Perceptions of the learning environment in higher specialist training of doctors: implications for recruitment and retention.

INTRODUCTION: Career choice, sense of professional identity and career behaviour are influenced, subject to change and capable of development through interaction with the learning environment. In this paper workplace learning discourses are used to frame ongoing concerns associated with higher specialist training. Data from the first stage of a multimethods investigation into recruitment into and retention in specialties in the West Midlands is used to consider some possible effects of the specialist learning environment on recruitment and retention. METHODS: The aim of the study was to identify issues, through interviews with 6 consultants and questionnaires completed by specialist registrars from specialties representing a range of recruitment levels. These would inform subsequent study of attributes and dispositions relevant to specialist practice and recruitment. The data were analysed using NVivo software for qualitative data management. RESULTS: Participants' perceptions are presented as bipolar dimensions, associated with: curriculum structure, learning relationships, assessment of learning, and learning climate. They demonstrate ongoing struggle between different models of workplace learning. CONCLUSION: Changes in the postgraduate education of doctors seem set to continue well into the future. How these are reflected in the balance between workplace learning models, and how they influence doctors' sense of identity as specialists suggests a useful basis for examination of career satisfaction and recruitment to specialties

The recruitment of foster carers: key messages from the research literature

This report summarises key learning from existing literature around the recruitment of foster carers

An intervention for people with learning disabilities and epilepsy

Date of Acceptance: 09/01/2015Epilepsy is relatively common in people with learning disabilities, and can be complex and refractory to treatment, with negative effects on quality of life and service costs. This article describes a randomised controlled feasibility trial, called Wordless Intervention for Epilepsy in Learning Disabilities, under way at Hertfordshire Partnership University NHS Foundation Trust. Recruitment of people with learning disabilities and epilepsy to the trial has been affected by logistical issues, such as difficulties in identifying potential patients and contacting carers. However, public and patient involvement has improved study design and management, and has helped maximise recruitment. Should the present study confirm feasibility, a full-scale randomised controlled trial will address the effects of the Books Beyond Words title Getting on With Epilepsy as an intervention for people with learning disabilities and epilepsy.Peer reviewe

Guest editors' introduction to special theme issue [of Studies in Learning, Evaluation, Innovation and Development]: Retention, recruitment and placement

Guest editors’ introduction to special theme issue [of Studies in Learning, Evaluation, Innovation and development]: Retention, recruitment and placement

Recruitment Market Trend Analysis with Sequential Latent Variable Models

Recruitment market analysis provides valuable understanding of industry-specific economic growth and plays an important role for both employers and job seekers. With the rapid development of online recruitment services, massive recruitment data have been accumulated and enable a new paradigm for recruitment market analysis. However, traditional methods for recruitment market analysis largely rely on the knowledge of domain experts and classic statistical models, which are usually too general to model large-scale dynamic recruitment data, and have difficulties to capture the fine-grained market trends. To this end, in this paper, we propose a new research paradigm for recruitment market analysis by leveraging unsupervised learning techniques for automatically discovering recruitment market trends based on large-scale recruitment data. Specifically, we develop a novel sequential latent variable model, named MTLVM, which is designed for capturing the sequential dependencies of corporate recruitment states and is able to automatically learn the latent recruitment topics within a Bayesian generative framework. In particular, to capture the variability of recruitment topics over time, we design hierarchical dirichlet processes for MTLVM. These processes allow to dynamically generate the evolving recruitment topics. Finally, we implement a prototype system to empirically evaluate our approach based on real-world recruitment data in China. Indeed, by visualizing the results from MTLVM, we can successfully reveal many interesting findings, such as the popularity of LBS related jobs reached the peak in the 2nd half of 2014, and decreased in 2015.Comment: 11 pages, 30 figure, SIGKDD 201

Extinction of cue-evoked food seeking recruits a GABAergic interneuron ensemble in the dorsal medial prefrontal cortex of mice

Animals must quickly adapt food-seeking strategies to locate nutrient sources in dynamically changing environments. Learned associations between food and environmental cues that predict its availability promote food-seeking behaviors. However, when such cues cease to predict food availability, animals undergo 'extinction' learning, resulting in the inhibition of food-seeking responses. Repeatedly activated sets of neurons, or 'neuronal ensembles', in the dorsal medial prefrontal cortex (dmPFC) are recruited following appetitive conditioning and undergo physiological adaptations thought to encode cue-reward associations. However, little is known about how the recruitment and intrinsic excitability of such dmPFC ensembles are modulated by extinction learning. Here, we used in vivo 2-Photon imaging in male Fos-GFP mice that express green fluorescent protein (GFP) in recently behaviorally-activated neurons to determine the recruitment of activated pyramidal and GABAergic interneuron mPFC ensembles during extinction. During extinction, we revealed a persistent activation of a subset of interneurons which emerged from a wider population of interneurons activated during the initial extinction session. This activation pattern was not observed in pyramidal cells, and extinction learning did not modulate the excitability properties of activated neurons. Moreover, extinction learning reduced the likelihood of reactivation of pyramidal cells activated during the initial extinction session. Our findings illuminate novel neuronal activation patterns in the dmPFC underlying extinction of food-seeking, and in particular, highlight an important role for interneuron ensembles in this inhibitory form of learning