The Wearable Internet of Medical Things (WIoMT) is a collective term for all wearable medical devices connected to the internet to facilitate the collection and sharing of health data such as blood pressure, heart rate, oxygen level, and more. Standard wearable devices include smartwatches and fitness bands. This evolving phenomenon due to the IoT has become prevalent in managing health and poses severe security and privacy risks to personal information. For better implementation, performance, adoption, and secured wearable medical devices, observing users' perception is crucial. This study examined users' perspectives of trust in the WIoMT while also exploring the associated security risks. Data analysed from 189 participants indicated a significant variance (R = 0.553) on intention to use WIoMT devices, which was determined by the significant predictors (95% Confidence Interval; < 0.05) perceived usefulness, perceived ease of use, and perceived security and privacy. These were found to have important consequences, with WIoMT users intending to use the devices based on the trust factors of usefulness, easy to use, and security and privacy features. Further outcomes of the study identified how users' security matters while adopting the WIoMT and provided implications for the healthcare industry to ensure regulated devices that secure confidential data.
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http://dx.doi.org/10.3390/ijerph20085519 | DOI Listing |
Lancet Reg Health Eur
March 2025
Faculty of Pharmacy and Medicine, Sapienza University, Rome, Italy.
Digital technologies can help support the health of migrants and refugees and facilitate research on their health issues. However, ethical concerns include security and confidentiality of information; informed consent; how to engage migrants in designing, implementing and researching digital tools; inequitable access to mobile devices and the internet; and access to health services for early intervention and follow-up. Digital technical solutions do not necessarily overcome problems that are political, social, or economic.
View Article and Find Full Text PDFBMC Med Ethics
January 2025
Klinic Community Health, Winnipeg, MB, Canada.
Background: This study explored the ethical issues associated with community-based HIV testing among African, Caribbean, and Black (ACB) populations in Canada, focusing on their perceptions of consent, privacy, and the management of HIV-related data and bio-samples.
Methods: A qualitative community-based participatory research (CBPR) approach was employed to actively engage ACB community members in shaping the research process. The design included in-depth qualitative interviews with 33 ACB community members in Manitoba, Canada.
Int J Med Inform
January 2025
Faculty of Health Sciences, Universitat Oberta de Catalunya, Barcelona, Spain.
Background: The COVID-19 pandemic greatly challenged health systems worldwide. The adoption and application of mHealth technology emerged as a critical response. However, the permanent implementation and use of such technology faces several barriers, which vary by each country's innovation level and specific health policies.
View Article and Find Full Text PDFEJIFCC
December 2024
National Reference Laboratory, Abu Dhabi, UAE.
Background: An increasing number of wearable medical devices are being used for personal monitoring and professional health care purposes. These mobile health devices collect a variety of biometric and health data but do not routinely connect to a patient's electronic health record (EHR) or electronic medical record (EMR) for access by a patient's health care team.
Methods: The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Committee on Mobile Health and Bioengineering in Laboratory Medicine (C-MHBLM) developed consensus recommendations for consideration when interfacing mobile health devices to an EHR/EMR.
Brain Inform
January 2025
Department of Computing, Glasgow Caledonian University, Glasgow, G4 0BA, Scotland.
A digital twin is a virtual model of a real-world system that updates in real-time. In healthcare, digital twins are gaining popularity for monitoring activities like diet, physical activity, and sleep. However, their application in predicting serious conditions such as heart attacks, brain strokes and cancers remains under investigation, with current research showing limited accuracy in such predictions.
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