e.g. mhealth
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Skip search results from other journals and go to results- 50 JMIR Formative Research
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AI tools are strongly related with data mining and AI is nowadays ranked among the top-10 technology, whichever the application [9]. Despite their limitations, AI tools and techniques that are still in their infancy already provide substantial benefits in providing in-depth knowledge on individuals’ health and predicting population health risks. Their use for medicine and public health is expected to increase substantially in the near future [10].
JMIR Form Res 2025;9:e37160
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However, these studies [15-28] have issues with heterogeneity among interventions used, consistency of their application, patient population specifics, duration of studies, and outcome measures. In addition, studies have suggested that support from a third party, such as a health care professional may improve engagement levels [16,21,23,24,28].
JMIR Mhealth Uhealth 2025;13:e56318
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But if the application can tell me well done, you have achieved your target, to me it is good enough.
Physiotherapists expressed the need to have easily accessible patient information within the program to facilitate seamless follow-up coordination. They emphasized the efficiency of receiving prompts when patients are not progressing well, as it would save valuable time for the clinicians.
JMIR Rehabil Assist Technol 2025;12:e59688
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When physicians are better informed about the positive clinical outcomes that can be achieved through m Health apps, as well as aspects related to practical application, such as data integrity and privacy, their perceived usefulness and ease of use increase. This increased knowledge reduces uncertainty and skepticism, which ultimately leads to greater acceptance and integration of technology into everyday medical practice.
JMIR Mhealth Uhealth 2025;13:e56666
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Reference 18: Engagement with Manage My Pain mobile health application among patients at the Transitional Reference 42: A decision-theoretic generalization of on-line learning and an application to boostingapplication
JMIR Med Inform 2025;13:e67178
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Reference 40: The iCanCope pain self-management application for adolescents with juvenile idiopathicapplication
JMIR Pediatr Parent 2025;8:e65826
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The development and application of EACH were segmented into several steps, as illustrated in Figure 1. We tried to follow the guideline for developing reporting machine learning prediction models in biomedical research [22].
Visual guide to the sequential steps and their detailed execution. SHAP: SHapley Additive ex Planations.
J Med Internet Res 2025;27:e58021
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During the second design workshop, members of the research team invited individuals at random to participate in a cognitive walkthrough to evaluate the usability of the application. Of the 25 workshop participants, 6 (24%) completed the walkthrough exercise. Participants were asked to perform several in-app tasks and seek specific information presented in the app while narrating out loud what they were doing.
JMIR Hum Factors 2025;12:e59485
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The study also aimed to determine the usefulness of using a commercially licensed software application on Android and i OS devices as a tool for EMA.
This EMA study was part of a larger program of research, the APPETIt E project, which examines feeding and eating in preschool children with avid eating behavior to inform future intervention design and efficacy. An avid eating behavior profile in preschool children was identified and defined in an earlier APPETIt E study using latent profile analysis (LPA) [1].
JMIR Form Res 2025;9:e66807
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