Accessing dental anxiety online support groups: An exploratory qualitative study of motives and experiences

Objectives: In recent years, Internet access has grown markedly providing individuals with new opportunities for online information retrieval, psychological advice and support. The objectives of the present study were to explore the context through which dentally anxious individuals access an online support group and the nature of their online experiences. Methods: An online questionnaire was completed by 143 individuals who accessed the Dental Fear Central online support group bulletin board. Qualitative analysis was conducted on the responses. Results: Analysis revealed three emergent themes which reflected the motives and experiences of individuals: ‘Searching for help’, ‘Sharing fears’ and ‘I feel empowered’. Conclusion: This exploratory study suggests that for most individuals accessing this online support group was a positive and beneficial experience. Practice Implications: Online support groups may represent a convenient and beneficial tool that may assist certain individuals to confront their debilitating anxiety/phobia and successfully receive dental care.

ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization

Background: Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results: We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion: ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.