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. 2015 Aug 7:10:109.
doi: 10.1186/s13012-015-0295-0.

Use of concept mapping to characterize relationships among implementation strategies and assess their feasibility and importance: results from the Expert Recommendations for Implementing Change (ERIC) study

Thomas J Waltz  1   2 , Byron J Powell  3 , Monica M Matthieu  4   5   6 , Laura J Damschroder  7 , Matthew J Chinman  8   9 , Jeffrey L Smith  10   11 , Enola K Proctor  12 , JoAnn E Kirchner  13   14   15
Affiliations

Use of concept mapping to characterize relationships among implementation strategies and assess their feasibility and importance: results from the Expert Recommendations for Implementing Change (ERIC) study

Thomas J Waltz et al. Implement Sci. .

Abstract

Background: Poor terminological consistency for core concepts in implementation science has been widely noted as an obstacle to effective meta-analyses. This inconsistency is also a barrier for those seeking guidance from the research literature when developing and planning implementation initiatives. The Expert Recommendations for Implementing Change (ERIC) study aims to address one area of terminological inconsistency: discrete implementation strategies involving one process or action used to support a practice change. The present report is on the second stage of the ERIC project that focuses on providing initial validation of the compilation of 73 implementation strategies that were identified in the first phase.

Findings: Purposive sampling was used to recruit a panel of experts in implementation science and clinical practice (N = 35). These key stakeholders used concept mapping sorting and rating activities to place the 73 implementation strategies into similar groups and to rate each strategy's relative importance and feasibility. Multidimensional scaling analysis provided a quantitative representation of the relationships among the strategies, all but one of which were found to be conceptually distinct from the others. Hierarchical cluster analysis supported organizing the 73 strategies into 9 categories. The ratings data reflect those strategies identified as the most important and feasible.

Conclusions: This study provides initial validation of the implementation strategies within the ERIC compilation as being conceptually distinct. The categorization and strategy ratings of importance and feasibility may facilitate the search for, and selection of, strategies that are best suited for implementation efforts in a particular setting.

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Figures

Fig. 1
Fig. 1
Point and cluster map of all 73 strategies identified in the ERIC process. The map reflects the product of an expert panel (valid response n = 32) sorting 73 discrete implementation strategies into groupings by similarity with each strategy being depicted by a yellow dot and accompanied by a number supporting cross-referencing to the strategies enumerated in Table 1. Spatial distances reflect how frequently the strategies were sorted together as similar. In general, the closer two points are together, the more frequently those strategies were sorted together. Strategies distal from one another were infrequently, if at all, sorted together. These spatial relationships are relative to the sorting data obtained in this study, and distances do not reflect an absolute relationship (i.e., a 5-mm distance in the present map does not reflect the same relationship as a 5-mm distance on a map from a different data set). The legend provides the label for each of the nine clusters of strategies. Dotted lines within the Develop stakeholder interrelationships cluster indicate how two separate clusters were merged into one large cluster due to conceptual similarity among their items. Dotted lines extending between other clusters archive the reassignment of strategies from their original cluster to a neighboring cluster to which there was a better conceptual fit (i.e., strategies #48, #58, and #62)
Fig. 2
Fig. 2
Go-zone plot for all 73 strategies based on expert ratings. Note. The range of the x and y axes reflect the mean values obtained for all 73 of the discrete implementation strategies for each of the rating scales. The plot is divided into quadrants on the basis of the overall mean values for each of the rating scales. Quadrant labels are depicted with roman numerals next to the plot. Strategies in quadrant I fall above the mean for both the importance and the feasibility ratings. Thus, these strategies are those where there was the highest consensus regarding their relative high importance and feasibility. Conversely, quadrant III reflects the strategies where there was consensus regarding their relative low importance and feasibility. Quadrants II and IV reflect strategies that were relatively high in feasibility or importance, respectively, but low on the other rating scale
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