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Psychological and Behavioral Insights From Social Media Users: Natural Language Processing-Based Quantitative Study on Mental Well-Being.
JMIR Form Res
January 2025
Smith School of Business, Queen's University, Kingston, ON, Canada.
Background: Depression significantly impacts an individual's thoughts, emotions, behaviors, and moods; this prevalent mental health condition affects millions globally. Traditional approaches to detecting and treating depression rely on questionnaires and personal interviews, which can be time consuming and potentially inefficient. As social media has permanently shifted the pattern of our daily communications, social media postings can offer new perspectives in understanding mental illness in individuals because they provide an unbiased exploration of their language use and behavioral patterns.
View Article and Find Full Text PDFIdentifying Fraudulent Responses in a Study Exploring Delivery Options for Pregnancies Impacted by Gestational Diabetes: Lessons Learned From a Web-Based Survey.
J Med Internet Res
January 2025
Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada.
Current literature is unclear on the safety and optimal timing of delivery for pregnant individuals with gestational diabetes mellitus, which inspired our study team to conduct a web-based survey study exploring patient and provider opinions on delivery options. However, an incident of fraudulent activity with survey responses prompted a shift in the focus of the research project. Unfortunately, despite the significant rise of web-based surveys used in medical research, there remains very limited evidence on the implications of and optimal methods to handle fraudulent web-based survey responses.
View Article and Find Full Text PDFA New Smartphone-Based Cognitive Screening Battery for Multiple Sclerosis (icognition): Validation Study.
J Med Internet Res
January 2025
AIMS Lab, Center for Neurosciences, Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel, Brussels, Belgium.
Background: Cognitive deterioration is common in multiple sclerosis (MS) and requires regular follow-up. Currently, cognitive status is measured in clinical practice using paper-and-pencil tests, which are both time-consuming and costly. Remote monitoring of cognitive status could offer a solution because previous studies on telemedicine tools have proved its feasibility and acceptance among people with MS.
View Article and Find Full Text PDFDeveloping a Machine Learning-Based Automated Patient Engagement Estimator for Telehealth: Algorithm Development and Validation Study.
JMIR Form Res
January 2025
Department of Computer Science, Purdue University, West Lafayett, IN, United States.
Background: Patient engagement is a critical but challenging public health priority in behavioral health care. During telehealth sessions, health care providers need to rely predominantly on verbal strategies rather than typical nonverbal cues to effectively engage patients. Hence, the typical patient engagement behaviors are now different, and health care provider training on telehealth patient engagement is unavailable or quite limited.
View Article and Find Full Text PDFThe Canadian Genomics Research and Development Initiative for Antimicrobial Resistance (GRDI-AMR) uses a genomics-based approach to understand how health care, food production and the environment contribute to the development of antimicrobial resistance. Integrating genomics contextual data streams across the One Health continuum is challenging because of the diversity in data scope, content and structure. To better enable data harmonization for analyses, a contextual data standard was developed.
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