collaboration: Introducing the ASAP scheme
6.9 Interrelations between ASAP institutionalization, relational network structures, network size and relational network structures, network size and
age, and network context
Finally, interrelations between the networks’ ASAP scores, different types of network structures and network context, as introduced above, were assessed.
First of all, by relating the networks’ ASAP scores with Brößkamp-Stone’s relational net-work structures, data suggest that netnet-works with higher levels of institutionalization had better been able to grow since the networks’ ASAP score highly correlates with their size (Kendall’s tau_b = .53, p < 1%) (compare Figure 30 below).
Figure 30: The association between the networks’ ASAP scores and their size (N=28)
If assessing interrelations between the ASAP dimensions and size in more detail, size was found to specifically interrelate with the second ASAP dimension, i.e. with the network’ coordina-tion structures and resources: First of all, there were clear interrelacoordina-tions between network size / coverage and the networks’ governance types. While self-governed networks (networks with a low degree of institutionalized network governance) remained clearly below the median val-ues both with regard to their absolute size and their coverage of potential member organiza-tions, lead organization-governed networks had the highest relative coverage, and network administrative organization-governed networks had the highest absolute membership figures (compare Figure 31 below).
Figure 31: Relations between network size, coverage of potential network members, and network governance type (N=28)
y = 0,0612x + 4,7445 R² = 0,3793 0
2 4 6 8 10 12
0 20 40 60 80 100 120
ASAP score
Network size
5
16
26,5 1
75
50 0 20 40 60 80
Self-goverened (n=7)
Lead organization-governed (n=15)
Network Administrative Organization (n=6)
Median size Median coverage
Findings suggest that, within the national / regional HPH networks, lead organization-governed networks were predominant in smaller and medium-sized countries and regions (which explains their high median coverage of potential members), while larger countries tended to develop networks governed by network administrative organizations. Furthermore, size was also found to strongly interrelate with the networks’ number of coordination struc-tures in place (Kendall’s tau_b = .44, p < 1%), indicating that bigger networks provided better conditions for implementing differentiated coordination structures. And, still pertaining to the second ASAP dimension, according to Mann-Whitney rank sum tests, network size signifi-cantly increased three dimensions of network resources, i.e. network budgets, the existence of a formal network office, and the number of full-time equivalents working for the networks:
Budgets: According to Cohen’s scale of effect size (Cohen 1988), a strong effect size (Kendall’s tau_b =.40, p < 1%) was detected between the amount of the network budget and network size. Bigger networks were more likely to charge a membership fee. Networks with no budget had a median size of only 6 members, as opposed to a median size of 22 members in networks with a dedicated budget (sig. = .000 according to a Mann-Whitney rank sum test).
The existence of a formal office: The 12 networks with an explicit office were characterized by a median size of 26.5 members, those without a dedicated office by a median size of 7.5 members. The mean rank difference in size between the two groups was signifi-cant according to a Mann-Whitney test (sig. = .003). Findings can be interpreted in two ways: Either an explicit network office allows handling a higher number of net-work members; or a specified office makes sense only for bigger netnet-works.
Number of full-time equivalents (FTEs) in office staff: Networks with more than the median number of 0.8 FTEs (which was observed in the total PRICES-HPH network sample) had, according to a Mann-Whitney test a significantly higher median number of mem-bers than networks with less FTEs (38.5 memmem-bers versus 7.5 memmem-bers; sig. = .000).Another strong correlation existed – not surprisingly – between the networks’ ASAP scores and the involvement of their members in decision-taking (Kendall’s tau_b = .42; p < 5%), indicating that better institutionalized networks disposed of better means for participatory performance (compare Figure 32 below).
Figure 32: The association between ASAP scores and decision involvement in the networks (N=28)
y = 0,054x + 3,8585 R² = 0,3211 0
2 4 6 8 10 12
0 20 40 60 80 100
ASAP score
Decision involvement
The interrelation between the networks’ ASAP sores and the connectedness between net-work members (operationalized as the percentage of netnet-work members having stated that they were using peer support in the network) had, according to Cohen’s scale, still medium effect size (Kendall’s tau_b = .35, p<5%) (compare Figure 33 below).
Figure 33: The association between the networks’ ASAP scores and their connectedness (N=28)
A comparable effect size existed between the networks’ ASAP sore and the complexity of the networks (operationalized as the number of network sub-structures) (Kendall’s tau_b
= .36, p<5%) (compare Figure 34 below).
Figure 34: The association between the networks’ ASAP scores and their complexity (N=28)
Overall, the ASAP score of the networks appeared rather independently of their age (Ken-dall’s tau_b = .12) (compare also Figure 35 below) – implying that the formalized institutional-ization of the networks does not necessarily increase over time.
Figure 35: The association between the networks’ ASAP scores and network age (N=28) y = 0,0337x + 3,9541
R² = 0,1838 0
5 10 15
0 20 40 60 80 100 120
ASAP score
Connectedness
y = 0,5317x + 5,6658 R² = 0,1464 0
2 4 6 8 10 12
0 2 4 6 8
ASAP score
Complexity
y = 0,0938x + 5,1031 R² = 0,0227 0
2 4 6 8 10 12
0 5 10 15 20
ASAP score
Age
If analyzing interrelations between network age and the networks’ ASAP scores in more detail, by taking the median age of 12.5 years as the cut-point between younger and older net-works, data indicate that one fifth of older networks had not been able to develop differentiat-ed network structures in their more than 12.5 years of existence (compare Figure 36 below).
Figure 36: Differences in 3 types of network governance between networks aged above and below the median of 12.5 years (figures in %) (N=28)
Last but not least, interrelations between the networks’ ASAP scores and their relevant en-vironments were assessed. There were no significant differences in scores between networks with and without legal frameworks (sig. = .114) or funding options (sig. = .975) for health promotion in healthcare according to Mann-Whitney rank sum tests. The number of offers by the international HPH network utilized by the national / regional HPH networks was found to be moderately but not significantly associated with the networks’ ASAP scores (Kendall’s tau_b = .25).
28,6
64,3
7,1 21,4
42,9
42,9 0 20 40 60 80 Self-goverened
(n=7) Lead organization-governed (n=15)
NAO-governed (n=6)
Age below median Age above median