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A systematic review of the use of the Consolidated Framework for Implementation Research

Overview of attention for article published in Implementation Science, May 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

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Title
A systematic review of the use of the Consolidated Framework for Implementation Research
Published in
Implementation Science, May 2016
DOI 10.1186/s13012-016-0437-z
Pubmed ID
Authors

M. Alexis Kirk, Caitlin Kelley, Nicholas Yankey, Sarah A. Birken, Brenton Abadie, Laura Damschroder

Abstract

In 2009, Damschroder et al. developed the Consolidated Framework for Implementation Research (CFIR), which provides a comprehensive listing of constructs thought to influence implementation. This systematic review assesses the extent to which the CFIR's use in implementation research fulfills goals set forth by Damschroder et al. in terms of breadth of use, depth of application, and contribution to implementation research. We searched Scopus and Web of Science for publications that cited the original CFIR publication by Damschroder et al. (Implement Sci 4:50, 2009) and downloaded each unique result for review. After applying exclusion criteria, the final articles were empirical studies published in peer-review journals that used the CFIR in a meaningful way (i.e., used the CFIR to guide data collection, measurement, coding, analysis, and/or reporting). A framework analysis approach was used to guide abstraction and synthesis of the included articles. Twenty-six of 429 unique articles (6 %) met inclusion criteria. We found great breadth in CFIR application; the CFIR was applied across a wide variety of study objectives, settings, and units of analysis. There was also variation in the method of included studies (mixed methods (n = 13); qualitative (n = 10); quantitative (n = 3)). Depth of CFIR application revealed some areas for improvement. Few studies (n = 3) reported justification for selection of CFIR constructs used; the majority of studies (n = 14) used the CFIR to guide data analysis only; and few studies investigated any outcomes (n = 11). Finally, reflections on the contribution of the CFIR to implementation research were scarce. Our results indicate that the CFIR has been used across a wide range of studies, though more in-depth use of the CFIR may help advance implementation science. To harness its potential, researchers should consider how to most meaningfully use the CFIR. Specific recommendations for applying the CFIR include explicitly justifying selection of CFIR constructs; integrating the CFIR throughout the research process (in study design, data collection, and analysis); and appropriately using the CFIR given the phase of implementation of the research (e.g., if the research is post-implementation, using the CFIR to link determinants of implementation to outcomes).

X Demographics

X Demographics

The data shown below were collected from the profiles of 63 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 1,212 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 <1%
United Kingdom 1 <1%
Sierra Leone 1 <1%
Canada 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 1206 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 212 17%
Student > Master 169 14%
Student > Ph. D. Student 163 13%
Student > Doctoral Student 90 7%
Other 64 5%
Other 216 18%
Unknown 298 25%
Readers by discipline Count As %
Medicine and Dentistry 213 18%
Nursing and Health Professions 167 14%
Social Sciences 165 14%
Psychology 92 8%
Business, Management and Accounting 27 2%
Other 183 15%
Unknown 365 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 40. 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 01 December 2021.
All research outputs
#1,048,556
of 25,765,370 outputs
Outputs from Implementation Science
#152
of 1,821 outputs
Outputs of similar age
#18,849
of 343,429 outputs
Outputs of similar age from Implementation Science
#2
of 41 outputs
Altmetric has tracked 25,765,370 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,821 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 91% 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 343,429 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 94% of its contemporaries.
We're also able to compare this research output to 41 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 95% of its contemporaries.