Engaging junior doctors:evidence from "open spaces" in England

Purpose: This paper aims to report on a project undertaken in order to identify, develop and reflect on the leadership and managerial skills of clinicians. The main aim of the project was to design, plan, organise and deliver a learning session for Foundation Year 2 Doctors within the premises of one of the largest NHS Foundation Trusts in the UK. The key theme of the learning session was the introduction of the notion of competent medical leadership in the NHS. A leadership role has been traditionally seen as the task of managers and as such clinicians have seemed reluctant to engage. Design/methodology/approach: A two hour workshop was designed and delivered with the use of Open Space Technology. Foundation Year 2 doctors were invited to consider the importance of leadership in their everyday roles. An awareness of the Medical Leadership Competency Framework had been a key aspect of the learning session. Findings: The project's outcome can be identified as being the encouragement of Foundation Year 2 doctors in considering their roles as leaders in their everyday tasks. Originality/value: Design, planning, organisation and delivery of a two hour Open Space learning session with the Foundation Year 2 doctors portrays the session's learning potentials and the potential for such sessions to provide a platform for difficult discussions in the NHS. This is particularly beneficial where a cultural shift is needed in order to see a way forward, notably when facing significant change. © Emerald Group Publishing Limited.

Optimal embedding for watermarking in discrete data spaces

In this paper, we address the problem of robust information embedding in digital data. Such a process is carried out by introducing modifications to the original data that one would like to keep minimal. It assumes that the data, which includes the embedded information, is corrupted before the extraction is carried out. We propose a principled way to tailor an efficient embedding process for given data and noise statistics. © Springer-Verlag Berlin Heidelberg 2005.