e.g. mhealth
Search Results (1 to 4 of 4 Results)
Download search results: CSV END BibTex RIS
Skip search results from other journals and go to results- 3 JMIR mHealth and uHealth
- 1 JMIR Public Health and Surveillance
- 0 Journal of Medical Internet Research
- 0 Medicine 2.0
- 0 Interactive Journal of Medical Research
- 0 iProceedings
- 0 JMIR Research Protocols
- 0 JMIR Human Factors
- 0 JMIR Medical Informatics
- 0 JMIR Serious Games
- 0 JMIR Mental Health
- 0 JMIR Rehabilitation and Assistive Technologies
- 0 JMIR Preprints
- 0 JMIR Bioinformatics and Biotechnology
- 0 JMIR Medical Education
- 0 JMIR Cancer
- 0 JMIR Challenges
- 0 JMIR Diabetes
- 0 JMIR Biomedical Engineering
- 0 JMIR Data
- 0 JMIR Cardio
- 0 JMIR Formative Research
- 0 Journal of Participatory Medicine
- 0 JMIR Dermatology
- 0 JMIR Pediatrics and Parenting
- 0 JMIR Aging
- 0 JMIR Perioperative Medicine
- 0 JMIR Nursing
- 0 JMIRx Med
- 0 JMIRx Bio
- 0 JMIR Infodemiology
- 0 Transfer Hub (manuscript eXchange)
- 0 JMIR AI
- 0 JMIR Neurotechnology
- 0 Asian/Pacific Island Nursing Journal
- 0 Online Journal of Public Health Informatics
- 0 JMIR XR and Spatial Computing (JMXR)
Projections of Climate Change Impact on Acute Heat Illnesses in Taiwan: Case-Crossover Study
In response to global warming, Taiwan has established a real-time epidemic surveillance and early warning system to monitor acute heat illnesses since January 1, 2011 [8]. Instead of reporting past cases of acute heat illnesses, projecting their future number of acute heat illnesses is crucial for developing prevention strategies and health service planning [9,10]. However, predicting the number of acute heat illnesses requires forecasting temperature changes that are influenced by adaptation policies.
JMIR Public Health Surveill 2024;10:e57948
Download Citation: END BibTex RIS
The measurements of WBGT and heat index were categorized using the reference values according to Parsons [12] and the National Weather Service [13]. We employed unadjusted linear regression and multilinear regression analyses [4,8,29-32] considering factors such as maximum daily and minimal nighttime heat and heavy rainfall. The multilinear models further considered gender, age, and BMI as confounders.
JMIR Mhealth Uhealth 2024;12:e54669
Download Citation: END BibTex RIS
The overarching objective of this observational study was to examine the impact of heat and heavy rainfall on the population’s health in rural Burkina Faso using consumer-grade wearables. Specifically, we captured daily activity, sleep, and HR using a wearable in a sample of the Nouna HDSS population. Our primary objectives were to study the relationships between (1) daily activity and heat and heavy rain, (2) nighttime sleep duration and heat and heavy rain, and (3) HR and heat and heavy rain.
JMIR Mhealth Uhealth 2023;11:e46980
Download Citation: END BibTex RIS
Wearables for Measuring Health Effects of Climate Change–Induced Weather Extremes: Scoping Review
In recent years, some reviews have been conducted on the assessment of heat strain and individual heat exposure using wearable devices. However, these studies have mainly focused on urban and occupational heat exposure [10,11], although populations living in low- and middle-income countries and rural settings have a high vulnerability to climate change [12].
JMIR Mhealth Uhealth 2022;10(9):e39532
Download Citation: END BibTex RIS