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Table 1 Local health department practitioners’ importance and availability ratings of ten evidence-based decision making (EBDM) competencies

From: Capacity building for evidence-based decision making in local health departments: scaling up an effective training approach

 

Control (n = 214)

Intervention (n = 82)

Intervention effect b (SE)†

Pre mean

Post mean

Pre mean

Post mean

Unadjusted

Adjusted

Prioritization: Understand how to prioritize program and policy options.

 

Importance

8.8

9.2

9.1

9.1

-0.42

(0.19)*

-0.24

(0.21)

 

Availability

6.8

7.5

6.4

7.2

0.09

(0.32)

0.22

(0.37)

 

Gap

2.0

1.7

2.7

1.9

-0.51

(0.34)

-0.46

(0.40)

Adapting interventions: Understand how to modify programs and policies for different communities and settings.

 

Importance

8.7

8.8

9.1

9.0

-0.28

(0.22)

-0.21

(0.25)

 

Availability

6.3

6.9

5.9

6.6

0.17

(0.31)

0.35

(0.35)

 

Gap

2.4

1.9

3.2

2.4

-0.44

(0.34)

-0.56

(0.39)

Evaluation designs: Understand the different designs that are useful in program or policy evaluation.

 

Importance

8.1

8.4

8.7

8.8

-0.15

(0.22)

-0.17

(0.25)

 

Availability

5.5

6.0

5.2

6.3

0.63

(0.34)

0.78

(0.39)*

 

Gap

2.6

2.4

3.5

2.5

-0.78

(0.37)*

-0.95

(0.42)*

Quantifying the issue: Understand the uses of descriptive epidemiology (e.g., concepts of person, place, time) in quantifying a public health issue.

 

Importance

8.4

8.8

8.5

8.8

-0.10

(0.21)

0.03

(0.25)

 

Availability

6.8

6.9

6.2

7.0

0.69

(0.35)*

0.78

(0.39)*

 

Gap

1.6

1.9

2.3

1.8

-0.80

(0.37)*

-0.78

(0.42)

Quantitative evaluation: Understand the uses of quantitative evaluation approaches (e.g. surveillance, surveys).

 

Importance

8.4

8.8

8.8

8.9

-0.27

(0.19)

-0.25

(0.22)

 

Availability

6.8

7.1

6.8

7.3

0.16

(0.33)

0.48

(0.38)

 

Gap

1.6

1.7

2.0

1.6

-0.43

(0.35)

-0.73

(0.40)

Qualitative evaluation: Understand the value of qualitative evaluation approaches (e.g. focus groups, key informant interviews) including the steps involved in conducting qualitative evaluations.

 

Importance

8.0

8.3

8.5

8.8

-0.03

(0.23)

0.03

(0.26)

 

Availability

6.1

6.5

6.2

6.8

0.18

(0.33)

0.32

(0.38)

 

Gap

1.9

1.8

2.3

2.0

-0.22

(0.35)

-0.29

(0.40)

Action planning: Understand the importance of developing an action plan for how to achieve goals and objectives.

 

Importance

8.9

9.1

9.3

9.3

-0.20

(0.17)

-0.06

(0.19)

 

Availability

7.2

7.5

7.0

8.0

0.77

(0.31)*

0.98

(0.35)**

 

Gap

1.7

1.6

2.3

1.3

-0.97

(0.29)**

-1.04

(0.34)**

Community assessment: Understand how to define the health issue according to the needs and assets of the population/community of interest.

 

Importance

8.9

9.2

9.4

9.5

-0.21

(0.17)

-0.14

(0.19)

 

Availability

7.2

7.6

7.4

7.7

-0.06

(0.29)

0.02

(0.34)

 

Gap

1.7

1.6

2.0

1.8

-0.15

(0.30)

-0.16

(0.35)

Communicating research to policy makers: Understand the importance of effectively communicating with policy makers about public health issues.

 

Importance

8.8

9.0

9.1

9.2

-0.20

(0.20)

-0.19

(0.23)

 

Availability

6.2

6.4

5.2

6.3

0.88

(0.35)*

0.86

(0.41)*

 

Gap

2.6

2.6

3.9

2.9

-1.08

(0.39)**

-1.05

(0.45)*

Economic evaluation: Understand how to use economic data in the decision making process.

 

Importance

8.6

8.7

9.0

8.8

-0.32

(0.20)

-0.35

(0.23)

 

Availability

5.6

5.6

4.9

5.1

0.24

(0.36)

0.65

(0.41)

 

Gap

3.0

3.1

4.1

3.7

-0.56

(0.38)

-1.00

(0.43)*

Mean of all 10 EBDM competencies

 

Importance

8.5

8.8

8.9

9.0

-0.22

(0.13)

-0.15

(0.15)

 

Availability

6.4

6.8

6.1

6.8

0.37

(0.22)

0.55

(0.25)*

 

Gap

2.1

2.0

2.8

2.2

-0.59

(0.23)*

-0.70

(0.27)**

  1. Importance and Availability scores measured on 0-10 scale (greater scores = greater importance/availability); Gap = Importance-Availability.
  2. †Unstandardized regression parameter estimate (b) and standard error (SE) for group assignment (Intervention = 1, Control = 0) in simple linear regression model (unadjusted) and multivariate linear regression model (adjusted for job position, population of jurisdiction, highest degree, gender, age, years of public health experience, state); outcome variable is difference score (posttest - pretest); **p-value ≤ 0.01 *p-value ≤0.05.
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Implementation Science

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