| Literature DB >> 30841888 |
Karishma S Furtado1, Elizabeth L Budd2, Rebecca Armstrong3, Tahna Pettman3, Rodrigo Reis4, Pauline Sung-Chan5, Zhaoxin Wang6, Ross C Brownson4,7.
Abstract
BACKGROUND: Mis-implementation (i.e., the premature termination or inappropriate continuation of public health programs) contributes to the misallocation of limited public health resources and the sub-optimal response to the growing global burden of chronic disease. This study seeks to describe the occurrence of mis-implementation in four countries of differing sizes, wealth, and experience with evidence-based chronic disease prevention (EBCDP).Entities:
Keywords: Chronic disease; Dissemination and implementation; Evidence-based chronic disease prevention; Evidence-based public health; Mis-implementation
Mesh:
Year: 2019 PMID: 30841888 PMCID: PMC6404329 DOI: 10.1186/s12889-019-6591-x
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Differences in Participant and Agency Characteristics by Country
| Australia | Brazil | China | United States | Chi-Sq | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Characteristic | % | n | % | n | % | n | % | n | ||
| Participant Demographics | ||||||||||
| Female | 88.4% | 107 | 65.8% | 50 | 71.7% | 71 | 87.1% | 88 | 32.9 |
|
| Age | 89.0 |
| ||||||||
| 21–29 | 20.7% | 25 | 8.2% | 6 | 21.6% | 22 | 6.9% | 7 | ||
| 30–39 | 33.1% | 40 | 38.4% | 28 | 56.9% | 58 | 21,8% | 22 | ||
| 40–49 | 14.9% | 18 | 31.5% | 23 | 10.8% | 11 | 28.7% | 29 | ||
| 50–59 | 20.7% | 25 | 21.1% | 16 | 3.9% | 4 | 28.7% | 29 | ||
| 60+ | 10.7% | 13 | 3.9% | 3 | 0.0% | 0 | 10.9% | 11 | ||
| Missing | 0.0% | 0 | 0.0% | 0 | 6.7% | 7 | 3.0% | 3 | ||
| Education/Credentials | 92.5 |
| ||||||||
| Doctorate | 14.2% | 17 | 4.0% | 3 | 0.0% | 0 | 6.9% | 7 | ||
| Master’s | 42.5% | 51 | 32.0% | 24 | 23.5% | 24 | 48.5% | 49 | ||
| Bachelor’s | 30.0% | 36 | 22.7% | 17 | 68.6% | 70 | 27.8% | 28 | ||
| Other | 13.3% | 16 | 41.3% | 31 | 7.8% | 8 | 15.8% | 16 | ||
| Missing | 0.8% | 1 | 1.3% | 1 | 0.0% | 0 | 1.0% | 1 | ||
| Primary Position | ||||||||||
| Physician | 37.2% | 45 | 1.3% | 1 | 2.9% | 3 | 41.6% | 42 | 77.4 |
|
| Community Health Nurse | 3.3% | 4 | 13.2% | 10 | 43.1% | 44 | 7.9% | 8 | 73.8 |
|
| Department Head | 5.0% | 6 | 28.9% | 22 | 5.9% | 6 | 14.9% | 15 | 30.2 |
|
| Nutritionist | 0.8% | 1 | 9.2% | 7 | 40.2% | 41 | 0.0% | 0 | 103.5 |
|
| Statistician | 15.7% | 19 | 26.3% | 20 | 3.9% | 4 | 1.0% | 1 | 36.5 |
|
| Health Educator | 13.2% | 16 | 2.6% | 2 | 2.0% | 2 | 18.8% | 19 | 22.5 |
|
| Division of Bureau Head/Deputy Director | 0.0% | 0 | 11.8% | 9 | 0.0% | 0 | 10.9% | 11 | 26.6 |
|
| Program Manager/Administrator/Coordinator | 9.1% | 11 | 1.3% | 1 | 0.0% | 0 | 0.0% | 0 | 22.4 |
