A review of the information-gathering process for the provision of medicines for self-medication via community pharmacies in developing countries

Background: Currently, no review has been completed regarding the information-gathering process for the provision of medicines for self-medication in community pharmacies in developing countries. Objective: To review the rate of information gathering and the types of information gathered when patients present for self-medication requests. Methods: Six databases were searched for studies that described the rate of information gathering and/or the types of information gathered in the provision of medicines for self-medication in community pharmacies in developing countries. The types of information reported were classified as: signs and symptoms, patient identity, action taken, medications, medical history, and others. Results: Twenty-two studies met the inclusion criteria. Variations in the study populations, types of scenarios, research methods, and data reporting were observed. The reported rate of information gathering varied from 18% to 97%, depending on the research methods used. Information on signs and symptoms and patient identity was more frequently reported to be gathered compared with information on action taken, medications, and medical history. Conclusion: Evidence showed that the information-gathering process for the provision of medicines for self-medication via community pharmacies in developing countries is inconsistent. There is a need to determine the barriers to appropriate information-gathering practice as well as to develop strategies to implement effective information-gathering processes. It is also recommended that international and national pharmacy organizations, including pharmacy academics and pharmacy researchers, develop a consensus on the types of information that should be reported in the original studies. This will facilitate comparison across studies so that areas that need improvement can be identified. © 2013 Elsevier Inc.

Reliability of vegetation community information derived using decorana ordination and fuzzy c-means clustering

Descriptions of vegetation communities are often based on vague semantic terms describing species presence and dominance. For this reason, some researchers advocate the use of fuzzy sets in the statistical classification of plant species data into communities. In this study, spatially referenced vegetation abundance values collected from Greek phrygana were analysed by ordination (DECORANA), and classified on the resulting axes using fuzzy c-means to yield a point data-set representing local memberships in characteristic plant communities. The fuzzy clusters matched vegetation communities noted in the field, which tended to grade into one another, rather than occupying discrete patches. The fuzzy set representation of the community exploited the strengths of detrended correspondence analysis while retaining richer information than a TWINSPAN classification of the same data. Thus, in the absence of phytosociological benchmarks, meaningful and manageable habitat information could be derived from complex, multivariate species data. We also analysed the influence of the reliability of different surveyors' field observations by multiple sampling at a selected sample location. We show that the impact of surveyor error was more severe in the Boolean than the fuzzy classification. © 2007 Springer.

A simple remote sensing based information system for monitoring sites of conservation importance

Monitoring is essential for conservation of sites, but capacity to undertake it in the field is often limited. Data collected by remote sensing has been identified as a partial solution to this problem, and is becoming a feasible option, since increasing quantities of satellite data in particular are becoming available to conservationists. When suitably classified, satellite imagery can be used to delineate land cover types such as forest, and to identify any changes over time. However, the conservation community lacks (a) a simple tool appropriate to the needs for monitoring change in all types of land cover (e.g. not just forest), and (b) an easily accessible information system which allows for simple land cover change analysis and data sharing to reduce duplication of effort. To meet these needs, we developed a web-based information system which allows users to assess land cover dynamics in and around protected areas (or other sites of conservation importance) from multi-temporal medium resolution satellite imagery. The system is based around an open access toolbox that pre-processes and classifies Landsat-type imagery, and then allows users to interactively verify the classification. These data are then open for others to utilize through the online information system. We first explain imagery processing and data accessibility features, and then demonstrate the toolbox and the value of user verification using a case study on Nakuru National Park, Kenya. Monitoring and detection of disturbances can support implementation of effective protection, assist the work of park managers and conservation scientists, and thus contribute to conservation planning, priority assessment and potentially to meeting monitoring needs for Aichi target 11.