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Making sense of implementation theories, models and frameworks

Overview of attention for article published in Implementation Science, April 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#6 of 1,807)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Citations

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2470 Dimensions

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5059 Mendeley
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3 CiteULike
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Title
Making sense of implementation theories, models and frameworks
Published in
Implementation Science, April 2015
DOI 10.1186/s13012-015-0242-0
Pubmed ID
Authors

Per Nilsen

Abstract

Implementation science has progressed towards increased use of theoretical approaches to provide better understanding and explanation of how and why implementation succeeds or fails. The aim of this article is to propose a taxonomy that distinguishes between different categories of theories, models and frameworks in implementation science, to facilitate appropriate selection and application of relevant approaches in implementation research and practice and to foster cross-disciplinary dialogue among implementation researchers. Theoretical approaches used in implementation science have three overarching aims: describing and/or guiding the process of translating research into practice (process models); understanding and/or explaining what influences implementation outcomes (determinant frameworks, classic theories, implementation theories); and evaluating implementation (evaluation frameworks). This article proposes five categories of theoretical approaches to achieve three overarching aims. These categories are not always recognized as separate types of approaches in the literature. While there is overlap between some of the theories, models and frameworks, awareness of the differences is important to facilitate the selection of relevant approaches. Most determinant frameworks provide limited "how-to" support for carrying out implementation endeavours since the determinants usually are too generic to provide sufficient detail for guiding an implementation process. And while the relevance of addressing barriers and enablers to translating research into practice is mentioned in many process models, these models do not identify or systematically structure specific determinants associated with implementation success. Furthermore, process models recognize a temporal sequence of implementation endeavours, whereas determinant frameworks do not explicitly take a process perspective of implementation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 321 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5,059 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 16 <1%
United States 12 <1%
Netherlands 5 <1%
Canada 5 <1%
Malaysia 3 <1%
Denmark 3 <1%
Spain 3 <1%
Indonesia 2 <1%
Italy 1 <1%
Other 12 <1%
Unknown 4997 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 870 17%
Student > Ph. D. Student 826 16%
Researcher 635 13%
Student > Doctoral Student 432 9%
Other 245 5%
Other 967 19%
Unknown 1084 21%
Readers by discipline Count As %
Medicine and Dentistry 791 16%
Nursing and Health Professions 744 15%
Social Sciences 710 14%
Psychology 365 7%
Business, Management and Accounting 234 5%
Other 875 17%
Unknown 1340 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 238. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 February 2024.
All research outputs
#157,877
of 25,369,304 outputs
Outputs from Implementation Science
#6
of 1,807 outputs
Outputs of similar age
#1,633
of 279,642 outputs
Outputs of similar age from Implementation Science
#2
of 54 outputs
Altmetric has tracked 25,369,304 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,807 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 279,642 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 54 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.