|
| Academic Research | 9.1% | 11 | 0.0% | 0 | 0.0% | 0 | 0.0% | 0 | 26.1 |
|
| Other | 1.6% | 2 | 5.2% | 4 | 2.0% | 2 | 2.1% | 3 | 6.9 |
|
| Missing | 5.0% | 6 | 0.0% | 0 | 0.0% | 0 | 2.0% | 2 | 4.2 |
|
| Agency Features | ||||||||||
| Number of Employees | 83.8 |
| ||||||||
| 0–100 | 37.7% | 43 | 38.0% | 27 | 9.8% | 10 | 56.4% | 57 | ||
| 101–400 | 20.2% | 23 | 28.2% | 20 | 64.7% | 66 | 24.8% | 25 | ||
| > 400 | 42.1% | 48 | 33.8% | 24 | 21.6% | 22 | 17.8% | 18 | ||
| Missing | 5.8% | 7 | 6.7% | 5 | 3.9% | 4 | 1.0% | 1 | ||
| Size of Population Served | 127.0 |
| ||||||||
| 0–49,999 | 28.3% | 30 | 29.4% | 20 | 0.0% | 0 | 23.8% | 24 | ||
| 50,000-99,999 | 10.4% | 11 | 10.3% | 7 | 0.0% | 0 | 24.8% | 25 | ||
| 100,000-399,999 | 20.8% | 22 | 27.9% | 19 | 81.4% | 83 | 25.8% | 26 | ||
| > 400,000 | 40.6% | 43 | 32.4% | 22 | 18.6% | 19 | 23.8% | 24 | ||
| Missing | 12.3% | 15 | 10.5% | 8 | 0.0% | 0 | 2.0% | 2 | ||
Boldface indicates significant at alpha < 0.05
Differences in Knowledge of EBCDP, Mis-implementation, and Reasons Programs End and Continue by Country
| Australia | Brazil | China | United States | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Chi-Sq | ||||||||||
| Characteristic | % | n | % | n | % | n | % | n | ||
| Knowledgeable of EBCDP | 146.7 |
| ||||||||
| Not at all | 0.8% | 1 | 2.6% | 2 | 15.7% | 16 | 1.0% | 1 | ||
| Slightly | 4.2% | 5 | 2.6% | 2 | 31.4% | 32 | 2.0% | 2 | ||
| Somewhat | 20.2% | 24 | 32.9% | 25 | 32.4% | 33 | 14.9% | 15 | ||
| Moderately | 60.0% | 73 | 44.7% | 34 | 18.6% | 19 | 54.5% | 55 | ||
| Extremely | 15.0% | 18 | 17.1% | 13 | 2.0% | 2 | 27.7% | 28 | ||
| Mis-implementation | ||||||||||
| Frequency of Mis-Termination (Inappropriate Ending) | 148.4 |
| ||||||||
| Never | 1.7% | 2 | 2.6% | 2 | 12.2% | 12 | 1.0% | 1 | ||
| Sometimes | 31.6% | 38 | 39.5% | 30 | 36.7% | 37 | 51.5% | 52 | ||
| Often | 56.4% | 68 | 36.8% | 28 | 5.1% | 5 | 40.4% | 41 | ||
| Don’t Know | 9.4% | 11 | 10.5% | 8 | 45.9% | 47 | 7.1% | 7 | ||
| Missing | 1.7% | 2 | 10.5% | 8 | 1.0% | 1 | 0% | 0 | ||
| Frequency of Mis-Continuation (Inappropriate Continuation) | 241.1 |
| ||||||||
| Never | 1.7% | 2 | 10.5% | 8 | 11.0% | 11 | 5.9% | 6 | ||
| Sometimes | 0.0% | 0 | 60.5% | 46 | 33.0% | 34 | 19.8% | 20 | ||
| Often | 58.0% | 70 | 7.9% | 6 | 4.0% | 4 | 36.8% | 37 | ||
| Don’t Know | 37.8% | 46 | 14.5% | 11 | 52.0% | 53 | 34.5% | 35 | ||
| Missing | 2.5% | 3 | 6.6% | 5 | 0% | 0 | 3.0% | 3 | ||
| Reasons Programs End and Continue | ||||||||||
| Reasons Programs End (% of times in top 3)a | ||||||||||
| Grant funding ended | 63.6% | 77 | 43.4% | 33 | 24.5% | 25 | 84.2% | 85 | 80.8 |
