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In addition to identifying use and perceptions, exploring young adults’ preferences for nutrition content is also needed. Exploring how young adults use the internet for nutrition content and what topics they engage with can identify opportunities for targeted intervention. In addition, understanding their perceptions of the reliability and engagement of online sources and their preferences can guide health professionals in creating effective evidence-based content.
J Med Internet Res 2025;27:e67640
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Studies have shown that HCWs’ TB preventive behaviors widely differ and are determined by their risk perceptions, knowledge levels, and institutional support. For example, HCWs at a higher risk of TB are generally more engaged in preventive behaviors [17,18]. Yet, persistent barriers remain, such as insufficient personal protective equipment, poor ventilation, and TB stigma [19,20]. Such gaps warrant strategic mapping of existing literature on HCWs’ perceptions and practices to inform future interventions.
JMIR Res Protoc 2025;14:e64037
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Factors Influencing the Use of Online Symptom Checkers in the United Kingdom: Cross-Sectional Study
Specifically, we sought to (1) assess the demographic characteristics of OSC users, (2) evaluate user perceptions of the usability and effectiveness of OSCs, (3) identify concerns related to the privacy, security, and accuracy of OSCs, and (4) quantify the weight of these various factors on the adoption and use of OSCs.
The Imperial College Research Ethics Committee granted ethical clearance for the study (ICREC# 20 IC5974).
JMIR Form Res 2025;9:e65314
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The study described here was undertaken to collect and collate social media posts during the COVID-19 pandemic in the United Kingdom with the objective to assess public perceptions, insights, and sentiments throughout the patient pathway.
To investigate discussions surrounding COVID-19 treatment on social media, we collected data from various social media platforms using a comprehensive search query (Table S1 in Multimedia Appendix 1).
JMIR Form Res 2025;9:e63997
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Falls Prevention Among Older Adults in Rural Communities: Protocol for a Scoping Review
We have included our primary and secondary research questions below:
Primary research question: What are rural older adults’ perceptions about falls prevention?
Secondary research questions: (1) How do older adults living in rural communities perceive their risk of falls? (2) What do rural older adults identify as the contributing factors of falls? (3) What are rural older adults’ perspectives of mitigation strategies to reduce falls?
JMIR Res Protoc 2025;14:e63716
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A qualitative methodology allows us to gather participants’ perceptions in an unbiased way, and especially to recognize the reasons for these perceptions to enhance understanding [26,27]. The exchange in focus groups and the stimulus given can trigger responses and allow participants to build on ideas that might not have come up in individual interviews [28].
J Med Internet Res 2025;27:e70487
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Beliefs and perceptions of the virus’s spread and control were partially adapted from the World Health Organization (WHO) resources. Specifically, some of the questions were adapted from the COVID-19 rapid quantitative assessment tool [8,9]. Three main perception themes were explored: perceived facilitators for the spread of the virus (6 items), perceived inhibitors (7 items), and risk labeling (8 items), as well as sociodemographic variables, including access to communication resources.
JMIR Form Res 2025;9:e66751
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Authors’ Reply: Citation Accuracy Challenges Posed by Large Language Models
We appreciate the thoughtful critique of our manuscript “Perceptions and earliest experiences of medical students and faculty with Chat GPT in medical education: qualitative study” [1] by Zhao and Zhang [2]. Concerns over the generation of hallucinated citations by large language models (LLMs), such as Open AI’s Chat GPT, Google’s Gemini, and Hangzhou’s Deep Seek, warrant exploring advanced and novel methodologies to ensure citation accuracy and overall output integrity [3].
JMIR Med Educ 2025;11:e73698
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Citation Accuracy Challenges Posed by Large Language Models
In the recent study titled “Perceptions and earliest experiences of medical students and faculty with Chat GPT in medical education: qualitative study,” the section addressing concerns about Chat GPT deserves a deeper discussion [1].
There are several reasons for the citation issues in LLMs, which can be analyzed as follows. First, most LLMs cannot access paid subscription databases and therefore solely rely on open-access resources [2].
JMIR Med Educ 2025;11:e72998
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