Recent Articles
![Public Perceptions and Discussions of the US Food and Drug Administration's JUUL Ban Policy on Twitter: Observational Study Article Thumbnail](https://asset.jmir.pub/assets/edb6846c3eeb4fc54ee8fc5921ce4721.png 480w,https://asset.jmir.pub/assets/edb6846c3eeb4fc54ee8fc5921ce4721.png 960w,https://asset.jmir.pub/assets/edb6846c3eeb4fc54ee8fc5921ce4721.png 1920w,https://asset.jmir.pub/assets/edb6846c3eeb4fc54ee8fc5921ce4721.png 2500w)
![Predictive Model for Extended-Spectrum β-Lactamase–Producing Bacterial Infections Using Natural Language Processing Technique and Open Data in Intensive Care Unit Environment: Retrospective Observational Study Article Thumbnail](https://asset.jmir.pub/assets/cdacc733fa7526359575b3cc8f418a16.png 480w,https://asset.jmir.pub/assets/cdacc733fa7526359575b3cc8f418a16.png 960w,https://asset.jmir.pub/assets/cdacc733fa7526359575b3cc8f418a16.png 1920w,https://asset.jmir.pub/assets/cdacc733fa7526359575b3cc8f418a16.png 2500w)
Machine learning has advanced medical event prediction, mostly using private data. The public MIMIC-3 (Medical Information Mart for Intensive Care III) data set, which contains detailed data on over 40,000 intensive care unit patients, stands out as it can help develop better models including structured and textual data.
![Interactive Health Technology Tool for Kidney Living Donor Assessment to Standardize the Informed Consent Process: Usability and Qualitative Content Analysis Article Thumbnail](https://asset.jmir.pub/assets/757b7b2635816d2c3d2233a3e1b5efa2.png 480w,https://asset.jmir.pub/assets/757b7b2635816d2c3d2233a3e1b5efa2.png 960w,https://asset.jmir.pub/assets/757b7b2635816d2c3d2233a3e1b5efa2.png 1920w,https://asset.jmir.pub/assets/757b7b2635816d2c3d2233a3e1b5efa2.png 2500w)
![Patient and Provider Satisfaction With a Geomapping Tool for Finding Community Family Physicians in Ontario, Canada: Cross-Sectional Online Survey Study Article Thumbnail](https://asset.jmir.pub/assets/e9c053ae0caeae11cc848f242aeb5a85.png 480w,https://asset.jmir.pub/assets/e9c053ae0caeae11cc848f242aeb5a85.png 960w,https://asset.jmir.pub/assets/e9c053ae0caeae11cc848f242aeb5a85.png 1920w,https://asset.jmir.pub/assets/e9c053ae0caeae11cc848f242aeb5a85.png 2500w)
Language-concordant health care, or health care in a patient’s language of choice, is an important element of health accessibility that improves patient safety and comfort and facilitates an increased quality of care. However, prior research has found that linguistic minorities often face higher travel burdens to access language-concordant care compared to the general population.
![Evaluation of a Remote Patient Monitoring Program During the COVID-19 Pandemic: Retrospective Case Study With a Mixed Methods Explanatory Sequential Design Article Thumbnail](https://asset.jmir.pub/assets/8188e3c8d754f449fd57f42a559258a6.png 480w,https://asset.jmir.pub/assets/8188e3c8d754f449fd57f42a559258a6.png 960w,https://asset.jmir.pub/assets/8188e3c8d754f449fd57f42a559258a6.png 1920w,https://asset.jmir.pub/assets/8188e3c8d754f449fd57f42a559258a6.png 2500w)
Community health center (CHC) patients experience a disproportionately high prevalence of chronic conditions and barriers to accessing technologies that might support the management of these conditions. One such technology includes tools used for remote patient monitoring (RPM), the use of which surged during the COVID-19 pandemic.
![A Simple and Systematic Approach to Qualitative Data Extraction From Social Media for Novice Health Care Researchers: Tutorial Article Thumbnail](https://asset.jmir.pub/assets/42b1e8b415b1964ea39031cea9cb2cce.png 480w,https://asset.jmir.pub/assets/42b1e8b415b1964ea39031cea9cb2cce.png 960w,https://asset.jmir.pub/assets/42b1e8b415b1964ea39031cea9cb2cce.png 1920w,https://asset.jmir.pub/assets/42b1e8b415b1964ea39031cea9cb2cce.png 2500w)
Social media analyses have become increasingly popular among health care researchers. Social media continues to grow its user base and, when analyzed, offers unique insight into health problems. The process of obtaining data for social media analyses varies greatly and involves ethical considerations. Data extraction is often facilitated by software tools, some of which are open source, while others are costly and therefore not accessible to all researchers. The use of software for data extraction is accompanied by additional challenges related to the uniqueness of social media data. Thus, this paper serves as a tutorial for a simple method of extracting social media data that is accessible to novice health care researchers and public health professionals who are interested in pursuing social media research. The discussed methods were used to extract data from Facebook for a study of maternal perspectives on sudden unexpected infant death.
