHealth. The author has an hindex of 17, co-authored 34 publications receiving 2984 citations. Previous affiliations of Stoyan Stoyanov include University of Queensland & University of Sydney.

Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps

Abstract: Background: The use of mobile apps for health and well being promotion has grown exponentially in recent years. Yet, there is currently no app-quality assessment tool beyond “star”-ratings. Objective: The objective of this study was to develop a reliable, multidimensional measure for trialling, classifying, and rating the quality of mobile health apps. Methods: A literature search was conducted to identify articles containing explicit Web or app quality rating criteria published between January 2000 and January 2013. Existing criteria for the assessment of app quality were categorized by an expert panel to develop the new Mobile App Rating Scale (MARS) subscales, items, descriptors, and anchors. There were sixty well being apps that were randomly selected using an iTunes search for MARS rating. There were ten that were used to pilot the rating procedure, and the remaining 50 provided data on interrater reliability. Results: There were 372 explicit criteria for assessing Web or app quality that were extracted from 25 published papers, conference proceedings, and Internet resources. There were five broad categories of criteria that were identified including four objective quality scales: engagement, functionality, aesthetics, and information quality; and one subjective quality scale; which were refined into the 23-item MARS. The MARS demonstrated excellent internal consistency (alpha = .90) and interrater reliability intraclass correlation coefficient (ICC = .79). Conclusions: The MARS is a simple, objective, and reliable tool for classifying and assessing the quality of mobile health apps. It can also be used to provide a checklist for the design and development of new high quality health apps.

Development and Validation of the User Version of the Mobile Application Rating Scale (uMARS)

Abstract: Background - The Mobile Application Rating Scale (MARS) provides a reliable method to assess the quality of mobile health (mHealth) apps. However, training and expertise in mHealth and the relevant health field is required to administer it. Objective - This study describes the development and reliability testing of an end-user version of the MARS (uMARS). Methods - The MARS was simplified and piloted with 13 young people to create the uMARS. The internal consistency and test-retest reliability of the uMARS was then examined in a second sample of 164 young people participating in a randomized controlled trial of a mHealth app. App ratings were collected using the uMARS at 1-, 3,- and 6-month follow up. Results - The uMARS had excellent internal consistency (alpha = .90), with high individual alphas for all subscales. The total score and subscales had good test-retest reliability over both 1-2 months and 3 months. Conclusions - The uMARS is a simple tool that can be reliably used by end-users to assess the quality of mHealth apps.

Review and Evaluation of Mindfulness-Based iPhone Apps.

Abstract: Background There is growing evidence for the positive impact of mindfulness on wellbeing. Mindfulness-based mobile apps may have potential as an alternative delivery medium for training. While there are hundreds of such apps, there is little information on their quality. Objective This study aimed to conduct a systematic review of mindfulness-based iPhone mobile apps and to evaluate their quality using a recently-developed expert rating scale, the Mobile Application Rating Scale (MARS). It also aimed to describe features of selected high-quality mindfulness apps. Methods A search for “mindfulness” was conducted in iTunes and Google Apps Marketplace. Apps that provided mindfulness training and education were included. Those containing only reminders, timers or guided meditation tracks were excluded. An expert rater reviewed and rated app quality using the MARS engagement, functionality, visual aesthetics, information quality and subjective quality subscales. A second rater provided MARS ratings on 30% of the apps for inter-rater reliability purposes. Results The “mindfulness” search identified 700 apps. However, 94 were duplicates, 6 were not accessible and 40 were not in English. Of the remaining 560, 23 apps met inclusion criteria and were reviewed. The median MARS score was 3.2 (out of 5.0), which exceeded the minimum acceptable score (3.0). The Headspace app had the highest average score (4.0), followed by Smiling Mind (3.7), iMindfulness (3.5) and Mindfulness Daily (3.5). There was a high level of inter-rater reliability between the two MARS raters. Conclusions Though many apps claim to be mindfulness-related, most were guided meditation apps, timers, or reminders. Very few had high ratings on the MARS subscales of visual aesthetics, engagement, functionality or information quality. Little evidence is available on the efficacy of the apps in developing mindfulness.