|
| Funding diverted to a higher priority program | 31.4% | 38 | 31.6% | 24 | 20.6% | 21 | 36.6% | 37 | 6.6 | 0.085 |
| Change in political leadership | 50.4% | 61 | 47.4% | 36 | 8.8% | 9 | 11.9% | 12 | 73.2 |
|
| Program was evaluated but did not demonstrate impact | 22.3% | 27 | 21.1% | 16 | 42.2% | 43 | 9.9% | 10 | 30.0 |
|
| Opposition/lack of support from policy makers | 26.4% | 32 | 28.9% | 22 | 18.6% | 19 | 18.8% | 19 | 4.4 | 0.219 |
| Program was challenging to maintain | 9.9% | 12 | 10.5% | 8 | 48.0% | 49 | 20.8% | 21 | 55.6 |
|
| Program was never evaluated | 19.0% | 23 | 23.7% | 18 | 10.8% | 11 | 15.8% | 16 | 5.6 | 0.130 |
| Opposition/lack of support from the general public | 2.5% | 3 | 21.1% | 16 | 38.2% | 39 | 8.9% | 9 | 56.9 |
|
| Opposition/lack of support from leaders in my agency | 10.7% | 13 | 35.5% | 27 | 13.7% | 14 | 10.9% | 11 | 26.1 |
|
| A program champion departed | 22.3% | 27 | 25.0% | 19 | 5.9% | 6 | 9.9% | 10 | 19.1 |
|
| Program was expensive | 5.8% | 7 | 11.8% | 9 | 15.7% | 16 | 8.9% | 9 | 6.3 | 0.098 |
| Program was not evidence-based | 3.3% | 4 | 23.7% | 18 | 12.7% | 13 | 3.0% | 3 | 29.4 |
|
| Program was adopted or continued by other organizations | 4.1% | 5 | 2.6% | 2 | 2.0% | 2 | 13.9% | 14 | 16.9 |
|
| Insurance funding/coverage ended | 1.7% | 2 | 9.2% | 7 | 0.0% | 0 | 7.9% | 8 | 14.5 |
|
| Reasons Programs Continue (% of times in top 3)a | ||||||||||
| Sustained support from policymakers | 27.3% | 33 | 43.4% | 33 | 31.4% | 32 | 22.1% | 22 | 11.6 |
|
| Sustained funding | 28.1% | 34 | 39.5% | 30 | 36.3% | 37 | 35.6% | 36 | 3.2 | 0.358 |
| Sustained support from leaders in your agency | 27.3% | 33 | 18.4% | 14 | 35.3% | 36 | 24.8% | 25 | 6.7 | 0.084 |
| Absence of alternative options | 28.1% | 34 | 26.3% | 20 | 22.5% | 23 | 17.8% | 18 | 3.6 | 0.310 |
| Program was never evaluated | 33.1% | 40 | 35.5% | 27 | 8.8% | 9 | 16.8% | 17 | 27.1 |
|
| Sustained support from the general public | 15.7% | 19 | 21.1% | 16 | 37.3% | 38 | 15.8% | 16 | 18.7 |
|
| Program was easy to maintain | 24.0% | 29 | 18.4% | 14 | 21.6% | 22 | 23.8% | 24 | 1.0 | 0.799 |
| Presence of a program champion | 23.1% | 28 | 28.9% | 22 | 13.7% | 14 | 21.8% | 22 | 6.3 | 0.096 |
| Program was low-cost | 19.0% | 23 | 18.4% | 14 | 8.8% | 9 | 18.8% | 19 | 5.6 | 0.135 |
| Prohibitive costs of starting something new | 13.2% | 16 | 9.2% | 7 | 9.8% | 10 | 6.9% | 7 | 2.5 | 0.473 |
| Program was considered evidence-based | 10.7% | 13 | 3.9% | 3 | 16.7% | 17 | 6.9% | 7 | 9.3 |
|
Boldface indicates significant at alpha < 0.05
aThe original series of questions asked participants to select the three most frequent reasons from the lists above