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| http://dx.doi.org/10.1016/S1473-3099(23)00185-8 | DOI Listing |
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Psychological and Behavioral Insights From Social Media Users: Natural Language Processing-Based Quantitative Study on Mental Well-Being.
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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 PDFDevelopment of an eHealth Intervention Including Self-Management for Reducing Sedentary Time in the Transition to Retirement: Participatory Design Study.
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Division of Psychology, School of Health, Care and Social Welfare, Mälardalen University, Västerås/Eskilstuna, Sweden.
Background: Having a great amount of sedentary time is common among older adults and increases with age. There is a strong need for tools to reduce sedentary time and promote adherence to reduced sedentary time, for which eHealth interventions have the potential to be useful. Interventions for reducing sedentary time in older adults have been found to be more effective when elements of self-management are included.
View Article and Find Full Text PDFDeveloping a Machine Learning-Based Automated Patient Engagement Estimator for Telehealth: Algorithm Development and Validation Study.
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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 PDFApplication of the 6-SNP elevated LDL-cholesterol polygenic risk score in individuals with familial hypercholesterolemia phenotype from an Argentine population.
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January 2025
Universidad de Buenos Aires, Facultad de Farmacia y Bioquímica, Departamento de Bioquímica Clínica, Laboratorio de Lípidos y Aterosclerosis, Ciudad Autónoma de Buenos Aires.
Introduction: LDL-cholesterol greater than 190 mg/dL indicates severe hypercholesterolemia (HS) of monogenic and/or polygenic origin. Genetic risk scores (GRS) evaluate potential polygenic causes.
Objective: we applied a GRS of 6-SNP (GRS-6) in HS individuals.
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