University of Bedfordshire

About: University of Bedfordshire is a education organization based out in Luton, Bedford, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 3860 authors who have published 6079 publications receiving 143448 citations. The organization is also known as: University of Luton.

Performance enhancing drug abuse and cardiovascular risk in athletes: implications for the clinician

Abstract: The use of performance-enhancing and social drugs by athletes raises a number of ethical and health concerns. The World Anti-Doping Agency was constituted to address both of these issues as well as publishing a list of, and testing for, banned substances in athletes. Despite continuing methodological developments to detect drug use and associated punishments for positive dope tests, there are still many athletes who choose to use performance and image enhancing drugs. Of primary concern to this review are the health consequences of drug use by athletes. For such a large topic we must put in place delimitations. Specifically, we will address current knowledge, controversies and emerging evidence in relation to cardiovascular (CV) health of athletes taking drugs. Further, we delimit our discussion to the CV consequences of anabolic steroids and stimulant (including amphetamines and cocaine) use. These drugs are reported in the majority of adverse findings in athlete drug screenings and thus are more likely to be relevant to the healthcare professionals responsible for the well-being of athletes. In detailing CV health issues related to anabolic steroid and stimulant abuse by athletes we critique current research evidence, present exemplar case studies and suggest important avenues for on-going research. Specifically we prompt the need for awareness of clinical staff when assessing the potential CV consequences of drug use in athletes.

Training interventions for improving telephone consultation skills in clinicians

Abstract: Internal sources • New Source of support, Not specified. • eHealth Unit, Imperial College, UK. Support was gained from previous Cochrane Reviews either submitted or in the process of being completed External sources • No sources of support supplied.

Commitments, norms and custard creams – a social influence approach to reducing did not attends (DNAs)

