Abstract
Building on a narrative synthesis of adoption theories by Wisdom et al. (2013), this review identifies 118 measures associated with the 27 adoption predictors in the synthesis. The distribution of measures is uneven across the predictors and predictors vary in modifiability. Multiple dimensions and definitions of predictors further complicate measurement efforts. For state policymakers and researchers, more effective and integrated measurement can advance the adoption of complex innovations such as evidence-based practices.
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Acknowledgments
This study was funded by the National Institute of Mental Health (P30 MH090322: Advanced Center for State Research to Scale up EBPs for Children, PI: Hoagwood).
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Appendices
Appendices
Appendix 2: Databases and Search Strategy (Wisdom et al. 2013)
Ovid Medline, PsycINFO, and Web of Science were the major electronic databases used for Medical Subject Heading (MeSH) and article keyword searches.
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1.
Ovid Medline provided the first and primary source of literature. First, exploratory searches were conducted using these individual MeSH terms:
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DIFFUSION OF INNOVATION (13,774 hits);
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EVIDENCE-BASED PRACTICE (51,940 hits);
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EVIDENCE-BASED MEDICINE (47,305 hits) a subset of EVIDENCE-BASED PRACTICE;
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MODELS, THEORETICAL (1,120,350 hits).
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Next, the following MeSH terms were combined with the AND Boolean operator:
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DIFFUSION OF INNOVATION AND EVIDENCE-BASED PRACTICE (1,781 hits); DIFFUSION OF INNOVATION AND MODELS, THEORETICAL (1,299 hits);
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DIFFUSION OF INNOVATION AND EVIDENCE-BASED PRACTICE (1,397 hits).
Considering theoretical frameworks are the focus of this review, further combinations of the following MeSH terms were conducted using the AND Boolean operator:
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DIFFUSION OF INNOVATION AND EVIDENCE-BASED PRACTICE AND MODELS, THEORETICAL (320 hits);
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DIFFUSION OF INNOVATION AND EVIDENCE-BASED MEDICINE AND MODELS, THEORETICAL (237 hits).
Since EVIDENCE-BASED MEDICINE is a subset of EVIDENCE-BASED PRACTICE in the MeSH grouping, the search narrowed down to DIFFUSION OF INNOVATION AND EVIDENCE-BASED PRACTICE AND MODELS, THEORETICAL.
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2.
We used PsycInfo to supplement the original pool of literature using a similar search logic of MeSH:
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ADOPTION (15,535 hits);
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EVIDENCE BASED PRACTICE (8,940 hits);
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INNOVATION (3,995 hits);
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MODELS (65,923 hits);
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THEORIES (91,148 hits).
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Since ADOPTION as a MeSH in PsycInfo is quite broad and often refers to the child welfare taxonomy, we used the AND Boolean operator for the following combinations:
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ADOPTION AND EVIDENCE BASED PRACTICE (291 hits);
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ADOPTION AND INNOVATION (339 hits).
Next, to add a theoretical focus to this pool, we used the AND Boolean operator for the following combinations:
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ADOPTION AND EVIDENCE BASED PRACTICE AND INNOVATION (10 hits);
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ADOPTION AND EVIDENCE BASED PRACTICE AND MODELS (11 hits);
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ADOPTION AND EVIDENCE BASED PRACTICE AND THEORIES (9 hits);
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ADOPTION AND INNOVATION AND MODELS (18 hits);
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ADOPTION AND INNOVATION AND THEORIES (6 hits).
All articles from these last searches in PsycInfo were screened for overlaps.
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3.
To gain a broader perspective on other fields, we used Web of Science to expand the pool of literature obtained from Ovid Medline and PsycInfo, using the following topic searches:
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ADOPTION (45,440 hits);
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DIFFUSION (425,401 hits);
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EVIDENCE-BASE (47,294 hits);
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INNOVATION (76,818 hits);
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MODEL (3,894,846 hits);
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THEORY (1,172,347).
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Given these large yields, we used the Boolean operator AND to combine the following topic searches:
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ADOPTION AND EVIDENCE-BASE (899 hits);
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ADOPTION AND INNOVATION (4,209 hits);
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ADOPTION AND DIFFUSION (3,059 hits);
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ADOPTION AND EVIDENCE-BASE AND INNOVATION (135 hits).
To narrow the focus on theoretical models, further combinations using the Boolean operator AND were used:
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ADOPTION AND INNOVATION AND MODEL (48 hits);
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ADOPTION AND INNOVATION AND THEORY (194 hits);
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ADOPTION AND EVIDENCE-BASE AND MODEL (23 hits);
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ADOPTION AND EVIDENCE-BASE AND THEORY (80 hits);
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ADOPTION AND INNOVATION AND MODEL AND THEORY (439 hits);
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ADOPTION AND EVIDENCE-BASE AND MODEL AND THEORY (42 hits);
The last step searches from these three databases formed the preliminary pool of literature. All articles were searched for overlaps within and between databases, which yielded 332 unique hits. To systematically zero into specific adoption theories and their measures, we screened article keywords so at least one of the following keywords was included:
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ADOPTION;
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ADOPTION OF INNOVATION;
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CONCEPTUAL MODEL;
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DIFFUSION;
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EVIDENCE-BASED INTERVENTIONS;
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EVIDENCE-BASED PRACTICE;
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FRAMEWORK;
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INNOVATION;
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THEORY.
In addition, article titles were screened so that at least one of the following words was included:
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ADOPTION;
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DIFFUSION;
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DIFFUSION OF INNOVATION;
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DIFFUSION OF INNOVATIONS;
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EVIDENCE-BASED INTERVENTIONS;
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EVIDENCE-BASED MENTAL HEALTH TREATMENTS;
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EVIDENCE-BASED PRACTICE;
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FRAMEWORK;
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INNOVATION;
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INNOVATION ADOPTION;
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MODEL;
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MULTILEVEL;
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RESEARCH-BASED PRACTICE;
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THEORETICAL MODELS.
Finally, we screened the actual titles of the adoption theories within the texts of the articles so that at least one the following words were included:
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ADOPTION;
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DIFFUSION;
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EVIDENCE-BASED;
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EVIDENCE-BASED PRACTICE;
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FRAMEWORK;
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INNOVATION;
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MODEL.
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Chor, K.H.B., Wisdom, J.P., Olin, SC.S. et al. Measures for Predictors of Innovation Adoption. Adm Policy Ment Health 42, 545–573 (2015). https://doi.org/10.1007/s10488-014-0551-7
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DOI: https://doi.org/10.1007/s10488-014-0551-7