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Table 2 Criteria used for selecting theory (n = 212)

From: Criteria for selecting implementation science theories and frameworks: results from an international survey

Criterion and definition

Percent

1. Analytic level, e.g., individual, organizational, system

58.02

2. Logical consistency/plausibility, i.e., inclusion of meaningful, face-valid explanations of proposed relationships

56.13

3. Description of a change process, i.e., provides an explanation of how changes in process factors lead to changes in implementation-related outcomes

53.77

4. Empirical support, i.e., use in empirical studies with results relevant to the framework or theory, contributing to cumulative theory-building

52.83

5. Generalizability, i.e., applicability to various disciplines, settings, and populations

47.17

6. Application to a specific setting (e.g., hospitals, schools) or population (e.g., cancer)

44.34

7. Inclusion of change strategies/techniques, i.e., provision of specific method(s) for promoting change in implementation-related processes and/or outcomes

44.34

8. Outcome of interest, i.e., conceptual centrality of the variable to which included constructs are thought to be related

41.04

9. Inclusion of a diagrammatic representation, i.e., elaboration in a clear and useful figure representing the concepts within and their interrelations

41.04

10. Associated research method (e.g., informs qualitative interviews, associated with a valid questionnaire or methodology for constructing one), i.e., recommended or implied method to be used in an empirical study that uses the framework or theory

40.09

11. Process guidance, i.e., provision of a step-by-step approach for application

38.68

12. Disciplinary approval, i.e., frequency of use, popularity, acceptability, and perceptions of influence among a given group of scholars or reviewers, country, funding agencies, etc.; endorsement or recommendation by credible authorities in the field

33.96

13. Explanatory power/testability, i.e., ability to provide explanations around variables and effects; generates hypotheses that can be empirically tested

32.55

14. Simplicity/parsimony, i.e., relatively few assumptions are used to explain effects

32.08

15. Specificity of causal relationships among constructs, i.e., summary, explanation, organization, and description of relationships among constructs

32.08

16. Disciplinary origins, i.e., philosophical foundations

18.40

17. Falsifiability, i.e., verifiable; ability to be supported with empirical data

15.09

18. Uniqueness, i.e., ability to be distinguished from other theories or frameworks

12.74

19. Fecundity, i.e., offers a rich source for generating hypotheses

9.91

None of the above

0.00