JMIR mHealth and uHealth
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JMIR mHealth and uHealth · Jul 2020
The Mobile App Development and Assessment Guide (MAG): Delphi-Based Validity Study.
In recent years, there has been an exponential growth of mobile health (mHealth)-related apps. This has occurred in a somewhat unsupervised manner. Therefore, having a set of criteria that could be used by all stakeholders to guide the development process and the assessment of the quality of the apps is of most importance. ⋯ The data supports the validity of the MAG. In addition, the findings identified the criteria that stakeholders consider to be most important. The MAG will help advance the field by providing developers, health care professionals, and end users with a valid guide so that they can develop and identify mHealth-related apps that are of quality.
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JMIR mHealth and uHealth · Jul 2020
Barriers to and Facilitators of the Prescription of mHealth Apps in Australian General Practice: Qualitative Study.
The ubiquity of smartphones and health apps make them a potential self-management tool for patients that could be prescribed by medical professionals. However, little is known about how Australian general practitioners and their patients view the possibility of prescribing mobile health (mHealth) apps as a nondrug intervention. ⋯ mHealth app prescription appears to be feasible in general practice. The barriers and facilitators identified by the providers and patients overlapped, though privacy was of less concern to patients. The involvement of health professionals and patients is vital for the successful integration of effective, evidence-based mHealth apps with clinical practice.
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JMIR mHealth and uHealth · Jul 2020
Assessment of the Fairness of Privacy Policies of Mobile Health Apps: Scale Development and Evaluation in Cancer Apps.
Cancer patients are increasingly using mobile health (mHealth) apps to take control of their health. Many studies have explored their efficiency, content, usability, and adherence; however, these apps have created a new set of privacy challenges, as they store personal and sensitive data. ⋯ In this paper, we present a scale for the assessment of mHealth apps that is an improved version of our previous scale with adjusted scores. The results showed a lack of fairness in the mHealth app privacy policies that we examined, and the scale provides developers with a tool to evaluate their privacy policies.
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JMIR mHealth and uHealth · Jul 2020
User-Dependent Usability and Feasibility of a Swallowing Training mHealth App for Older Adults: Mixed Methods Pilot Study.
Swallowing difficulties (ie, dysphagia) are common among older adults, with a 13% to 54% prevalence. Adequate interventions to improve the swallowing function of older adults would reduce morbidity and enhance health-related quality of life outcomes. Mobile health (mHealth) apps may help alleviate dysphagia symptoms by providing programs that maximize the intensity and frequency of training without requiring high costs or regular clinic visits. ⋯ To the best of the authors' knowledge, this usability and feasibility study is the first report of a swallowing training app designed to improve the swallowing function of older adults. Future research should consider several issues, such as user characteristics, pretraining education, and the intensity and innate characteristics of the intervention program.
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JMIR mHealth and uHealth · Jul 2020
Evaluation Criteria for Weight Management Apps: Validation Using a Modified Delphi Process.
The use of apps for weight management has increased over recent years; however, there is a lack of evidence regarding the efficacy and safety of these apps. The EVALAPPS project will develop and validate an assessment instrument to specifically assess the safety and efficacy of weight management apps. ⋯ Results confirmed the robustness of the criteria that were identified, with those relating to security and privacy being deemed most relevant by stakeholders. Additionally, a specific set of criteria based on health indicators (activity data, physical state data, and personal data) was also prioritized.