OBJECTIVE: This scientometric investigation aims to examine collaborative research networks, dominant research themes and disciplines, and seminal research studies that have contributed most to the field of telemedicine. This information is vital for scientists, institutions, and policy stakeholders to evaluate research areas where more infrastructural or scholarly contributions are required.
METHODS: For analyses, we used CiteSpace (version 4.0 R5; Drexel University), which is a Java-based software that allows scientometric analysis, especially visualization of collaborative networks and research themes in a specific field.
RESULTS: We found that scholarly activity has experienced a significant increase in the last decade. Most important works were conducted by institutions located in high-income countries. A discipline-specific shift from radiology to telestroke, teledermatology, telepsychiatry, and primary care was observed. The most important innovations that yielded a collaborative influence were reported in the following medical disciplines, in descending order: public environmental and occupational health, psychiatry, pediatrics, health policy and services, nursing, rehabilitation, radiology, pharmacology, surgery, respiratory medicine, neurosciences, obstetrics, and geriatrics.
CONCLUSIONS: Despite a continuous rise in scholarly activity in telemedicine, we noticed several gaps in the literature. For instance, all the primary and secondary research central to telemedicine was conducted in the context of high-income countries, including the evidence synthesis approaches that pertained to implementation aspects of telemedicine. Furthermore, the research landscape and implementation of telemedicine infrastructure are expected to see exponential progress during and after the COVID-19 era.
AIMS: To systematically identify and summarize the available literature on whether the modifiable risk factors associated with prediabetes displays similar relationship in both the genders.
METHODS: A systematic search was performed on electronic databases i.e. PubMed, EBSCOhost, and Scopus using "sex", "gender", "modifiable risk factors" and "prediabetes" as keywords. Reference list from identified studies was used to augment the search strategy. Methodological quality and results from individual studies were summarized in tables.
RESULTS: Gender differences in the risk factor association were observed among reviewed studies. Overall, reported association between risk factors and prediabetes apparently stronger among men. In particular, abdominal obesity, dyslipidemia, smoking and alcohol drinking habits were risk factors that showed prominent association among men. Hypertension and poor diet quality may appear to be stronger among women. General obesity showed stringent hold, while physical activity not significantly associated with the risk of prediabetes in both the genders.
CONCLUSIONS: Evidence suggests the existence of gender differences in risk factors associated with prediabetes, demands future researchers to analyze data separately based on gender. The consideration and the implementation of gender differences in health policies and in diabetes prevention programs may improve the quality of care and reduce number of diabetes prevalence among prediabetic subjects.
Method: A cross-sectional study involving a convenience sampling of 125 documented migrant workers from five selected countries was conducted. A researcher-administered questionnaire consisting of socio-demographic questions, three-day 24-hour dietary recall (3DR), and nine-item Household Food Insecurity Access Scale was used. Anthropometric measurements, including body weight, height, and waist circumference, were taken.
Findings: About 57.6% of the households studied were food insecure (24.8% mildly, 29.6% moderately, and 3.2% severely). Burmese were found to have the highest rate of household food insecurity (96%). The majority of the migrant workers were of normal weight (68.0%). No significant relationship was found between monthly household income and household food security status (p = 0.475), as well as between household food security status and weight status (p = 0.535).
Conclusion: Results imply that food security status affects certain nutrient intake among migrant workers. There were no significant associations between variables. Interventions focusing on nutritional education on food choices and implementation on health policy are recommended. Further studies should consider the accessibility, nutritional-related diseases, and dietary aspects of migrant workers, which are risk factors for food insecurity.