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Table 2 Implementation Science Centers for Cancer Control (ISC3) Year 1 collaboration network descriptive characteristics

From: Collaboration networks of the implementation science centers for cancer control: a social network analysis

Network characteristic

All collaboration activities

Planning/conducting research

Capacity building

Product development

Scientific dissemination

Practice/policy dissemination

N

192

190

190

173

185

149

Ties

2480

1470

1336

825

654

284

 % cross-center

33.0

11.7

31.0

48.1

23.5

6.0

Median degree (range)

22 (2, 89)

15 (1, 48)

10 (1, 58)

6 (1, 45)

5 (1, 30)

2 (1, 22)

 Within-center

17 (2, 50)

13 (1, 44)

7 (1, 48)

4 (1, 25)

4 (1, 25)

2 (1, 21)

 Cross-center

7 (1, 56)

3 (1, 17)

3 (1, 43)

5 (1, 40)

2 (1, 20)

1 (1, 4)

Density (%)a

13.5

8.2

7.4

5.5

3.8

2.6

Betweenness centralizationb

0.07

0.12

0.13

0.11

0.23

0.20

Degree centralizationb

0.33

0.17

0.23

0.21

0.12

0.12

Transitivityc

0.47

0.56

0.37

0.34

0.33

0.33

Isolates

0

2

2

19

7

43

  1. IS implementation science, NCI = National Cancer Institute
  2. aDensity is the ratio of the number of ties to the total number of possible ties in the network; often used to measure the overall connectivity of a network or degree of cohesion among a network of collaborators [0, 1]
  3. bCentralization is used to assess the extent of hierarchy in the network; extent that connections in the network are associated with a select few most central nodes in the network [0, 1]. Degree centralization is based on the number of connections (higher degree centralization=one or more nodes hold most of the connections), whereas betweenness centralization is used to measure the extent to which each network member represents a bridge or gatekeeper to others in the network (based on the number of connections or paths in the network an individual lies between, higher betweenness centralization=one or a few nodes responsible for holding the network together)
  4. cTransitivity is a measure of clustering [0, 1] with higher transitivity suggests that new ties are more likely to form between nodes that share a common collaborator (e.g., referred by an existing collaborator)