A total of 182 participants completed the survey (95% response rate; 91-100% across centers). ISC3 network member characteristics are reported in Table 1. Most participants reported their primary discipline as public health (54.4%) or medicine (24.2%). More than two-thirds (69.8%) of members reported 10+ years of experience in their field. The most prevalent network roles were faculty (60.4%) and center staff (23.6%). The largest proportion of members reported intermediate (41.8%), followed by beginner (35.2%) and advanced (23.1%) IS expertise. Most members identified as female (68.7%) and white (78.7%).
Table 1
Implementation Science Centers for Cancer Control (ISC3) Year 1 network participant characteristics (n=182).
|
Participant Characteristics
|
Characteristic
|
n (%)
|
Discipline
|
|
Public health
|
99 (54.4)
|
Medicine
|
44 (24.2)
|
Othera
|
39 (21.4)
|
Experience in field
|
|
< 5 years
|
18 (9.9)
|
5-9 years
|
37 (20.3)
|
10-15 years
|
56 (30.8)
|
> 15 years
|
71 (39.0)
|
Role
|
|
Trainee
|
12 (6.6)
|
Staff
|
43 (23.6)
|
Faculty
|
110 (60.4)
|
NCI staff
|
11 (6.0)
|
Otherb
|
6 (3.3)
|
Implementation science expertise level
|
|
Beginner
|
64 (35.2)
|
Intermediate
|
76 (41.8)
|
Advanced
|
42 (23.1)
|
Gender identityc
|
|
Female
|
125 (68.7)
|
Male
|
56 (30.8)
|
Racial/ethnic backgroundd
|
|
White
|
140 (78.7)
|
Asian
|
18 (10.1)
|
Black or African American
|
11 (6.2)
|
Hispanic or Latino
|
5 (2.8)
|
Other
|
4 (2.2)
|
a Examples of other disciplines include psychology, social work, economics, health services research, and implementation science. |
b Examples of other roles included consultants and advisors. |
c n=181 |
d n=178 |
Network Characteristics
Ten survey non-respondents were nominated as collaborators by responders and included in the full network. With all collaboration activities combined, the ISC3 network included 192 members and 2480 collaboration ties, of which members had a median of 22 connections (Table 2). Figure 1 displays the network for all collaboration activities combined and Figure 2 displays the network for each collaboration type. The practice/policy dissemination network was the smallest network with 143 of the 192 ISC3 network members represented, whereas the other networks ranged from 173-190 members. The greatest number of ties were reported in planning/conducting research (1470 ties; median 15 ties/member) and the fewest ties were reported in practice/policy dissemination (284 ties; median 2 ties/member). For all collaboration activities, density, or the ratio of the number of ties to the total number of possible ties in the network, was 13.5%. Across the different collaboration types, the most and least densely connected networks were planning/conducting research (8.2%) and practice/policy dissemination (2.6%), respectively.
Table 2
Implementation Science Centers for Cancer Control (ISC3) Year 1 collaboration network descriptive characteristics.
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
|
IS = implementation science; NCI = National Cancer Institute. |
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]. |
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). |
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). |
The overall ISC3 network was fairly decentralized (degree centralization=0.33 and betweenness centralization=0.07; Table 2), consistent with Figure 1’s basic linked local network shape (no strong central node or group of nodes). For separate activities, capacity building and product development had the highest degree centralization (0.23 and 0.21, respectively) compared to other collaboration activities, which ranged from 0.12 to 0.17, suggesting influential positions for some members in these networks (“hub and spoke” network structure). Scientific dissemination and practice/policy dissemination networks had the highest betweenness centralization (0.23 and 0.20, respectively), suggesting some members may be closer to each other and/or are more easily connected or reached. As more connections “pass” through these central members, their removal would result in a high number of isolates (those with no connections).
Overall, the ISC3 network’s transitivity (0.47) suggests the heightened probability of triangles in the network, though variation exists across collaboration types. Planning/conducting research had the highest transitivity measure (0.56) compared to all other collaboration networks (transitivity range: 0.33 to 0.37), suggesting that two investigators that are collaborating with the same investigator are likely to also be collaborating with each other.
One-third of all collaboration ties (33.0%) occurred between members from different centers. We observed the largest proportion of cross-center collaboration in product development (48.1%), which includes involvement with cross-center workgroups. Collaboration on practice/policy dissemination and planning/conducting research mostly occurred within members’ respective centers (6.0% and 11.7% cross-center ties, respectively). Network members had a median of 17 connections within their center and 7 connections from other centers across all activities.
There were no isolates for the all collaboration activities network because our overall network was derived from having at least one collaboration activity reported. Notably, practice/policy dissemination and product development were the two activity networks with the largest number of isolates (n=43 and n=19, respectively). Half of the ISC3 trainees (n=6) were not connected in product development.
Member connectedness by role, IS expertise, and racial/ethnic background
The number of connections (degree) varied significantly across ISC3 roles in all collaboration activities combined (χ2 = 10.59(4), p=0.032) with NCI staff having the highest median degree in all activities combined (28 (range: 6-65) ties), followed by faculty (24 (4-89) ties) (Figure 3) (Additional File 2). Degree also varied significantly by role for planning/conducting research (χ2 = 27.94(4), p=<0.001), capacity building (χ2 = 11.97(4), p=0.018), product development (χ2 = 10.06(4), p=0.039), scientific dissemination (χ2 = 11.31(4), p=0.023), and practice/policy dissemination (χ2 = 12.10(4), p = 0.017).
Members with advanced IS expertise were more connected in all networks (Additional File 2); these individuals are shown in Figures 1-2 as nodes with a black border. Median degree varied significantly across IS expertise levels in all collaboration activities combined (χ2 = 34.42(2), p=<0.001) and in four of the five activity networks: planning/conducting research (χ2 = 15.74(2), p=<0.001), capacity building (χ2 = 34.17(2), p=<0.001), product development (χ2 = 20.21(2), p=<0.001), and in scientific dissemination (χ2 = 40.80(2), p=<0.001) (Figure 4).
Degree varied significantly across racial/ethnic backgrounds in all collaboration activities combined (χ2 = 13.14(4), p=0.011), planning/conducting research (χ2 = 25.52(4), p=<0.001), scientific dissemination (χ2 = 22.50(4), p=<0.001) (Figure 5). Hispanic or Latino network members were most connected in all collaborations (32 (24-45) ties) followed by white members (23.5 (4-89) ties). Black or African American members were least connected (13 (5-50) ties) (Additional File 2).