Hidden Gems: systematically searching electronic databases for research publications for social work and social care.

Context: Electronic bibliographic databases are a key source for professional publications about social work and community care more generally. This article describes and evaluates a method of identifying relevant articles as part of a systematic review of research evidence. Decision making about institutional and home care services for older people is used as an example. Method: Four databases (Social Science Citation Index, Medline, CINAHL, and Caredata) that abstract publications relevant to health and social services were searched systematically to identify relevant research studies. The items retrieved were appraised independently using a standard form developed for the purpose. The searches were compared in terms of sensitivity, precision, overlap between databases, and inter-rater reliability. Results: The search retrieved 525 articles, of which 276 were relevant. The four databases retrieved 55%, 41%, 19%, and 1% of the relevant articles respectively, achieving these sensitivities with precision levels of 54%, 48%, 84% and 94%. The databases retrieved 116, 73, 24 and 15 unique relevant articles respectively, showing the need to use a range of databases. Discussion: A general approach to creating a search to retrieve relevant research has been developed. The development of an international, indexed database dedicated to literature relevant to social services is a priority to enable progress in evidence-based policy and practice in social work. Editors and researchers should consider using structured abstracts in order to improve the retrieval and dissemination of research.

Rural Development Group Politics. A hidden cost?

I challenge the popular notion of European rural development group dynamics and argue for a better understanding of the role of micro-politics as a means of enhancing the performance of these groups. The views are research based and have relevance to the broader rural development and regeneration sector. Micro-politics involves knowledge, power, trust, perceptions, understanding, social networks, values and traits that arise as a result of individuals interacting within a group whilst working on a shared goal, such as rural development. The monetary and time costs to a community of failing to address micro-politics and nurture positive group relations are considerable. These include time spent in unproductive meetings and poorly prioritized—and ultimately unsuccessful—funding applications as a result of failure to agree priorities. Successful groups rely on individuals interacting in a way that achieves a greater social good. Mutual trust amongst the actors lies at the heart of effective group activity. Effective management of micro-politics requires steps to nurture a culture of mutual trust to ensure that rural development actors co-operate rather than play destructive games with one another. A case study example of a relatively straightforward approach illustrates how this might be done in practice.

Hidden Conditional Random Fields for Visual Speech Recognition

In this paper we present the application of Hidden Conditional Random Fields (HCRFs) to modelling speech for visual speech recognition. HCRFs may be easily adapted to model long range dependencies across an observation sequence. As a result visual word recognition performance can be improved as the model is able to take more of a contextual approach to generating state sequences. Results are presented from a speaker-dependent, isolated digit, visual speech recognition task using comparisons with a baseline HMM system. We firstly illustrate that word recognition rates on clean video using HCRFs can be improved by increasing the number of past and future observations being taken into account by each state. Secondly we compare model performances using various levels of video compression on the test set. As far as we are aware this is the first attempted use of HCRFs for visual speech recognition.