Web-based screening and brief intervention for hazardous drinking: a double-blind randomized controlled trial

Background Strong evidence exists for the efficacy of screening and brief intervention for reducing hazardous drinking. However, problems have been highlighted with respect to its implementation in health-care systems, not least of which is a reluctance of some doctors to discuss alcohol proactively with their patients. Aims To determine the efficacy of a novel web-based screening and brief intervention (e-SBI) to reduce hazardous drinking. Design A double-blind randomized controlled trial. Setting A university student health service. Participants A total of 16 7 students (17-26 years) were recruited in the reception area and completed a 3-minute web-based screen including the Alcohol Use Disorder Identifiation Test (AUDIT) questionnaire. Of these, 112 tested positive, and 104 (52 females) who consented to follow-up were included in the trial. Measurements Drinking frequency, typical occasion quantity, total volume, heavy episode frequency (females > 80 g ethanol, males > 120 g ethanol), number of personal problems, an academic problems score. Intervention Participants were randomized to 10-15 minutes of web-based assessment and personalized feedback on their drinking (intervention, n = 5 1) or to a leaflet-only control group (n = 5 3). Findings Mean baseline AUDIT scores for control and intervention groups were 16.6 (SD = 6.0) and 16.6 (SD = 5.7). At 6 weeks, participants receiving e-SBI reported significantly lower total consumption (geometric mean ratio = 0.74; 9 5 % confidence interval: 0.56-0.96), lower heavy episode frequency (0.63; 0.42-0.92) and fewer personal problems (0.70; 0.54-0.91). At 6 months personal problems remained lower (0.76; 0.60-0.97), although consumption did not differ significantly. At 6 months, academic problems were lower in the intervention group relative to controls (0.72; 0.51-1.02). Conclusions e-SBI reduced hazardous drinking among university students, to an extent similar to that found for practitioner-delivered brief interventions in the general population. e-SBI offers promise as a strategy to reduce alcohol-related harm in a way that is non-intrusive, appealing to the target group, and capable of being incorporated into primary care. Research is required to replicate the findings, to determine the duration of intervention effects, and to investigate the mechanisms by which the intervention operates.

A knowledge-based system for liquid retaining structure design with blackboard architecture

Owing to the high degree of vulnerability of liquid retaining structures to corrosion problems, there are stringent requirements in its design against cracking. In this paper, a prototype knowledge-based system is developed and implemented for the design of liquid retaining structures based on the blackboard architecture. A commercially available expert system shell VISUAL RULE STUDIO working as an ActiveX Designer under the VISUAL BASIC programming environment is employed. Hybrid knowledge representation approach with production rules and procedural methods under object-oriented programming are used to represent the engineering heuristics and design knowledge of this domain. It is demonstrated that the blackboard architecture is capable of integrating different knowledge together in an effective manner. The system is tailored to give advice to users regarding preliminary design, loading specification and optimized configuration selection of this type of structure. An example of application is given to illustrate the capabilities of the prototype system in transferring knowledge on liquid retaining structure to novice engineers. (C) 2004 Elsevier Ltd. All rights reserved.

Multiresolution spatial databases: Making web-based spatial advances faster

Spatial data has now been used extensively in the Web environment, providing online customized maps and supporting map-based applications. The full potential of Web-based spatial applications, however, has yet to be achieved due to performance issues related to the large sizes and high complexity of spatial data. In this paper, we introduce a multiresolution approach to spatial data management and query processing such that the database server can choose spatial data at the right resolution level for different Web applications. One highly desirable property of the proposed approach is that the server-side processing cost and network traffic can be reduced when the level of resolution required by applications are low. Another advantage is that our approach pushes complex multiresolution structures and algorithms into the spatial database engine. That is, the developer of spatial Web applications needs not to be concerned with such complexity. This paper explains the basic idea, technical feasibility and applications of multiresolution spatial databases.

Semantic caching for web-based spatial applications

Client-side caching of spatial data is an important yet very much under investigated issue. Effective caching of vector spatial data has the potential to greatly improve the performance of spatial applications in the Web and wireless environments. In this paper, we study the problem of semantic spatial caching, focusing on effective organization of spatial data and spatial query trimming to take advantage of cached data. Semantic caching for spatial data is a much more complex problem than semantic caching for aspatial data. Several novel ideas are proposed in this paper for spatial applications. A number of typical spatial application scenarios are used to generate spatial query sequences. An extensive experimental performance study is conducted based on these scenarios using real spatial data. We demonstrate a significant performance improvement using our ideas.

Development and evaluation of an automated annotation pipeline and cDNA annotation system

Manual curation has long been held to be the gold standard for functional annotation of DNA sequence. Our experience with the annotation of more than 20,000 full-length cDNA sequences revealed problems with this approach, including inaccurate and inconsistent assignment of gene names, as well as many good assignments that were difficult to reproduce using only computational methods. For the FANTOM2 annotation of more than 60,000 cDNA clones, we developed a number of methods and tools to circumvent some of these problems, including an automated annotation pipeline that provides high-quality preliminary annotation for each sequence by introducing an uninformative filter that eliminates uninformative annotations, controlled vocabularies to accurately reflect both the functional assignments and the evidence supporting them, and a highly refined, Web-based manual annotation tool that allows users to view a wide array of sequence analyses and to assign gene names and putative functions using a consistent nomenclature. The ultimate utility of our approach is reflected in the low rate of reassignment of automated assignments by manual curation. Based on these results, we propose a new standard for large-scale annotation, in which the initial automated annotations are manually investigated and then computational methods are iteratively modified and improved based on the results of manual curation.