جستجوی مقالات مرتبط با کلیدواژه « تحلیل هم رخدادی واژگان » در نشریات گروه « پزشکی »

It is necessary to study the emerging trends and areas of knowledge and to predict the direction of future research on the concept of health literacy in order to promote community health. Therefore, this study was conducted with the aim of mapping research knowledge in the field of health literacy and showing the structure of knowledge and their evolution over time.

This scientometrics research was conducted using Co-word analysis technique includes the steps include: Data retrieval, Data analysis and Mapping and Visualization Papers from the MEDLINE database during (1970-2018) retrieved and analyzed. The bibliographic data analyzed using the visualization of similarities technique by text‑mining and visualization techniques of VOSviewer.

A total of 7,429 documents, growth of scientific publications related to the field of health literacy has been increased rapidly over the past 10 years and continues to grow in recent years. The stronger studies were mainly conducted at research institutions of higher education in the Canada and United States. Four Core authors groups with a higher influence were identified. The keyword of “communication”, “depression”, “health education”, and “internet” had respectively the highest frequency. The results of cluster analysis identified and categorized them into three major clusters. Health literacy field had a close relationship with the lifestyle dimensions, health information technology, mental health literacy and chronic diseases.

Given the interdisciplinary nature of health literacy the areas of education, health, Information Communication Technology (ICT) science, and mental health will help the cooperation of experts in these areas to enrich scientific research and make them more applicable.

Topic evolutions of scientific and academic disciplines can be clarified by drawing scientific maps and identifies emerging or developed topics of scientific disciplines, sub-topics and the relationship between different topics of a discipline. The purpose of this study is to draw a strategic diagram to analyze the developments of the last twenty years of library and information science field.

This was a Scientometrics study with co-occurrence analysis of words that was conducted on ten journals with the highest impact factor in the field of library and information science. Twenty years (1998-2017) publications were extracted from LISTA database and imported into SciMAT software. After preparing the data, all publications were divided into four time periods, strategic diagrams of each period were drawn and topic clusters were analyzed

The largest clusters of the first two periods were “Information Retrieval” and “Bibliometrics”, which in the next period “Citation-Analysis” appeared instead of “Information Retrieval” cluster, but nevertheless the largest node of this cluster was “Information Retrieval”. These clusters were the most developed topics in the field of library and information science

Information retrieval and bibliometrics are at the forefront of library and information science. Sentiment analysis and information literacy with a cognitive approach are emerging topics in the field. Also, studies related to information production and related indicators have led to qualitative research.

Due to the high prevalence of depression and the considerable pressure it puts on individuals, society and healthcare system, it is essential to conduct sufficient research to help with decision making in prevention, treatment and control of this condition. To assist with research planning and setting priorities, this paper aimed to identify the thematic structure of papers related to depression treatment.
This was an applied research study which used Scientometrics approach. To obtain data, the keyword “Depression” was searched as a mesh descriptor with the subdivision “Therapy” in PubMed database for the period of 2005 to 2014. The data were analyzed using co-word and clustering methods with the help of Excel and SPSS software packages.
The growth of scientific production in this field appeared to have been balanced throughout the ten-year period examined in the study. The most active research areas for the two five year periods (2005-2009 and 2010-2014) were drug therapy, psychology, and medication adherence. Two hierarchical graphs of descriptors for each five-year period were prepared both of which were composed of 12 clusters with 34 common descriptors.
The findings based on the inclusion index showed that only 20 percent of topics in the second five-year period of the study were novel. Therefore, it could be concluded that research areas that were related with each other in previous years will probably co-occur with other topics in the future might disappear. In every discipline, some topics are considered to be fundamental and research works are being carried out on them almost every year.

A considerable amount of research is conducted in the area of depression therapy from all over the world. Exploration of the relationships between title keywords of the papers provides helpful information for researchers. The aim of this paper is to draw up scientific maps for this research area in PubMed.
This research is conducted based on scientometrics approaches. It uses the techniques of co-word analysis and social network analysis to identify conceptual relationship between papers related to the field of depression therapy. Using Ravar Matrix, Ucinet and Netdraw software packages, 6, 172 papers related to the treatment of depression in PubMed were analyzed during the period from 2005 to 2014.
Findings: The subject areas of Medication adherence and Suicidal ideation were identified as the most prevalent new and emerging topics in this field. Results of Closeness and Between Centrality indicators, revealed that the greatest value is related to the topics of »Psychology, Drug Therapy, and Anti-depressive Agents«.
According to the findings, Drug Therapy, Psychology, Anti-depressive agents, and Treatment outcome are the most active research areas. Scientific maps help users and policy makers get a better understanding of the structure of a research area, explore the research status of a field and make plans to improve the quality and quantity of scientific products.