What can a participatory approach to evaluation contribute to the field of integrated care?

© 2017 BMJ Publishing Group. All rights reserved. Better integration of care within the health sector and between health and social care is seen in many countries as an essential way of addressing the enduring problems of dwindling resources, changing demographics and unacceptable variation in quality of care. Current research evidence about the effectiveness of integration efforts supports neither the enthusiasm of those promoting and designing integrated care programmes nor the growing efforts of practitioners attempting to integrate care on the ground. In this paper we present a methodological approach, based on the principles of participatory research, that attempts to address this challenge. Participatory approaches are characterised by a desire to use social science methods to solve practical problems and a commitment on the part of researchers to substantive and sustained collaboration with relevant stakeholders. We describe how we applied an emerging practical model of participatory research, the researcher-in-residence model, to evaluate a large-scale integrated care programme in the UK. We propose that the approach added value to the programme in a number of ways: by engaging stakeholders in using established evidence and with the benefits of rigorously evaluating their work, by providing insights for local stakeholders that they were either not familiar with or had not fully considered in relation to the development and implementation of the programme and by challenging established mindsets and norms. While there is still much to learn about the benefits and challenges of applying participatory approaches in the health sector, we demonstrate how using such approaches have the potential to help practitioners integrate care more effectively in their daily practice and help progress the academic study of integrated care

The Dimension of Subcode-Subfields of Shortened Generalized Reed Solomon Codes

Reed-Solomon (RS) codes are among the most ubiquitous codes due to their good parameters as well as efficient encoding and decoding procedures. However, RS codes suffer from having a fixed length. In many applications where the length is static, the appropriate length can be obtained by an RS code by shortening or puncturing. Generalized Reed-Solomon (GRS) codes are a generalization of RS codes, whose subfield-subcodes are extensively studied. In this paper we show that a particular class of GRS codes produces many subfield-subcodes with large dimension. An algorithm for searching through the codes is presented as well as a list of new codes obtained from this method

Planetary nebulae in M32 and the bulge of M31: Line intensities and oxygen abundances

We present spectroscopy of planetary nebulae in M32 and in the bulge of M31 that we obtained with the MOS spectrograph at the Canada-France-Hawaii Telescope. Our sample includes 30 planetary nebulae in M31 and 9 planetary nebulae in M32. We also observed one H II region in the disk of M31. We detected [O III]$\lambda$4363 in 18 of the planetary nebulae, 4 in M32 and 14 in the bulge of M31. We use our line intensities to derive electron temperatures and oxygen abundances for the planetary nebulae.Comment: 17 pages, 12 figures, accepted by Astronomy & Astrophysics Supplement Serie

Planning Network UK (PNUK): a manifesto for planning and land reform

The Manifesto is an analysis of the shortcomings of the current planning and land policy system in the UK with a number of policy proposals for refor

Medial temporal lobe contributions to intra-item associative recognition memory in the aging brain

Aging is associated with a decline in episodic memory function. This is accompanied by degradation of and functional changes in the medial temporal lobe (MTL) which subserves mnemonic processing. To date no study has investigated age-related functional change in MTL substructures during specific episodic memory processes such as intra-item associative memory. The aim of this study was to characterize age-related change in the neural correlates of intra-item associative memory processing. Sixteen young and 10 older subjects participated in a compound word intra-item associative memory task comprising a measure of associative recognition memory and a measure of recognition memory. There was no difference in performance between groups on the associative memory measure but each group recruited different MTL regions while performing the task.The young group recruited the left anterior hippocampus and posterior parahippocampal gyrus whereas the older participants recruited the hippocampus bilaterally. In contrast, recognition memory was significantlyworse in the older subjects.The left anterior hippocampuswas recruited in the young group during successful recognition memory whereas the older group recruited a more posterior region of the left hippocampus and showed a more bilateral activation of frontal brain regions than was observed in the young group. Our results suggest a reorganization of the neural correlates of intra-item associative memory in the aging brain

As a New CEO, president, vice president, Director or General Manager For a Business Organization, What Should Be Your First 30 to 60 Days Priorities and Efforts?

I am often asked this question by many business executives, business professors, business teachers and trainers, business consultants and advisors, and in my personal teaching and training. The answers to this question are the same for any business executive who is tasked with ‘Turn-Around Management’ to help grow the business. The first 30 to 60 days are critica

Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping

The lack of reliable data in developing countries is a major obstacle to sustainable development, food security, and disaster relief. Poverty data, for example, is typically scarce, sparse in coverage, and labor-intensive to obtain. Remote sensing data such as high-resolution satellite imagery, on the other hand, is becoming increasingly available and inexpensive. Unfortunately, such data is highly unstructured and currently no techniques exist to automatically extract useful insights to inform policy decisions and help direct humanitarian efforts. We propose a novel machine learning approach to extract large-scale socioeconomic indicators from high-resolution satellite imagery. The main challenge is that training data is very scarce, making it difficult to apply modern techniques such as Convolutional Neural Networks (CNN). We therefore propose a transfer learning approach where nighttime light intensities are used as a data-rich proxy. We train a fully convolutional CNN model to predict nighttime lights from daytime imagery, simultaneously learning features that are useful for poverty prediction. The model learns filters identifying different terrains and man-made structures, including roads, buildings, and farmlands, without any supervision beyond nighttime lights. We demonstrate that these learned features are highly informative for poverty mapping, even approaching the predictive performance of survey data collected in the field.Comment: In Proc. 30th AAAI Conference on Artificial Intelligenc

The Psychology of Business Development

Bhagat & McQuaid (1982) advanced that “undoubtedly, the most significant cross-cultural study of work-related values is the one carried out by Hofstede”. There has been interests on the influence of culture be it national or corporate on organisations and with growing national diversity in today’s businesses, culture remains an important dimension. Hofstede’s landmark study of IBM (Hofstede 1980 has highlighted some essential facts about culture that impact on organisational performance. Preceding Hofstede’s study was the work of Bartels (1967) who was one of the first to relate the importance of culture, illustrating the concept in decision-making and business ethics