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Building the community: Endogenous network formation, homophily and prosocial sorting among therapeutic community residents.
Drug and Alcohol Dependence ( IF 3.9 ) Pub Date : 2019-11-26 , DOI: 10.1016/j.drugalcdep.2019.107773
Keith Warren 1 , Benjamin Campbell 2 , Skyler Cranmer 2 , George De Leon 3 , Nathan Doogan 4 , Mackenzie Weiler 2 , Fiona Doherty 1
Affiliation  

BACKGROUND Researchers have begun to consider the ways in which social networks influence therapeutic community (TC) treatment outcomes. However, there are few studies of the way in which the social networks of TC residents develop over the course of treatment. METHODOLOGY We used a Temporal Exponential Random Graph Model (TERGM) to analyze changes in social networks totaling 320,387 peer affirmations exchanged between residents in three correctional TCs, one of which serves men and two of which serve both men and women. The networks were analyzed within weekly and monthly time-frames. RESULTS Within a weekly time-frame residents tended to close triads. Residents who were not previously connected tended not to affirm the same peers. Residents showed homophily by entry cohort. Other results were inconsistent across TC units. Within a monthly time-frame participants showed homophily by graduation status. They showed the same patterns of triadic closure when connected, tendency not to affirm the same peers when not connected and homophily by cohort entry time as in a weekly time frame. CONCLUSIONS TCs leverage three human tendencies to bring about change. The first is the tendency of cooperators to work together, in this case in seeking graduation. The second is the tendency of people to build clusters. The third is homophily, in this case by cohort entry time. Consistent with TC clinical theory, residents spread affirmations to a variety of peers when they have no previous connection. This suggests that residents balance network clustering with a concern for the community as a whole.

中文翻译:


建设社区:治疗社区居民之间的内源网络形成、同质性和亲社会排序。



背景研究人员已经开始考虑社交网络影响治疗社区(TC)治疗结果的方式。然而,关于 TC 居民的社交网络在治疗过程中发展方式的研究很少。方法 我们使用时态指数随机图模型 (TERGM) 来分析社交网络的变化,三个惩教 TC 的居民之间总共交换了 320,387 个同伴肯定信息,其中一个为男性服务,另外两个为男性和女性服务。在每周和每月的时间范围内对网络进行分析。结果 在每周的时间内,居民倾向于关闭三合会。以前没有联系过的居民往往不会肯定相同的同伴。居民在入境队列中表现出同质性。其他结果在 TC 单位之间不一致。在每月的时间范围内,参与者的毕业状况表现出同质性。他们在连接时表现出相同的三重封闭模式,在未连接时倾向于不确认相同的同伴,并且按队列进入时间与每周时间范围内的同质性。结论 TC 利用人类的三种倾向来带来变革。第一个是合作者共同努力的倾向,在本例中是为了寻求毕业。二是人们建立集群的倾向。第三个是同质性,在本例中是按队列进入时间。与 TC 临床理论一致,当居民以前没有联系时,他们会向各种同龄人传播肯定。这表明居民平衡网络集群与对整个社区的关注。
更新日期:2019-11-27
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