Development and validation of the user version of the Mobile Application Rating Scale (uMARS)

Abstract: Background - The Mobile Application Rating Scale (MARS) provides a reliable method to assess the quality of mobile health (mHealth) apps. However, training and expertise in mHealth and the relevant health field is required to administer it. Objective - This study describes the development and reliability testing of an end-user version of the MARS (uMARS). Methods - The MARS was simplified and piloted with 13 young people to create the uMARS. The internal consistency and test-retest reliability of the uMARS was then examined in a second sample of 164 young people participating in a randomized controlled trial of a mHealth app. App ratings were collected using the uMARS at 1-, 3,- and 6-month follow up. Results - The uMARS had excellent internal consistency (alpha = .90), with high individual alphas for all subscales. The total score and subscales had good test-retest reliability over both 1-2 months and 3 months. Conclusions - The uMARS is a simple tool that can be reliably used by end-users to assess the quality of mHealth apps.

Mechanisms of Diabetic Complications

Abstract: It is increasingly apparent that not only is a cure for the current worldwide diabetes epidemic required, but also for its major complications, affecting both small and large blood vessels. These complications occur in the majority of individuals with both type 1 and type 2 diabetes. Among the most prevalent microvascular complications are kidney disease, blindness, and amputations, with current therapies only slowing disease progression. Impaired kidney function, exhibited as a reduced glomerular filtration rate, is also a major risk factor for macrovascular complications, such as heart attacks and strokes. There have been a large number of new therapies tested in clinical trials for diabetic complications, with, in general, rather disappointing results. Indeed, it remains to be fully defined as to which pathways in diabetic complications are essentially protective rather than pathological, in terms of their effects on the underlying disease process. Furthermore, seemingly independent pathways are also showing significant interactions with each other to exacerbate pathology. Interestingly, some of these pathways may not only play key roles in complications but also in the development of diabetes per se. This review aims to comprehensively discuss the well validated, as well as putative mechanisms involved in the development of diabetic complications. In addition, new fields of research, which warrant further investigation as potential therapeutic targets of the future, will be highlighted.

A Secure Base Clinical Applications Of Attachment Theory

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Annual Research Review: Digital health interventions for children and young people with mental health problems – a systematic and meta‐review

Abstract: Digital health interventions (DHIs), including computer-assisted therapy, smartphone apps and wearable technologies, are heralded as having enormous potential to improve uptake and accessibility, efficiency, clinical effectiveness and personalisation of mental health interventions. It is generally assumed that DHIs will be preferred by children and young people (CYP) given their ubiquitous digital activity. However, it remains uncertain whether: DHIs for CYP are clinically and cost-effective, CYP prefer DHIs to traditional services, DHIs widen access and how they should be evaluated and adopted by mental health services. This review evaluates the evidence-base for DHIs and considers the key research questions and approaches to evaluation and implementation. We conducted a meta-review of scoping, narrative, systematic or meta-analytical reviews investigating the effectiveness of DHIs for mental health problems in CYP. We also updated a systematic review of randomised controlled trials (RCTs) of DHIs for CYP published in the last 3 years. Twenty-one reviews were included in the meta-review. The findings provide some support for the clinical benefit of DHIs, particularly computerised cognitive behavioural therapy (cCBT), for depression and anxiety in adolescents and young adults. The systematic review identified 30 new RCTs evaluating DHIs for attention deficit/hyperactivity disorder (ADHD), autism, anxiety, depression, psychosis, eating disorders and PTSD. The benefits of DHIs in managing ADHD, autism, psychosis and eating disorders are uncertain, and evidence is lacking regarding the cost-effectiveness of DHIs. Key methodological limitations make it difficult to draw definitive conclusions from existing clinical trials of DHIs. Issues include variable uptake and engagement with DHIs, lack of an agreed typology/taxonomy for DHIs, small sample sizes, lack of blinded outcome assessment, combining different comparators, short-term follow-up and poor specification of the level of human support. Research and practice recommendations are presented that address the key research questions and methodological issues for the evaluation and clinical implementation of DHIs for CYP.