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

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

Perceived organization support factor	Reported programs often or always END that should have continued vs else (N = 353)^b				Reported programs often or always CONTINUE that should have ended (N = 347)^c
Perceived organization support factor	b (SE)	Wald	P-Value	Odds Ratio (95% CI)	b (SE)	Wald	P-Value	Odds Ratio (95% CI)
Awareness of EBDM	0.24	1.75	0.19	1.28 (0.89, 1.83)	−0.58	6.21	0.01	0.56 (0.36, 0.88)
EBDM Capacity	0.25	2.12	0.15	1.29 (0.92, 1.81)	−0.59	7.26	0.007	0.55 (0.36, 0.85)
Resource Availability	0.32	2.68	0.10	1.38 (0.94, 2.20)	−0.71	8.51	0.004	0.49 (0.30, 0.79)
Evaluation Capacity	0.27	2.98	0.08	1.31 (0.96, 1.79)	−0.67	12.06	0.005	0.51 (0.35, 0.75)
Climate Cultivation	0.36	2.74	0.10	1.44 (0.94, 2.21)	−0.96	12.10	0.005	0.39 (0.23, 0.66)
Partnerships that Support EBDM	0.15	0.57	0.45	1.16 (0.79, 1.69)	−0.48	4.37	0.04	0.62 (0.39, 0.97)
EBDM support overall (sum of 6)	−0.07 (0.50)	0.02	0.89	1.06 (0.99, 1.14)	−0.15 (0.05)	10.93	< 0.001	0.86 (0.79, 0.94)

^aA separate model was conducted for each mis-implementation type (dependent variable) and each EBDM factor (independent variable of interest)
^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
^cCONTINUING models were adjusted for jurisdiction population size, state, having a graduate degree in public health, and age group

ISSN: 1472-6963