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Table 3 Adjusted odds ratios of reporting mis-implementation by organizational supports, in separate multivariate logistic regression modelsa

From: Perspectives on program mis-implementation among U.S. local public health departments

Perceived organization support factorReported programs often or always END that should have continued vs else (N = 353)bReported programs often or always CONTINUE that should have ended (N = 347)c
b (SE)WaldP-ValueOdds Ratio (95% CI)b (SE)WaldP-ValueOdds Ratio (95% CI)
Awareness of EBDM0.241.750.191.28 (0.89, 1.83)−0.586.210.010.56 (0.36, 0.88)
EBDM Capacity0.252.120.151.29 (0.92, 1.81)−0.597.260.0070.55 (0.36, 0.85)
Resource Availability0.322.680.101.38 (0.94, 2.20)−0.718.510.0040.49 (0.30, 0.79)
Evaluation Capacity0.272.980.081.31 (0.96, 1.79)−0.6712.060.0050.51 (0.35, 0.75)
Climate Cultivation0.362.740.101.44 (0.94, 2.21)−0.9612.100.0050.39 (0.23, 0.66)
Partnerships that Support EBDM0.150.570.451.16 (0.79, 1.69)−0.484.370.040.62 (0.39, 0.97)
EBDM support overall (sum of 6)−0.07 (0.50)0.020.891.06 (0.99, 1.14)−0.15 (0.05)10.93< 0.0010.86 (0.79, 0.94)
  1. aA separate model was conducted for each mis-implementation type (dependent variable) and each EBDM factor (independent variable of interest)
  2. bENDING models were adjusted for: Jurisdiction population size, state, having a local board of health, having a graduate degree in any field, having a nursing background, and years worked in public health
  3. cCONTINUING models were adjusted for jurisdiction population size, state, having a graduate degree in public health, and age group