Introduction: The present study aimed to generate a model that would provide a conceptual framework for linking disparate components of knowledge translation. A theoretical model of such would enable the organization and evaluation of attempts to analyze current conditions and to design interventions on the transfer and utilization of research knowledge.
Methods: This research, performed in 2006-2007 at the Tehran University of Medical Sciences (TUMS), utilized two distinct methodologies: a narrative review to identify existing knowledge transfer models and frameworks and focus group discussions to determine the views and opinions of researchers and decision makers regarding barriers to knowledge translation within the health system.
Results: A knowledge translation cycle is described, with five domains: knowledge creation, knowledge transfer, research utilization, question transfer, and the context of organization.
Discussion: The knowledge translation cycle offers a theoretical basis for identifying basic requirements and linking mechanisms in the translation of knowledge for research utilization.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1002/chp.193 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Moganshan international consensus on further strengthening global scientific collaboration in the field of molecular imaging.
Eur J Nucl Med Mol Imaging
January 2025
College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Genomic reanalysis of a pan-European rare-disease resource yields new diagnoses.
Nat Med
January 2025
Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands.
Genetic diagnosis of rare diseases requires accurate identification and interpretation of genomic variants. Clinical and molecular scientists from 37 expert centers across Europe created the Solve-Rare Diseases Consortium (Solve-RD) resource, encompassing clinical, pedigree and genomic rare-disease data (94.5% exomes, 5.
View Article and Find Full Text PDFAuthor Correction: Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision.
Nat Methods
January 2025
OncoRNALab, Cancer Research Institute Ghent (CRIG), Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
Exploration of linear and interpretable models for quantification of cell parameters via contactless short-wave infrared hyperspectral sensing.
Sci Rep
January 2025
Fischell Department of Bioengineering, University of Maryland, College Park, USA.
The development of optical sensors for label-free quantification of cell parameters has numerous uses in the biomedical arena. However, using current optical probes requires the laborious collection of sufficiently large datasets that can be used to calibrate optical probe signals to true metabolite concentrations. Further, most practitioners find it difficult to confidently adapt black box chemometric models that are difficult to troubleshoot in high-stakes applications such as biopharmaceutical manufacturing.
View Article and Find Full Text PDFLinking altered neuronal and synaptic properties to nicotinic receptor Alpha5 subunit gene dysfunction: a translational investigation in rat mPFC and human cortical layer 6.
Transl Psychiatry
January 2025
Research Center Juelich, Institute of Neuroscience and Medicine 10, Research Center Juelich, Juelich, Germany.
Genetic variation in the α5 nicotinic acetylcholine receptor (nAChR) subunit of mice results in behavioral deficits linked to the prefrontal cortex (PFC). rs16969968 is the primary Single Nucleotide Polymorphism (SNP) in CHRNA5 strongly associated with nicotine dependence and schizophrenia in humans. We performed single cell-electrophysiology combined with morphological reconstructions on layer 6 (L6) excitatory neurons in the medial PFC (mPFC) of wild type (WT) rats, rats carrying the human coding polymorphism rs16969968 in Chrna5 and α5 knockout (KO) rats.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!