e.g. mhealth
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Skip search results from other journals and go to results- 8 JMIR Formative Research
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Electronic dashboards are a form of HIT that can be used to track critical information, provide alerts, assess performance indicators, develop reports, and customize data views, which makes them a useful tool for monitoring inventory data and facility-level readiness [7,8].
JMIR Hum Factors 2025;12:e64131
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The objective of this study is to develop a dashboard for DIs mediated by cytochromes using an HDW in order to display results that are easily readable and interpretable by clinical experts.
The first step was to define the requirements for creating a relevant dashboard for clinical practice. This tool was intended for pharmacologists, with whom 3 meetings were conducted. The first meeting aimed to define their needs related to their practice and research issues.
JMIR Med Inform 2024;12:e57705
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By further exploring these research avenues, we can develop a comprehensive understanding of how to use digital interventions to best support the mental health and well-being of high school students and staff, thereby promoting a positive and nurturing learning environment.
The COVID-19 pandemic has profoundly impacted every aspect of our lives, especially within the school community.
JMIR Form Res 2024;8:e56355
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Considering this, gamification strategies were used to develop Mob ERAS, including the use of figures representing the health status of patients, a reward system, avatars, and motivational figures, as well as a GPS attached to the system to monitor walking. We believe that this will motivate patients to fulfill their goals and consequently follow medical recommendations, thus reaching the desired postoperative objectives.
JMIR Perioper Med 2024;7:e56033
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This suggests the necessity of engaging both end users and health care professionals in co-design to design and develop the technology they will use together [36]. Although the number of available m Health apps is increasing rapidly, there is a need to create a rigorous design thinking process for their development [29] and guidance that ensures the sustainability of the apps [37,38].
Emerging apps do provide exercise support.
JMIR Diabetes 2024;9:e51491
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This study aimed to systematically develop 3 D nursing simulation content based on a VR educational design model and the National League for Nursing (NLN) Jeffries Simulation Theory. It also conducted user tests to evaluate its feasibility in nursing education. We propose a multidisciplinary VRS content development model and provide the basis for future VR-based nursing education.
JMIR Med Educ 2024;10:e53106
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Stimuli were built using botmock [59,60] to develop the chat dialogue, which was then integrated into Facebook Messenger (FM; Meta Platforms, Inc) using Chatfuel [61]. Participants had a guided initial chat conversation introducing the chatbot and program goals, querying about triggers for smoking, and setting a quit date. Subsequently, they interacted with Quit Bot for a second conversation, focusing on tracking triggers to smoke.
JMIR Mhealth Uhealth 2024;12:e57318
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Therefore, we aimed to develop and externally validate a CT-based fracture prediction model by using images of vertebral bones and muscles by employing a deep learning method. This study may help identify patients having high risk of fractures among those who undergo opportunistic CT scans for screening or other purposes.
This study was based on a retrospective longitudinal cohort study of 32,435 patients having abdominal CT images at Seoul National University Bundang Hospital between 2010 and 2019.
J Med Internet Res 2024;26:e48535
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A Deep Learning–Based Rotten Food Recognition App for Older Adults: Development and Usability Study
This study aimed to develop and evaluate a smartphone app that enables older adults to take pictures of food items with a smartphone camera and to determine whether the items are rotten. We first reviewed prior studies that have developed and evaluated similar spoilage detection tools. After reviewing the relevant literature, we trained a model that classifies the freshness of 3 fruits (ie, apples, bananas, and oranges) and evaluated the model’s performance.
JMIR Form Res 2024;8:e55342
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