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. 2020 Jan 12;10(1):e033227. doi: 10.1136/bmjopen-2019-033227

Table 6.

Multilevel models predicting change in knowledge and related quotes

Knowledge (ICC=0.44)
Model 1 Model 2 Model 3
Intercept 6.92* 5.97* 6.37*
Time 0.41* 0.42*
Group −0.62
σ2 e 1.39* 1.10* 1.10*
σ2 u0 1.12* 1.20* 1.11*
−2*log(lh) 497.62 474.3 471.8
df 3 4 5
Δ2*log(lh) 23.3* 2.5
Δdf 1 1
Pseudo R1 2 0.21
Pseudo R2 2 0.01
Interview quotes
Quote 4 ID9: … I have become more conscious and more structured concerning what I need to think about when working through the different steps [of the implementation], and also the clarification of what behavior it is that I want to change.
Quote 5 ID1: It is not a failure that it didn’t go well… //…like, okay, we tried something, oh well—let’s try again, and in this way you can proceed. So, it [the action plan for the implementation] is not finished when you launch it.
Quote 6 ID7: //…the leading aspect is somehow something you can learn; to implement something new without having to have deep knowledge of the particular [implementation case]…then I can feel more confident in managing restructurings. //…previously when I have been manager and implemented quality registries…//…I think I lost myself in the content [of the implementation] in some way…//

Table entries represent unstandardised parameter estimates. Individual level: n=128–140, group level: n=42. Time is centred at WS1/2; intervention group is coded 0=intervention group 1 and 1=intervention group 2.

*P<.05.

ICC, intraclass correlation coefficient.