Molecular Beams

Contains reports on five research projects

Molecular Beams

Contains research objectives and reports on six research projects

Molecular Beams

Contains research objectives and reports on two research projects.Joint Services Electronics Programs (U. S. Army, U. S. Navy, and U. S. Air Force) under Contract DA 36-039-AMC-03200(E

Molecular Beams

Contains research objectives and reports on five research projects

Assessing the Quality of Decision Support Technologies Using the International Patient Decision Aid Standards instrument (IPDASi)

Objectives To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids). Design Scale development study, involving construct, item and scale development, validation and reliability testing. Setting There has been increasing use of decision support technologies – adjuncts to the discussions clinicians have with patients about difficult decisions. A global interest in developing these interventions exists among both for-profit and not-for-profit organisations. It is therefore essential to have internationally accepted standards to assess the quality of their development, process, content, potential bias and method of field testing and evaluation. Methods Scale development study, involving construct, item and scale development, validation and reliability testing. Participants Twenty-five researcher-members of the International Patient Decision Aid Standards Collaboration worked together to develop the instrument (IPDASi). In the fourth Stage (reliability study), eight raters assessed thirty randomly selected decision support technologies. Results IPDASi measures quality in 10 dimensions, using 47 items, and provides an overall quality score (scaled from 0 to 100) for each intervention. Overall IPDASi scores ranged from 33 to 82 across the decision support technologies sampled (n = 30), enabling discrimination. The inter-rater intraclass correlation for the overall quality score was 0.80. Correlations of dimension scores with the overall score were all positive (0.31 to 0.68). Cronbach's alpha values for the 8 raters ranged from 0.72 to 0.93. Cronbach's alphas based on the dimension means ranged from 0.50 to 0.81, indicating that the dimensions, although well correlated, measure different aspects of decision support technology quality. A short version (19 items) was also developed that had very similar mean scores to IPDASi and high correlation between short score and overall score 0.87 (CI 0.79 to 0.92). Conclusions This work demonstrates that IPDASi has the ability to assess the quality of decision support technologies. The existing IPDASi provides an assessment of the quality of a DST's components and will be used as a tool to provide formative advice to DSTs developers and summative assessments for those who want to compare their tools against an existing benchmark

Model variations in predicting incidence of Plasmodium falciparum malaria using 1998-2007 morbidity and meteorological data from south Ethiopia

Background: Malaria transmission is complex and is believed to be associated with local climate changes. However, simple attempts to extrapolate malaria incidence rates from averaged regional meteorological conditions have proven unsuccessful. Therefore, the objective of this study was to determine if variations in specific meteorological factors are able to consistently predict P. falciparum malaria incidence at different locations in south Ethiopia. Methods: Retrospective data from 42 locations were collected including P. falciparum malaria incidence for the period of 1998-2007 and meteorological variables such as monthly rainfall (all locations), temperature (17 locations), and relative humidity (three locations). Thirty-five data sets qualified for the analysis. Ljung-Box Q statistics was used for model diagnosis, and R squared or stationary R squared was taken as goodness of fit measure. Time series modelling was carried out using Transfer Function (TF) models and univariate auto-regressive integrated moving average (ARIMA) when there was no significant predictor meteorological variable. Results: Of 35 models, five were discarded because of the significant value of Ljung-Box Q statistics. Past P. falciparum malaria incidence alone (17 locations) or when coupled with meteorological variables (four locations) was able to predict P. falciparum malaria incidence within statistical significance. All seasonal AIRMA orders were from locations at altitudes above 1742 m. Monthly rainfall, minimum and maximum temperature was able to predict incidence at four, five and two locations, respectively. In contrast, relative humidity was not able to predict P. falciparum malaria incidence. The R squared values for the models ranged from 16% to 97%, with the exception of one model which had a negative value. Models with seasonal ARIMA orders were found to perform better. However, the models for predicting P. falciparum malaria incidence varied from location to location, and among lagged effects, data transformation forms, ARIMA and TF orders. Conclusions: This study describes P. falciparum malaria incidence models linked with meteorological data. Variability in the models was principally attributed to regional differences, and a single model was not found that fits all locations. Past P. falciparum malaria incidence appeared to be a superior predictor than meteorology. Future efforts in malaria modelling may benefit from inclusion of non-meteorological factors

A Century of Environmental Legislation

We find three intertwined ambitions that drove federal legislation over wildlife and biodiversity at the beginning of the 20th Century: establishment of multiple-use federal lands, the economic development of natural resources, and the maintenance of option values. We examine this federal intervention in natural resource use by analyzing roll-call votes over the past century. These votes involved decisions regarding public land that reallocated the returns to users by changing the asset's physical character or its usage rights. We suggest that long term consequences affecting current resource allocations arose from disparities between broadly dispersed benefits and locally concentrated socio-economic and geophysical (spatial) costs. We show that a primary intent of public land management has become to preserve multiple-use option values and identify important factors in computing those option values. We do this by demonstrating how the willingness to forego current benefits for future ones depends on the community's resource endowments. These endowments are defined not only in terms of users' current wealth accumulation but also from their expected ability to extract utility from natural resources over time

Spatial access priority mapping (SAPM) with fishers : a quantitative GIS method for participatory planning

Spatial management tools, such as marine spatial planning and marine protected areas, are playing an increasingly important role in attempts to improve marine management and accommodate conflicting needs. Robust data are needed to inform decisions among different planning options, and early inclusion of stakeholder involvement is widely regarded as vital for success. One of the biggest stakeholder groups, and the most likely to be adversely impacted by spatial restrictions, is the fishing community. In order to take their priorities into account, planners need to understand spatial variation in their perceived value of the sea. Here a readily accessible, novel method for quantitatively mapping fishers’ spatial access priorities is presented. Spatial access priority mapping, or SAPM, uses only basic functions of standard spreadsheet and GIS software. Unlike the use of remote-sensing data, SAPM actively engages fishers in participatory mapping, documenting rather than inferring their priorities. By so doing, SAPM also facilitates the gathering of other useful data, such as local ecological knowledge. The method was tested and validated in Northern Ireland, where over 100 fishers participated in a semi-structured questionnaire and mapping exercise. The response rate was excellent, 97%, demonstrating fishers’ willingness to be involved. The resultant maps are easily accessible and instantly informative, providing a very clear visual indication of which areas are most important for the fishers. The maps also provide quantitative data, which can be used to analyse the relative impact of different management options on the fishing industry and can be incorporated into planning software, such as MARXAN, to ensure that conservation goals can be met at minimum negative impact to the industry. This research shows how spatial access priority mapping can facilitate the early engagement of fishers and the ready incorporation of their priorities into the decision-making process in a transparent, quantitative way