Volume 19, Issue 66 (1-2017)                   jha 2017, 19(66): 47-60 | Back to browse issues page

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Makkizadeh F, Hazeri A, Mobasheri E. Subject Analysis of Articles Related to Addiction in Medline through Hierarchical Clustering From 1991-2014. jha. 2017; 19 (66) :47-60
URL: http://jha.iums.ac.ir/article-1-2098-en.html
1- Assistant Professor of Department of Information Science and Knowledge Studies School of Social Science, Yazd University, Yazd, Iran , makkizadeh@yahoo.com
2- Assistant Professor of Department of Information Science and Knowledge Studies School of Social Science, Yazd University, Yazd, Iran
3- MA Student of Scientometrics School of Social Science, Yazd University, Yazd, Iran
Abstract:   (1006 Views)

Introduction: Addiction, which has recently attracted the attention of researchers, is a serious problem worldwide. The growth of relevant literature contributes to a better understanding of this problem and improves the interaction between executive organizations and academic institutions. It is important to identify the active subject areas within this field and to explore the topics which are more frequently discussed in research documents using techniques of subject clustering analysis. The main purpose of this paper is to do a content analysis of papers related to addiction in PubMed through hierarchical clustering.

Methods: This is a descriptive and applied research analyzing the content of literature through hierarchical clustering. To obtain data, a search for the keyword “Addiction” as a Mesh term in PubMed was conducted, on 21/04/2015, for papers published in 1991-2014. Descriptors were extracted from the papers retrieved, and data were analyzed using Ravar Matrix and SPSS 20.

Results: According to the findings, the size of scientific literature in the area of addiction increased during the period under the study. Subject clustering led to the identification of most widely used topics, including substance related disorders, addictions to the Internet, gambling, smoking, etc.

Conclusion: Through thematic analysis of documents (descriptors), a wide range of dispersed topics were grouped into six clusters.  The members of each cluster had common characteristics and they were structurally interrelated. The main concern of researchers, as indicated by descriptors in these six clusters, were on psychological aspects of the issue.

Full-Text [PDF 2061 kb]   (888 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/04/4 | Accepted: 2016/12/13 | Published: 2016/12/13

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