![Social Media Authentication and Users’ Assessments of Health Information: Random Assignment Survey Experiment Article Thumbnail](https://asset.jmir.pub/assets/36d0fbdc74da2f30eb315e3f5ebc816b.png 480w,https://asset.jmir.pub/assets/36d0fbdc74da2f30eb315e3f5ebc816b.png 960w,https://asset.jmir.pub/assets/36d0fbdc74da2f30eb315e3f5ebc816b.png 1920w,https://asset.jmir.pub/assets/36d0fbdc74da2f30eb315e3f5ebc816b.png 2500w)
In an effort to signal the authenticity of user accounts, social networking sites (SNSs) such as Facebook and X, formerly known as Twitter, use visual heuristics (blue checkmarks) to signify whether accounts are verified. While these verification badges are generally well recognized (and often coveted) by SNS users, relatively little is known about how they affect users’ perceptions of accuracy or their likelihood of engaging with web-based information. This is particularly true in the case of information posted by medical experts and health care professionals.
![A Novel mHealth App for Smokers Living With HIV Who Are Ambivalent About Quitting Smoking: Formative Research and Randomized Feasibility Study Article Thumbnail](https://asset.jmir.pub/assets/31d456e5e17493c3528f3a78d07bc140.png 480w,https://asset.jmir.pub/assets/31d456e5e17493c3528f3a78d07bc140.png 960w,https://asset.jmir.pub/assets/31d456e5e17493c3528f3a78d07bc140.png 1920w,https://asset.jmir.pub/assets/31d456e5e17493c3528f3a78d07bc140.png 2500w)
More people who smoke and are living with HIV now die from tobacco-related diseases than HIV itself. Most people are ambivalent about quitting smoking and want to quit someday but not yet. Scalable, effective interventions are needed to motivate and support smoking cessation among people ambivalent about quitting smoking (PAQS) who are living with HIV.
![Development of Promising Interventions to Improve Human Papillomavirus Vaccination in a School-Based Program in Quebec, Canada: Results From a Formative Evaluation Using a Mixed Methods Design Article Thumbnail](https://asset.jmir.pub/assets/3c4bc0052ae6aba9d8bb0714f0f56fad.png 480w,https://asset.jmir.pub/assets/3c4bc0052ae6aba9d8bb0714f0f56fad.png 960w,https://asset.jmir.pub/assets/3c4bc0052ae6aba9d8bb0714f0f56fad.png 1920w,https://asset.jmir.pub/assets/3c4bc0052ae6aba9d8bb0714f0f56fad.png 2500w)
Despite the availability of school-based human papillomavirus (HPV) vaccination programs, disparities in vaccine coverage persist. Barriers to HPV vaccine acceptance and uptake include parental attitudes, knowledge, beliefs, and system-level barriers. A total of 3 interventions were developed to address these barriers: an in-person presentation by school nurses, an email reminder with a web-based information and decision aid tool, and a telephone reminder using motivational interviewing (MI) techniques.
![Novel Methodology for Identifying the Occurrence of Ovulation by Estimating Core Body Temperature During Sleeping: Validity and Effectiveness Study Article Thumbnail](https://asset.jmir.pub/assets/66cf732015825d461a4c4937777b5c6a.png 480w,https://asset.jmir.pub/assets/66cf732015825d461a4c4937777b5c6a.png 960w,https://asset.jmir.pub/assets/66cf732015825d461a4c4937777b5c6a.png 1920w,https://asset.jmir.pub/assets/66cf732015825d461a4c4937777b5c6a.png 2500w)
![The Impact of Incentives on Data Collection for Online Surveys: Social Media Recruitment Study Article Thumbnail](https://asset.jmir.pub/assets/8db6bdc5a565a417c1b44d13c7fd1ced.png 480w,https://asset.jmir.pub/assets/8db6bdc5a565a417c1b44d13c7fd1ced.png 960w,https://asset.jmir.pub/assets/8db6bdc5a565a417c1b44d13c7fd1ced.png 1920w,https://asset.jmir.pub/assets/8db6bdc5a565a417c1b44d13c7fd1ced.png 2500w)
The use of targeted advertisements on social media platforms (eg, Facebook and Instagram) has become increasingly popular for recruiting participants for online survey research. Many of these surveys offer monetary incentives for survey completion in the form of gift cards; however, little is known about whether the incentive amount impacts the cost, speed, and quality of data collection.
![Capturing Home Care Information Management and Communication Processes Among Caregivers of Older Adults: Qualitative Study to Inform Technology Design Article Thumbnail](https://asset.jmir.pub/assets/7aad5387860ab7f4142b6964833a71da.png 480w,https://asset.jmir.pub/assets/7aad5387860ab7f4142b6964833a71da.png 960w,https://asset.jmir.pub/assets/7aad5387860ab7f4142b6964833a71da.png 1920w,https://asset.jmir.pub/assets/7aad5387860ab7f4142b6964833a71da.png 2500w)
The demand for complex home care is increasing with the growing aging population and the ongoing COVID-19 pandemic. Family and hired caregivers play a critical role in providing care for individuals with complex home care needs. However, there are significant gaps in research informing the design of complex home care technologies that consider the experiences of family and hired caregivers collectively.
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