The social negotiation of fitness for work: tensions in doctor-patient relationships over medical certification of chronic pain

The UK government is promoting the health benefits of work, in order to change doctors' and patients' behaviour and reduce sickness absence. The rationale is that many people 'off sick' would have better outcomes by staying at work; but reducing the costs of health care and benefits is also an imperative. Replacement of the 'sick note' with the 'fit note' and a national educational programme are intended to reduce sickness-certification rates, but how will these initiatives impact on doctor-patient relationships and the existing tension between the doctor as patient advocate and gate-keeper to services and benefits? This tension is particularly acute for problems like chronic pain where diagnosis, prognosis and work capacity can be unclear. We interviewed 13 doctors and 30 chronic pain patients about their experiences of negotiating medical certification for work absence and their views of the new policies. Our findings highlight the limitations of naïve rationalist approaches to judgements of work absence and fitness for work for people with chronic pain. Moral, socio-cultural and practical factors are invoked by doctors and patients to contest decisions, and although both groups support the fit note's focus on capacity, they doubt it will overcome tensions in the consultation. Doctors value tacit skills of persuasion and negotiation that can change how patients conceptualise their illness and respond to it. Policy-makers increasingly recognise the role of this tacit knowledge and we conclude that sick-listing can be improved by further developing these skills and acknowledging the structural context within which protagonists negotiate sick-listin

Generic Subsequence Matching Framework: Modularity, Flexibility, Efficiency

Subsequence matching has appeared to be an ideal approach for solving many problems related to the fields of data mining and similarity retrieval. It has been shown that almost any data class (audio, image, biometrics, signals) is or can be represented by some kind of time series or string of symbols, which can be seen as an input for various subsequence matching approaches. The variety of data types, specific tasks and their partial or full solutions is so wide that the choice, implementation and parametrization of a suitable solution for a given task might be complicated and time-consuming; a possibly fruitful combination of fragments from different research areas may not be obvious nor easy to realize. The leading authors of this field also mention the implementation bias that makes difficult a proper comparison of competing approaches. Therefore we present a new generic Subsequence Matching Framework (SMF) that tries to overcome the aforementioned problems by a uniform frame that simplifies and speeds up the design, development and evaluation of subsequence matching related systems. We identify several relatively separate subtasks solved differently over the literature and SMF enables to combine them in straightforward manner achieving new quality and efficiency. This framework can be used in many application domains and its components can be reused effectively. Its strictly modular architecture and openness enables also involvement of efficient solutions from different fields, for instance efficient metric-based indexes. This is an extended version of a paper published on DEXA 2012.Comment: This is an extended version of a paper published on DEXA 201

People, Penguins and Petri Dishes: Adapting Object Counting Models To New Visual Domains And Object Types Without Forgetting

In this paper we propose a technique to adapt a convolutional neural network (CNN) based object counter to additional visual domains and object types while still preserving the original counting function. Domain-specific normalisation and scaling operators are trained to allow the model to adjust to the statistical distributions of the various visual domains. The developed adaptation technique is used to produce a singular patch-based counting regressor capable of counting various object types including people, vehicles, cell nuclei and wildlife. As part of this study a challenging new cell counting dataset in the context of tissue culture and patient diagnosis is constructed. This new collection, referred to as the Dublin Cell Counting (DCC) dataset, is the first of its kind to be made available to the wider computer vision community. State-of-the-art object counting performance is achieved in both the Shanghaitech (parts A and B) and Penguins datasets while competitive performance is observed on the TRANCOS and Modified Bone Marrow (MBM) datasets, all using a shared counting model.Comment: 10 page

Piecewise Linear Representation Segmentation as a Multiobjective Optimization Problem

Proceedings of: Forth International Workshop on User-Centric Technologies and applications (CONTEXTS 2010). Valencia, September 7-10, 2010Actual time series exhibit huge amounts of data which require an unaffordable computational load to be processed, leading to approximate representations to aid these processes. Segmentation processes deal with this issue dividing time series into a certain number of segments and approximating those segments with a basic function. Among the most extended segmentation approaches, piecewise linear representation is highlighted due to its simplicity. This work presents an approach based on the formalization of the segmentation process as a multiobjetive optimization problem and the resolution of that problem with an evolutionary algorithm.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029-C02-02.Publicad

Cognitive load selectively influences the interruptive effect of pain on attention.

