PubMed Health⌕ Search

PubMed · 10281915

Is mandatory continuing education working?

Abstract

Mandatory continuing education (MCE) has been implemented by the states as a means of strengthening the relicensure process by requiring all licensees to participate in certain amounts of continuing education (CE) in hopes that such participation would enhance their performance. After two decades this somewhat controversial method for relicensure is still being questioned though there is evidence that benefits are being derived from such requirements. Licensees who do not actively participate voluntarily in CE are most affected, and they are developing renewed interest in their professions. Research studies are proving that well-designed CE programs do change behavior. Many additional programs become available when MCE is implemented and MCE, also, is helping to focus attention on other ways to improve performance. Information has been drawn from 16 different professions, though this article focuses on the health professions where the MCE movement has slowed significantly.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

L E Phillips. 1987. Is mandatory continuing education working?. https://doi.org/10.1002/chp.4760070110

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Probability estimation when some observations are grouped.

This paper considers the use of additional questions for decreasing survey non-response rates and an approach for estimating a probability based on the results obtained. In a survey, the respondents are asked to answer an original question and follow-up questions, where the answers for the follow-up questions are grouped answers for the original question. For example, respondents are asked to provide an exact number of incidents, but in cases of 'Do not know' or 'Refuse' responses, they are subsequently asked to pick an answer from a less specific categorical scale. The new estimator obtains smaller variance asymptotically and does not depend on a distribution family. This method is applied to income questions in a survey regarding injury prevention and behaviours. Another application is survey data on intimate partner violence, where some amendments were applied for incorporating post-stratification weights and for using non-random grouping. For additional illustration, an example of parameter estimation on artificially generated data is presented.

Data Collection↗