What Types of Networks Do Professionals Build, and How Are They Affected by the Results of Network Evaluation?
What Types of Networks Do Professionals Build, and How Are They Affected by the Results of Network Evaluation?
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DOI：
10.3389/fpubh.2021.758809
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发表时间：
2021
影响因子：
5.2
通讯作者：
Tsugawa S
中科院分区：
文献类型：
--
作者：
Haruta J;Tsugawa S
背景：我们的目的是探索社区中的医疗保健专业人员之间建立了什么样的以“咨询/被咨询”为特征的社交网络，以及向专业人员提供这些发现的影响。方法：我们采用社会网络分析（SNA）和内容分析的混合方法探索性研究。 SNA 可以可视化社交网络结构，例如个体之间的关系。医疗保健专业人员被问及他们咨询过的关键人物以及就这些医疗保健问题接受咨询的人：（1）日常工作； (2)患有急性腰痛的人； （三）邻居举报的房屋堆满垃圾的； (4) 痴呆症患者； （五）学习会。我们根据使用 SNA 的问题确定了关键角色。分析后，与参与者分享分析结果。为了探索他们的认知反应，我们提供了一份开放式问卷并进行了内容分析。结果：在 54 名医疗保健专业人员参与者中，其中 52 名的数据可供分析。结果（按上述五个主题的顺序排列）如下：节点数为165、95、85、82、68；聚类系数分别为0.19、0.03、0.02、0.11、0.23；配型性为-0.043、-0.11、-0.23、-0.17和-0.23；互易值为0.35、0.31、0.39、0.29和0.48。排名前三位的中心人物包括护士。共收到 87 条免费评论，其中 39 条属于描述性评论，10 条属于分析性评论，38 条属于批判性评论。讨论：“咨询/被咨询”网络的结构因主题而异。 SNA 可用于检测医疗资源网络，这可能有助于他们反思自己的网络。
Background: We aimed to explore what kind of social networks characterizable as “consult/be consulted” are built among healthcare professionals in a community and the impact of providing the professionals with these findings. Methods: We adopted mixed methods exploratory study using social network analysis (SNA) and content analysis. SNA can visualize social network structures such as relationships between individuals. The healthcare professionals were asked about the key persons they consulted and were consulted by concerning these healthcare issues: (1) daily work; (2) a person with acute back pain; (3) a garbage-filled house reported by a neighbor; (4) a person with dementia; and (5) a study meeting. We identified the key roles depending on the issues using SNA. After analysis, the analytical findings were shared with the participants. To explore their cognitive responses, an open-ended questionnaire was delivered and a content analysis was implemented. Results: Of 54 healthcare professional participants, the data of 52 were available for analysis. The findings (in the respective order of the five topics above) were as follows: the number of nodes was 165, 95, 85, 82, and 68; clustering coefficient was 0.19, 0.03, 0.02, 0.11, and 0.23; assortativity was −0.043, −0.11, −0.23, −0.17, and −0.23; reciprocity was 0.35, 0.31, 0.39, 0.29, and 0.48. The top three centralities included nurses. Eighty-seven free comments were received, of which 39 were categorized as descriptive, 10 as analytical, and 38 as critical. Discussion: The structure of “consult/be consulted” networks differed by topic. SNA is available to detect the healthcare resources network and it may have helped them to reflect on their own networks.
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影响因子：
2.7
作者：
Yao N;Zhu X;Dow A;Mishra VK;Phillips A;Tu SP
通讯作者：
Tu SP
影响因子：
1.7
作者：
Bidart, Claire;Charbonneau, Johanne
通讯作者：
Charbonneau, Johanne
DOI：
10.1186/s13012-016-0381-y
发表时间：
2016-02-11
期刊：
Implementation science : IS
影响因子：
--
作者：
Long JC;Hibbert P;Braithwaite J
通讯作者：
Braithwaite J
影响因子：
1.7
作者：
Marin, Alexandra;Hampton, Keith N.
通讯作者：
Hampton, Keith N.
影响因子：
3.4
作者：
Chan, Bosco;Reeve, Emily;Hilmer, Sarah N.
通讯作者：
Hilmer, Sarah N.