Experience of clinical services shapes attitudes to mental health data sharing: findings from a UK-wide survey.

BACKGROUND: Routinely-collected mental health data could deliver novel insights for mental health research. However, patients' willingness to share their mental health data remains largely unknown. We investigated factors influencing likelihood of sharing these data for research purposes amongst people with and without experience of mental illness. METHODS: We collected responses from a diverse sample of UK National Health Service (NHS) users (n = 2187) of which about half (n = 1087) had lifetime experience of mental illness. Ordinal logistic regression was used to examine the influence of demographic factors, clinical service experience, and primary mental illness on willingness to share mental health data, contrasted against physical health data. RESULTS: There was a high level of willingness to share mental (89.7%) and physical (92.8%) health data for research purposes. Higher levels of satisfaction with the NHS were associated with greater willingness to share mental health data. Furthermore, people with personal experience of mental illness were more willing than those without to share mental health data, once the variable of NHS satisfaction had been controlled for. Of the mental illnesses recorded, people with depression, obsessive-compulsive disorder (OCD), personality disorder or bipolar disorder were significantly more likely to share their mental health data than people without mental illness. CONCLUSIONS: These findings suggest that positive experiences of health services and personal experience of mental illness are associated with greater willingness to share mental health data. NHS satisfaction is a potentially modifiable factor that could foster public support for increased use of NHS mental health data in research.

The neglected zoonoses--the case for integrated control and advocacy.

The neglected zoonotic diseases (NZDs) have been all but eradicated in wealthier countries, but remain major causes of ill-health and mortality across Africa, Asia, and Latin America. This neglect is, in part, a consequence of under-reporting, resulting in an underestimation of their global burden that downgrades their relevance to policy-makers and funding agencies. Increasing awareness about the causes of NZDs and how they can be prevented could reduce the incidence of many endemic zoonoses. Addressing NZDs by targeting the animal reservoir can deliver a double benefit, as enhanced animal health means a reduced risk of infection for humans, as well as improved livelihoods through increased animal productivity. Advocacy for NZD control is increasing, but with it comes a growing awareness that NZD control demands activities both in the short term and over a long period of time. Moreover, despite the promise of cheap, effective vaccines or other control tools, these endemic diseases will not be sustainably controlled in the near future without long-term financial commitment, particularly as disease incidence decreases and other health priorities take hold. NZD intervention costs can seem high when compared with the public health benefits alone, but these costs are easily outweighed when a full cross-sector analysis is carried out and monetary/non-monetary benefits--particularly regarding the livestock sector--are taken into account. Public-private partnerships have recently provided advocacy for human disease control, and could prove equally effective in addressing endemic zoonoses through harnessing social impact investments. Evidence of the disease burdens imposed on communities by the NZDs and demonstration of the cost-effectiveness of integrated control can strengthen the case for a One Health approach to endemic zoonotic disease control.

The clinical implications of the collapsed cone planning algorithm.

AIMS: The accuracy of computer treatment planning systems is important in achieving clinically acceptable dose distributions. The pencil beam (PB) algorithm on Helax-TMS is currently used for all clinical treatment planning at the two centres involved in this study. However, it has been shown that the Helax-TMS collapsed cone (CC) algorithm is more accurate in regions of heterogeneity, such as the thorax, and head and neck. The aim of this study was to show the actual dose delivered to the patient when treating with a Helax-TMS PB plan, by using the corresponding Helax-TMS CC plan as the reference standard. MATERIALS AND METHODS: Thirty PB treatment plans (for lung and oesophageal treatments) were recalculated using the CC algorithm, and plans were then compared. RESULTS: The number of monitor units required to deliver the prescription dose differed between algorithms, by up to 3.4%. In most cases, the CC algorithm calculated more monitor units than the PB, indicating under-dosage at the prescription point during treatment. The dose distributions also seemed less homogeneous when calculated using the CC algorithm. The minimum dose to the planning target volume (PTV) was lower than the PB plan suggested in every case, by up to 23.2%. ICRU homogeneity requirements (i.e. a minimum 95% of the prescription dose in the PTV) were not met in any of the cases. Even with some attempts at optimisation, conformance to these requirements was difficult. CONCLUSION: The CC algorithm has several factors limiting its suitability for routine clinical use. However, it is an important milestone in radiotherapy treatment planning, and should be used to show expected changes in computer planned dose distributions with new accurate dose algorithms. It is worthwhile considering dose homogeneity requirements well before the advent of anticipated Monte Carlo-based models.

A collision prevention software tool for complex three-dimensional isocentric set-ups.

During treatment planning it can be difficult to check whether a particular plan is workable, that is it avoids obstructing treatment beams with parts of the patient couch and it avoids collisions between the treatment machine head and the patient couch. To overcome this problem, the trigonometric relationships between the placement of treatment beams and the patient couch are examined. From these relationships a set of useful equations that can be generally applied is derived. The application of these equations practically as a simple (non-graphical) planning tool is described. The resulting tool enables the feasibility of a plan to be checked during treatment planning, and gives guidance as to how a patient could be repositioned to allow the use of a plan when potential beam obstructions are detected, prior to verification of the treatment on a simulator.