Pain is known to interrupt attentional performance. Such interference effects seem to occur preferentially for tasks that are complex and/or difficult. However, few studies have directly manipulated memory load in the context of pain interference to test this view. Therefore, the present study examines the effect of experimental manipulations of both memory load and pain on three tasks previously found to be sensitive to pain interference. Three experiments were conducted. A different task was examined in each experiment, each comprising of a high and low cognitive load versions of the task. Experiment 1 comprised of an attention span (n-back) task, Experiment 2 an attention switching task, and Experiment 3 a divided attention task. Each task was conducted under painful and non-painful conditions. Within the pain condition, an experimental thermal pain induction protocol was administered at the same time participants completed the task. The load manipulations were successful in all experiments. Pain-related interference occurred under the high load condition, but only for the attention span task. No effect of pain was found on either the attentional switching or divided attention task. These results suggest that while cognitive load may influence the interruptive effect of pain on attention, this effect may be selective. Since pain affected the high load version of the n-back task, but did not interrupt performance on attentional switching or dual task paradigms, this means our findings did not completely support our hypotheses. Future research should explore further the parameters and conditions under which pain-related interference occurs

Prevalence and risk factors of sarcopenia among adults living in nursing homes

Objectives: Sarcopenia is a progressive loss of skeletal muscle and muscle function, with significant healthand disability consequences for older adults. We aimed to evaluate the prevalence and risk factors ofsarcopenia among older residential aged care adults using the European Working Group on Sarcopeniain Older People (EWGSOP) criteria.Study design: A cross-sectional study design that assessed older people (n = 102, mean age 84.5 ± 8.2 years)residing in 11 long-term nursing homes in Australia.Main outcome measurements: Sarcopenia was diagnosed from assessments of skeletal mass index bybioelectrical impedance analysis, muscle strength by handheld dynamometer, and physical performanceby the 2.4 m habitual walking speed test. Secondary variables where collected to inform a risk factoranalysis.Results: Forty one (40.2%) participants were diagnosed as sarcopenic, 38 (95%) of whom were categorizedas having severe sarcopenia. Univariate logistic regression found that body mass index (BMI) (Oddsratio (OR) = 0.86; 95% confidence interval (CI) 0.78–0.94), low physical performance (OR = 0.83; 95% CI0.69–1.00), nutritional status (OR = 0.19; 95% CI 0.05–0.68) and sitting time (OR = 1.18; 95% CI 1.00–1.39)were predictive of sarcopenia. With multivariate logistic regression, only low BMI (OR = 0.80; 95% CI0.65–0.97) remained predictive.Conclusions: The prevalence of sarcopenia among older residential aged care adults is very high. Inaddition, low BMI is a predictive of sarcopenia

The use of tensiometers to control the irrigation of nursery stock in containers.

End of Project ReportThe use of digital tensiometers to control the irrigation of nursery stock in containers was studied over a three year period. Over this time the tensiometers performed satisfactorily and successfully automated the irrigation of the plants. The results indicate the feasibility of using them to control nursery stock irrigation under Irish conditions. An irrigation tension of 50 hPa to trigger an irrigation period resulted in larger plants than those grown under drier regimes with irrigation tensions of 100 and 200 hPa. Measurements of stomatal resistance indicated that the plants in the drier regimes were growing under greater moisture stress. The drier regimes reduced the number of irrigations and also the overall usage of water. They reduced plant size but did not impair plant appearance. It may be possible to use this approach in the future to control plant growth. There was no difference in performance between plants gown with ebb and flood irrigation and those irrigated via overhead spraylines. The ebb and flood system gave a considerable reduction in water use.European Union Structural Funds (EAGGF

Discovering frequent patterns on agrometeorological data with TrieMotif

The “food safety” issue has concerned governments from several countries. The accurate monitoring of agriculture have become important specially due to climate change impacts. In this context, the development of new technologies for monitoring are crucial. Finding previously unknown patterns that frequently occur on time series, known as motifs, is a core task to mine the collected data. In this work we present a method that allows a fast and accurate time series motif discovery. From the experiments we can see that our approach is able to efficiently find motifs even when the size of the time series goes longer. We also evaluated our method using real data time series extracted from remote sensing images regarding sugarcane crops. Our proposed method was able to find relevant patterns, as sugarcane cycles and other land covers inside the same area, which are really useful for data analysis.FAPESPCNPqCAPESSticAmsudInternational Conference on Enterprise Information Systems - ICEIS (16. 2014 Lisbon