e.g. mhealth
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Skip search results from other journals and go to results- 91 Journal of Medical Internet Research
- 52 JMIR Formative Research
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Association Between Risk Factors and Major Cancers: Explainable Machine Learning Approach
Such insights can contribute to enhanced risk monitoring and patient stratification and provide valuable support for clinicians in their decision-making processes, ultimately improving the quality patient care. By elucidating these critical factors and their associated risk factor patterns, we provided clinicians valuable insights through rigorous analysis for enhancing risk monitoring and patient care across various cancer types.
JMIR Cancer 2025;11:e62833
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In recent decades, there has been an increasing focus on self-monitoring apps in primary care, which, with the advent of new technologies, have become more convenient and accessible for patients [1-3].
The use of mobile health (m Health) apps is undeniably a valuable tool for enabling self-monitoring and health care interventions [4,5]. Specifically, the advancement of noncontact techniques for monitoring human vital signs holds significant potential to enhance patient care across various settings [6,7].
JMIR Res Protoc 2025;14:e65229
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The discussions yielded themes centered on the user-friendly nature of the app, the capacity of the app to assist in self-monitoring of disease conditions, the need for personalized health education, concerns about data security, and considerations regarding subscription charges. Finally, 2 more attributes were added to the list generated from the stage 1 literature review, bringing the total to 40 attributes.
JMIR Mhealth Uhealth 2025;13:e58556
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In this context, our research group designed the mixed care model (MAM, from the Spanish Modelo Atencion Mixta), which incorporates the use of information and communication technologies, and also designed a previous pilot study called Digireuma, with the goal of developing a digital health tool for monitoring e PROs in patients with RA and Sp A[6].
JMIR Hum Factors 2025;12:e58095
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The objective of this study was to analyze the clinical and economic impacts of this e Health device in real life compared to the usual monitoring of frail older people living at home. In France, as this medical device is the first to predict ED use, there are, to our knowledge, few medico-economic studies available.
JMIR Form Res 2025;9:e63700
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Leveraging the convenience and ubiquity of mobile devices, EMA has been particularly effective in longitudinally monitoring conditions such as depression and mental well-being [1,2], mobility [3], physical activity [4], and fatigue [5].
The strength of EMA lies in its ability to minimize recall bias [6,7] and provide more fine-grained longitudinal data compared with traditional observation methods or retrospective reporting [8,9].
JMIR Mhealth Uhealth 2025;13:e57018
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Patients who self-reportedly used either 1 or multiple of the following technologies during OUT-III were categorized as a patient using digital tools: phone-based assessments by the attending cardiac rehabilitation facility and digital training diaries (with and without adherence monitoring done by the cardiac rehabilitation facility and with and without wearables).
JMIR Mhealth Uhealth 2025;13:e57413
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Such aggregated dashboards are helpful for monitoring, although they offer limited assistance in predicting and preventing falls in routine care settings. To the best of our knowledge, no previous study has reported the development of a dashboard designed to predict fall risks for individual residents and aid decision-making in preventing and managing falls.
JMIR Aging 2025;8:e63609
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According to Riegel and colleagues [15], self-care consists of 3 components: self-care maintenance, self-care monitoring, and self-care management. These 3 components are connected and work together concurrently. Self-care maintenance refers to behaviors that maintain health. Self-care monitoring involves observing for symptom changes. Self-care management is the response to any observed symptom changes [15].
J Med Internet Res 2025;27:e62822
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The current standard for monitoring growth and development during early pregnancy is the crown-rump length (CRL). Early measurements of the CRL are used in standard clinical practice to estimate gestational age. Moreover, CRL measurements can be used to predict miscarriages and are associated with estimated fetal weight, birth weight, and adverse pregnancy outcomes [1-5].
Volumetric measurements of the human embryo during early pregnancy are a novel way to assess growth and development.
J Med Internet Res 2025;27:e60887
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