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Innovation Adoption: A Review of Theories and Constructs
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Many theoretical frameworks seek to describe the dynamic process of the implementation of innovations. Little is known, however, about factors related to decisions to adopt innovations and how the likelihood of adoption of innovations can be increased. Using a narrative synthesis approach, this paper compared constructs theorized to be related to adoption of innovations proposed in existing theoretical frameworks in order to identify characteristics likely to increase adoption of innovations. The overall goal was to identify elements across adoption frameworks that are potentially modifiable and, thus, might be employed to improve the adoption of evidence-based practices. The review identified 20 theoretical frameworks that could be grouped into two broad categories: theories that mainly address the adoption process (N = 10) and theories that address adoption within the context of implementation, diffusion, dissemination, and/or sustainability (N = 10). Constructs of leadership, operational size and structure, innovation fit with norms and values, and attitudes/motivation toward innovations each are mentioned in at least half of the theories, though there were no consistent definitions of measures for these constructs. A lack of precise definitions and measurement of constructs suggests further work is needed to increase our understanding of adoption of innovations.
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“A number of literature reviews of implementation frameworks have also been conducted, concentrating on particular implementation concepts, such as a particular stage, or specifically on either the factors, strategies or evaluations, rather than addressing all the concepts that could affect an innovation’s implementation [13,17,19-26].”
From A systematic review of implementation frameworks of innovations in healthcare and resulting generic implementation framework (2015) · cites this paper as [25]
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Metadata
- Authors
- Wisdom, J. P., Chor, K. H. B., Hoagwood, K. E., & Horwitz, S. M.
- Affiliations
- George Washington University (US)
- NYU Langone Health (US)
- Corresponding author
- Wisdom, Jennifer P.
- Venue
- Administration and Policy in Mental Health and Mental Health Services Research
- Published
- 2013-04-03
- Volume
- 41
- Issue
- 4
- Pages
- 480-502
- ISSN
- 0894-587X (ISSN-L)
- 1573-3289
- PMC
- PMC3894251
- OpenAlex
- W1993125943
- Cited by
- 451
- References
- 38
- Citations by year
- 2026: 28 · 2025: 40 · 2024: 43 · 2023: 43 · 2022: 51 · 2021: 60 · 2020: 47 · 2019: 48 · 2018: 27 · 2017: 22 · 2016: 11 · 2015: 17 · 2014: 13
- FWCI
- 1.65
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Administration and Policy in Mental Health and Mental Health Services Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (P30MH090322)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Health Sciences › Health Professions › General Health Professions › Health Sciences Research and Education
- Life Sciences › Agricultural and Biological Sciences › General Agricultural and Biological Sciences › Agricultural Innovations and Practices
- Keywords
- innovation adoption, theoretical framework, evidence-based practice, implementation, diffusion of innovations, dissemination, sustainability, leadership, organizational structure
- MeSH terms
- Diffusion of Innovation, Humans, Evidence-Based Practice
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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