e.g. mhealth
Search Results (1 to 10 of 74 Results)
Download search results: CSV END BibTex RIS
Skip search results from other journals and go to results- 18 Journal of Medical Internet Research
- 14 JMIR Formative Research
- 11 JMIR Public Health and Surveillance
- 5 JMIRx Med
- 4 Interactive Journal of Medical Research
- 4 JMIR Aging
- 3 JMIR Human Factors
- 3 JMIR Medical Informatics
- 2 JMIR Medical Education
- 2 JMIR Mental Health
- 2 JMIR Research Protocols
- 2 JMIR mHealth and uHealth
- 1 JMIR Cancer
- 1 JMIR Infodemiology
- 1 JMIR Pediatrics and Parenting
- 1 JMIR Serious Games
- 0 Medicine 2.0
- 0 iProceedings
- 0 JMIR Rehabilitation and Assistive Technologies
- 0 JMIR Preprints
- 0 JMIR Bioinformatics and Biotechnology
- 0 JMIR Challenges
- 0 JMIR Diabetes
- 0 JMIR Biomedical Engineering
- 0 JMIR Data
- 0 JMIR Cardio
- 0 Journal of Participatory Medicine
- 0 JMIR Dermatology
- 0 JMIR Perioperative Medicine
- 0 JMIR Nursing
- 0 JMIRx Bio
- 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)
For further subgroup analyses, the 7-day mean of registrations was stratified by age and gender. Age was divided into two categories: patients being younger than 65 years of age or aged 65 years and older. The latter group is particularly important because adults older than 65 years of age were defined as high-risk groups for severe COVID-19 disease progression [17,18]. The analysis was again performed by comparison of graphs, but also differences in registration rate between the time periods.
J Med Internet Res 2025;27:e56961
Download Citation: END BibTex RIS
Both surveys provide detailed reports on the use of illicit and nonillicit drugs, disaggregated by age, gender, race, and ethnicity at a national level. In addition to these national surveys, various individual studies [16,24] have also explored SU disparities across demographics such as age, gender, race, and ethnicity.
While these surveys offer valuable insights, their scope is often limited by the diversity of true populations and the duration of the studied period.
JMIR Infodemiology 2025;5:e67333
Download Citation: END BibTex RIS
As model inputs, we used the patient’s age, gender, and all prior recorded vital signs, laboratory values, medications, and prior CAM assessments present in the medical record at 5 AM before the 24 hours in which delirium was to be predicted. Categorical values were converted to integers (eg, “1” for “Positive,” “0” for “Negative”).
JMIR Med Inform 2025;13:e60442
Download Citation: END BibTex RIS
Care preferences were also examined relative to potential predictors of care use: gender, race, age, (self and public) stigma, discrimination, and level of shame.
J Med Internet Res 2025;27:e54608
Download Citation: END BibTex RIS
Age brackets also differed in how they expressed happiness [13]. Other research studies have also shown differences between demographic groups in the factors associated with happiness levels [14,15].
As noted earlier, sex influences the sources of happiness. Age, marital status, and parenthood status also influence the sources of happiness. The effects of age and marital status would also appear to interact with sex to influence the importance of individual sources of happiness [14].
JMIR Form Res 2025;9:e65658
Download Citation: END BibTex RIS
Extracting comorbidities for an index condition based on age, gender, and other features required intensive computation power and storage capacity when dynamic linking the patient and clinical tables. The same challenge was seen for other data analyses.
J Med Internet Res 2025;27:e52385
Download Citation: END BibTex RIS
HF is generally associated with advancing age and has the highest readmission rates among all chronic diseases, adding to the increase in health care costs [2,12]. As such, effective and efficient management of HF using both pharmacological and nonpharmacological methods is essential.
As a nonpharmacological method, exercise training interventions have been shown to decrease hospitalizations, increase exercise capacity, and improve quality of life [13].
J Med Internet Res 2025;27:e54524
Download Citation: END BibTex RIS
In our previously published cross-sectional population survey, performed during the first wave of the pandemic, we found high self-reported adherence to official restrictions, which increased with age and level of worry [20]. As in the aforementioned studies, worry was high, particularly among people in isolation and with lower health literacy. Nearly half of the respondents felt that government responses were adequate or, associated with higher levels of worry, even insufficient.
Interact J Med Res 2025;14:e55636
Download Citation: END BibTex RIS
For male individuals, the search percentages across different age groups were highest for “Pilates,” “yoga,” “muscle training,” “exercise bike,” “walking,” “running,” and “hiking” in the 40-49 years age group. “Stretch” showed the highest search percentage in the 50-59 years group, whereas “tai chi” and “radio calisthenics” were the highest in the 70-79 years group.
JMIR Form Res 2024;8:e59395
Download Citation: END BibTex RIS
RA is the most common rheumatic disease with a global age-standardized point prevalence and annual incidence rates of 246.6 and 14.9 per 100,000 population in 2017 [2]. RA is associated with high medical costs [3] and contributes to a significant deterioration in quality of life [4]. Patients in rural areas usually have limited access to rheumatology care and therefore, accept longer diagnosis times [5].
J Med Internet Res 2024;26:e47733
Download Citation: END BibTex RIS