Developing a valid and reliable assessment of knowledge translation (KT) for continuing professional development program of health professionals.
Ontology highlight
ABSTRACT: Introduction:Knowledge Translation (KT) is expected to be a critical learning outcome of a Continuing Professional Development (CPD) program. It continues to serve as an area of interest among educators and healthcare providers due to its importance to evidence-based practice. This study endeavored to develop a valid and reliable KT learning assessment tool in CPD. Methods:The Inventory of Reflective Vignettes (IRV), an innovative approach of integrating research vignettes, was utilized in crafting the 20-item IRV-KT tool. This instrument includes knowledge creation and action as essential KT constructs. KT competency was assessed in three segments (i.e., before and after CPD event and if in a lecture) using a one-group post-posttest pre-experimental design. Health professionals who successfully completed a CPD program on a knowledge translation topic were asked to complete the IRV-KT during the pilot study (n = 10) and actual implementation (n = 45). Responses were subjected to Cronbach's reliability and criterion-validity testing. Results:The initial test of the IRV-KT tool demonstrated a high internal reliability (? = 0.97) and most items yielded acceptable validity scores. During the actual implementation, a higher reliability score of 0.98 was generated with significant correlations between the before-after segments for both KT constructs of creation (r = 0.33, p < 0.05) and action (r = 0.49, p < 0.05). All items have significant positive validity coefficients (r > 0.35, p < 0.05) in all segments of the tool. Discussion:The study produced a reflective assessment tool to validly and reliably assess KT learning in a CPD. IRV-KT is seen to guide the curriculum process of CPD programs to bridge learning and healthcare outcomes.
SUBMITTER: Ong IL
PROVIDER: S-EPMC6095105 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
ACCESS DATA