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Skip search results from other journals and go to results- 127 Journal of Medical Internet Research
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Clinical Nurse Educators’ Job Satisfaction and Turnover Intentions: Protocol for a Scoping Review
JMIR Res Protoc 2025;14:e66712
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Large Language Model Architectures in Health Care: Scoping Review of Research Perspectives
For example, Lim et al [41] compare the perceived accuracy and comprehensiveness of GPT-3.5, GPT-4, and BARD on myopia-related questions.
We identify 8 different stakeholders in our sample. Most studies provide insights for physicians (69/114, 60.53%), researchers (32/114, 28.07%), patients (23/114, 20.18%), and students (17/114, 14.91%).
J Med Internet Res 2025;27:e70315
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A systematic review and meta-analysis by Di Lorito et al [46] found that such interventions can produce positive effects on cognitive abilities among people with MCI and dementia. Furthermore, Karakose et al [47] conducted a comprehensive bibliometric and science mapping analysis, revealing the evolving landscape of digital addiction research, which is pertinent to understanding user engagement with digital health tools.
JMIR Hum Factors 2025;12:e70177
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Our protocol was developed using the scoping review methodological framework proposed by Arksey and O’Malley [39] and further refined by Peters et al [40].
The central research question guiding this review was as follows: “What are the most frequently reported risk factors associated with suicidal ideation in the psychology and mental health literature?”
JMIR Form Res 2025;9:e63272
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In a recent meta-analysis by Armache et al [31], the readability of 1124 education materials for patients with head and neck cancer was evaluated that was produced by professional societies, hospitals, and other organizations intended to inform patients, promote their engagement, and enhance their adherence to treatment plans. The mean Flesch-Kincaid grade level of these materials ranged from 8.8 to 14.8, with none of them meeting the recommended sixth-grade readability standard.
J Med Internet Res 2025;27:e73337
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Examples of the former include Shang et al [15] and Amirahmadi et al [28] that predicted medications based on diagnoses and diagnoses based on medication to induce relationships within the diagnoses and interventions in the learned representation. Med-BERT [11] introduced a length of stay auxiliary prediction task to enrich contextual information about the severity of patients’ health conditions.
JMIR Med Inform 2025;13:e68138
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