Abstract: If only Mary Poppins was right and all it took was a ‘spoonful of sugar’ to help the medicine go down. But, as most clinicians know, when it comes to persuading patients to take their medicines, do a little more exercise, eat healthily or simply turn up for scheduled appointments, it often takes more than just a spoonful of sugar to sweeten the deal. This latter problem – patients who do not attend their appointments (DNAs) and who fail to cancel with enough time to offer it to another – is an especially vexing one and a major drain on NHS resources. Up to 6 million appointments are missed each year with direct costs estimated to be in the region of £700 million.1,2 One survey of 683 GPs found that 84% considered DNAs a major problem leading to lengthened waiting times, difficulty in reaching performance targets and greater costs.3 Other studies have cited reduced patient satisfaction, public health issues and increases in inappropriate Accident & Emergency presentations as consequences.4 So why do patients DNA? There are doubtless many reasons. Perhaps they felt better or experienced anxiety about potential bad news. Maybe there were issues with transportation or they experienced difficulty getting through to cancel. Perhaps they couldn't get time off work. A simple fact however, backed up by surveys of patients themselves, is that whilst they do often feel better, experience anxiety or encounter problems with processes and systems, the most common reason why patients DNA is that they simply forget.5 Given this ‘epidemic of forgetfulness’ it shouldn't surprise anyone to learn that many attempts to reduce, or at least manage the impact of DNAs, have been made. Some centres may overbook their clinics in anticipation of experiencing high DNA rates. But approaches like these can have knock-on effects that ultimately disadvantage patients, and however frustrating and unnecessary a waste of clinician time DNAs can be, overbooking does not deal with the problem itself.6 One cannot assume that a DNA is a medical condition resolved. It is the authors' experience (and most likely readers' too) that patients still present, but at less convenient times, in less appropriate care settings, with the additional health and financial implications that frequently accompany a worsened condition. Perhaps a simpler solution would be to introduce a modest charge for appointments or fines for non-attendance. Given that over half of all appointments are accounted for by patients with long-term conditions such as diabetes and arthritis, this seems unfair – effectively penalizing people for falling ill.7 Fines present difficulties in terms of administration and enforcement.8 They can also backfire. Studies in children's day care centres found that penalizing late or non-attenders actually increased lateness and non-attendance.9 There is some evidence to support the use of reminder systems. Koshy et al. showed SMS reminders to have a modest effect in reducing DNAs at ophthalmology outpatients departments.10 A gastroenterology clinic found a telephone call to patients one week prior to their appointment reduced DNA rates from 23.3% to 5.7%.11 Whilst both approaches have been shown to have an effect in hospital settings, the challenge in primary care can be rather different. Most patients require appointments within a 24–48 hour period and so it may not be practical to put reminder systems in place. Consequently it is the authors' observation that one of the more common approaches is to publish the regrettable number of patients who don't attend presumably in an attempt to highlight the problem, shame non-attenders and appeal to patients' sense of responsibility (See Figure 1 for an example). Some centres might even threaten persistent non-attenders with removal from their lists, but we found it difficult to confirm the extent to which this actually occurs. Figure 1 Example of a typical communication highlighting the problem of DNAs As is sometimes the case when dealing with commonly occurring challenges it can be helpful to look beyond our immediate environment and examine how those outside medicine deal with similar issues. The hospitality industry, for example, has long dealt with the problem of ‘no shows’. Customers call a restaurant to reserve a table and some fail to show. Like the NHS the cost can be considerable. Renowned social psychologist Robert Cialdini cites the example of restaurateur Gorden Sinclair who added two words that his receptionists used when taking customer bookings over the telephone.12 Instead of the usual ‘Please call us if you need to change or cancel your booking’ before hanging up, Sinclair asked staff to instead say ‘Will you please call us if you need to change or cancel your booking?’ and then pause, prompting the customer to make a verbal commitment by answering ‘Yes’. Such a small change seems unlikely to yield big results, but this verbal commitment led to a notable drop in no-shows for a reason well known to behavioural scientists. People generally prefer to live up to their commitments, especially those that are voluntary and require active involvement. 13 But can behaviourally informed interventions like this be applied as effectively in busy healthcare centres to reduce DNAs? Over a 4 month period (February – May 2011), we sought an answer to this question by testing three interventions informed from the behavioural sciences (specifically social influence theory) in two health centres in NHS Bedfordshire. The Wheatfield Surgery, Luton is a 7-partner practice providing, on average, 7000 GP and nurse led appointments each month. Toddington Medical Centre is a 4-partner practice averaging 3200 appointments. Like many centres, both experienced frustrating levels of DNAs. In the previous 12-month period, DNAs totalled 4700. Applying these social influence approaches in two centres allowed us to test the impact of two separate interventions in one and simultaneously test the cumulative effect of the same two interventions plus a third at the Toddington Medical Centre. Prior to testing we held training sessions with reception staff supported by the partners and the practice manager. The training focussed on the rationale for the interventions and the practicalities of applying them. Training was held two weeks prior to starting the interventions allowing staff a period of time to reflect, ask questions and raise any concerns. There were none.

Learning Spatio-Temporal Patterns for Predicting Object Behaviour.

Abstract: Rule-based systems employed to model complex object behaviours, do not necessarily provide a realistic portrayal of true behaviour. To capture the real characteristics in a specific environment, a better model may be learnt from observation. This paper presents a novel approach to learning long-term spatio-temporal patterns of objects in image sequences, using a neural network paradigm to predict future behaviour. The results demonstrate the application of our approach to the problem of predicting animal behaviour in response to a predator.

A kinetic study of the effect of hydrogen peroxide and peracetic acid against Staphylococcus aureus and Pseudomonas aeruginosa using the bioscreen disinfection method.

Abstract: Hydrogen peroxide and peracetic acid at pH 4 were examined against Staphylococcus aureus and Pseudomonas aeruginosa using the published 'Bioscreen' technique of biocide analysis. The data were examined using either classical Chick-Watson (CW) log-linear disinfection kinetics or the empirical, non-linear time Hom model. In some cases, modelling the data with the classical CW method gave good linear correlations, in others, however, deviations from this model were observed. In such cases the Hom model proved an adequate descriptor of the data. The Bioscreen technique therefore gives data which can be analysed using the normal mechanistic and empirical models currently available.