Back

Identifying Dimensions and Components of Organizational Readiness for Knowledge Translation Implementation in Type I Medical Sciences Universities in Iran: A Scoping

hosseinzadeh, h.; sadatmosavi, a.; Tajedini, O.; Tavan, A.; Azami, M.

2025-07-01 health informatics
10.1101/2025.06.30.25330171 medRxiv
Show abstract

IntroductionHealthcare organizations must have the ability to adapt to rapid environmental changes and respond to evidence-based needs. One of the key prerequisites for the effective implementation of these changes is organizational readiness for knowledge translation (KT). The aim of this study is to identify the dimensions and components of organizational readiness for implementing KT in medical universities in Iran. MethodsThis research was conducted using a scoping review approach based on the Arksey and OMalley framework. A comprehensive search was performed without a time limitation in international databases such as PubMed, Scopus, Web of Science, and Persian databases MagIran and SID. Out of 4540 identified documents, 14 articles were included after screening and final assessment. ResultsAfter extracting the dimensions and components from the reviewed studies, five dimensions and 14 components were identified, as follows: Organizational Climate (culture of readiness and innovation, intra- and inter-organizational interactions, organizational dynamics), Organizational Support (development and training opportunities, financial resources, capacity building and organizational performance improvement), Change Management (strategies and change implementation capacity, leadership support), Organizational Context (knowledge management in the organization, organizational structure and technological advancement, social capital), and Human Resources (self-efficacy and motivation, leadership, collaboration and participation). ConclusionTo enhance organizational readiness for KT implementation, it is essential for health system managers and policymakers to understand the importance of utilizing research evidence and, through skill development and active participation in research processes, create the necessary environment for utilizing generated knowledge.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.