The Evolving Role of the Diabetes Educator

Core competencies for diabetes educators: A scoping review

AIMS

Diabetes educators (DEs) play a major role in diabetes education and management. The aims of this scoping review were to compile the currently identified core competencies for DEs and, to review the currently used criteria to assess DEs' core competencies.

METHODS

A scoping review was conducted using the methodology of the Joanna Briggs Institute. Five databases (Ovid, CINAHL, Scopus, Web of Science and PubMed) were searched. Keywords as well as inclusion and exclusion criteria were identified as search strategies and study selection for this review.

RESULTS

A total of (n = 22) publications comprising sixteen peer-reviewed studies and six professional-organisations (grey literature) were selected for review, as they listed the core competencies of DEs. The most common core competencies were related to knowledge and skills in diabetes self-management education, knowledge of pathophysiology and epidemiology, teaching skills, clinical skills and cultural competency. Evidently, an appropriate tool for assessing DEs' competencies is currently unavailable.

CONCLUSIONS

Given the importance of diabetes education in the care of people living with diabetes, it is imperative that DEs possess competencies in diabetes education and management. The review also identified the need to develop a globally applicable core competency assessment tool for DEs.

pubmed.mineR: an R package with text-mining algorithms to analyse PubMed abstracts

The PubMed literature database is a valuable source of information for scientific research. It is rich in biomedical literature with more than 24 million citations. Data-mining of voluminous literature is a challenging task. Although several text-mining algorithms have been developed in recent years with focus on data visualization, they have limitations such as speed, are rigid and are not available in the open source. We have developed an R package, pubmed.mineR, wherein we have combined the advantages of existing algorithms, overcome their limitations, and offer user flexibility and link with other packages in Bioconductor and the Comprehensive R Network (CRAN) in order to expand the user capabilities for executing multifaceted approaches. Three case studies are presented, namely, 'Evolving role of diabetes educators', 'Cancer risk assessment' and 'Dynamic concepts on disease and comorbidity' to illustrate the use of pubmed.mineR. The package generally runs fast with small elapsed times in regular workstations even on large corpus sizes and with compute intensive functions. The pubmed.mineR is available at http://cran.rproject. org/web/packages/pubmed.mineR.

pubmed.mineR: an R package with text-mining algorithms to analyse PubMed abstracts

The PubMed literature database is a valuable source of information for scientific research. It is rich in biomedical literature with more than 24 million citations. Data-mining of voluminous literature is a challenging task. Although several text-mining algorithms have been developed in recent years with focus on data visualization, they have limitations such as speed, are rigid and are not available in the open source. We have developed an R package, pubmed.mineR, wherein we have combined the advantages of existing algorithms, overcome their limitations, and offer user flexibility and link with other packages in Bioconductor and the Comprehensive R Network (CRAN) in order to expand the user capabilities for executing multifaceted approaches. Three case studies are presented, namely, 'Evolving role of diabetes educators', 'Cancer risk assessment' and 'Dynamic concepts on disease and comorbidity' to illustrate the use of pubmed.mineR. The package generally runs fast with small elapsed times in regular workstations even on large corpus sizes and with compute intensive functions. The pubmed.mineR is available at http://cran.rproject. org/web/packages/pubmed.mineR.