Approaches to mixed methods dissemination and implementation research: methods, strengths, caveats, and opportunities
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Limited translation of research into practice has prompted study of diffusion and implementation, and development of effective methods of encouraging adoption, dissemination and implementation. Mixed methods techniques offer approaches for assessing and addressing processes affecting implementation of evidence-based interventions. We describe common mixed methods approaches used in dissemination and implementation research, discuss strengths and limitations of mixed methods approaches to data collection, and suggest promising methods not yet widely used in implementation research. We review qualitative, quantitative, and hybrid approaches to mixed methods dissemination and implementation studies, and describe methods for integrating multiple methods to increase depth of understanding while improving reliability and validity of findings.
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Such a dimension or spectrum allows for nimble, rapid, and real-time assessment of type of school attendance problem, which must be a priority for implementation models.
“Such a dimension or spectrum allows for nimble, rapid, and real-time assessment of type of school attendance problem, which must be a priority for implementation models (see Part 2 of this review; Green et al., 2015).”
From Reconciling Contemporary Approaches to School Attendance and School Absenteeism: Toward Promotion and Nimble Response, Global Policy Review and Implementation, and Future Adaptability (Part 1) (2019) · cites this paper as Green et al., 2015
The Rapid Ethnographic Assessment section (page unavailable) says quick, real-time assessments of local conditions can inform intervention design and implementation. It does not discuss school attendance problems or establish that a dimension or spectrum enables their rapid classification or must be a priority for implementation models. (LLM, conf=0.84)
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- Authors
- Green, C. A., Duan, N., Gibbons, R. D., Hoagwood, K. E., Palinkas, L. A., & Wisdom, J. P.
- Affiliations
- Kaiser Permanente (US)
- Columbia University Irving Medical Center (US)
- University of Chicago (US)
- NYU Langone Health (US)
- University of Southern California (US)
- George Washington University (US)
- Corresponding author
- Green, Carla A.
- ORCID
- Venue
- Administration and Policy in Mental Health and Mental Health Services Research
- Published
- 2014-04-11
- Volume
- 42
- Issue
- 5
- Pages
- 508-523
- ISSN
- 0894-587X (ISSN-L)
- 1573-3289
- PMC
- PMC4363010
- OpenAlex
- W2063979429
- Cited by
- 205
- References
- 134
- Citations by year
- 2026: 13 · 2025: 24 · 2024: 23 · 2023: 13 · 2022: 30 · 2021: 25 · 2020: 17 · 2019: 21 · 2018: 21 · 2017: 5 · 2016: 3 · 2015: 6 · 2014: 2 · 2012: 1
- FWCI
- 9.63
- 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)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (P30MH090322)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
- Health Sciences › Health Professions › General Health Professions › Health Sciences Research and Education
- Keywords
- mixed methods, dissemination research, implementation research, evidence-based interventions, research-to-practice translation, qualitative research, quantitative methods, hybrid algorithm, methodological integration, reliability and validity
- MeSH terms
- Data Collection, Diffusion of Innovation, Health Services Research, Humans, Research Design, Reproducibility of Results, Information Dissemination, Qualitative Research, Evidence-Based Practice, Translational Research, Biomedical
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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