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目的尝试运用社会网络分析法研究社区静脉注射吸毒者(IDUs)交往的社会网络结构的可行性和特点。方法采用提名法,收集2013年主动参加针具交换的IDUs和其帮助交换针具的其他吸毒人员名单,根据结果建立社区IDUs交往的无向矩阵数据库,选择社会网络分析(SNA)常用的分析指标,并使用UCINET 6.212软件分析社区IDUs的社会组织结构特点,使用NetDraw对矩阵数据进行可视化处理。结果 2013年,共有69人参与针具交换活动,其中有65人提名其帮助交换针具的IDUs姓名,占94.20%(65/69)。参与调查的IDUs合计参与针具交换活动261次,累计提名410人,平均每次交换活动提名1.57人,公安在册和不在册IDUs平均每次提名1.59人和1.44人。结点中心度、接近中心度和中间中心度的最高两个数量级行动者占的比例分别为4.38%(14/320)、2.19%(7/320)和1.56%(5/320);整体网络密度为0.0077。成分分析显示,整个被调查群体分为三个独立群体,三个群体的行动者占整个群体比例为98.13%、1.25%和0.63%。派系分析显示,整个群体分为20个派系,派系之间存在共享成员的比例为85.00%。结论通过SNA调查方法和计算机软件,可以将日常收集的工作信息用于研究社区IDUs的交往网络。社区IDUs之间绝大部分存在相互关联,但IDUs之间交往程度低,整个网络受到少数人控制或影响。社区IDUs的交往网络与毒品流通有直接关系。可利用以上特点制定相应公共卫生干预策略、方式和提高干预效果。
Objective To explore the feasibility and characteristics of using social network analysis to study the social network structure of community drug users (IDUs). Methods The nominating method was used to collect IDUs actively participating in needle exchange in 2013 and other drug addicts who helped to exchange needles. According to the results, an undirected matrix database of community IDUs was established and the commonly used analytical indicators of social network analysis (SNA) And analyzed the social organizational structure of community IDUs using UCINET 6.212 software and visualized matrix data using NetDraw. Results In 2013, a total of 69 participants participated in needle exchange activities, of which 65 nominated IDUs whose names helped to exchange needles, accounting for 94.20% (65/69). IDUs involved in the survey totally participated in needle exchange activities for 261 times, with a total of 410 nominations, with an average of 1.57 nominees for each exchange event. On average, 1.59 and 1.44 people were nominated respectively by public security registered and non-registered IDUs. The proportions of the top two orders of magnitude actors with node center, center of approach and center of center were 4.38% (14/320), 2.19% (7/320) and 1.56% (5/320), respectively. The overall network The density is 0.0077. The component analysis shows that the surveyed population is divided into three independent groups, with the three groups accounting for 98.13%, 1.25% and 0.63% of the total population. Faction analysis shows that the entire group is divided into 20 factions, the proportion of factions sharing between members is 85.00%. Conclusion Using SNA survey methodology and computer software, routinely collected work information can be used to study the social network of community IDUs. Most of the interdependencies exist between community IDUs, but the degree of engagement between IDUs is low and the entire network is controlled or influenced by a few people. The community of community IDUs has a direct relationship with drug circulation. The above characteristics can be used to formulate corresponding public health intervention strategies, methods and enhance the effectiveness of interventions.