Scoping review of nursing-related dissemination and implementation research in German-speaking countries: Mapping the field / Scoping Review zum Stand der pflegebezogenen Disseminations- und Implementierungsforschung in deutschsprachigen Ländern: eine Bestandsaufnahme
Bibliographic record
Abstract
Abstract Implementing evidence-based innovations into care practice is a complex, slow and haphazard process. Dissemination and implementation (DI) research seeks to understand and optimize that process, to close gaps between research and practice and to improve quality of care. While there is a growing body of international DI research, little is known about the number and types of DI research studies and the DI topics studied in German-speaking nursing settings. This scoping review therefore evaluates the state of nursing-related DI research in German-speaking countries, discusses these results in light of the international state of DI research and provides directions for future research. We searched international databases (Web of Knowledge including Medline, CINAHL, PsycInfo, and GeroLit), German library meta-search engines, six German-language key trade journals, and reference lists of included articles. In total, 186 references representing 140 research projects were included in our review. Quality appraisal used five validated checklists. Methodological quality of the included studies was generally low. A total of 92 studies assessed the effects of DI strategies, 67 studied DI barriers and facilitators, 64 evaluated the impact or characteristics of DI processes, and 5 reported on the development or validation of DI research tools. None of the included studies focussed on methodological questions of DI research or on development and testing of DI theories and models. Future nursing-related DI research in German-speaking countries should particularly focus on these latter topics. Taking into account the international state of DI research will be especially crucial for those research activities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.079 | 0.202 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.041 | 0.043 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".