Genetic research presents ethical challenges to the achievement of valid informed consent, especially in developing countries with areas of low literacy. During the last several years, a number of genetic research proposals involving Omani nationals were submitted to the Department of Research and Studies, Ministry of Health, Oman.The objective of this paper is to report on the results of an internal quality assurance initiative to determine the extent of the information being provided in genetic research informed consent forms. In order (...) to achieve this, we developed checklists to assess the inclusion of basic elements of informed consent as well as elements related to the collection and future storage of biological samples. Three of the authors independently evaluated and reached consensus on seven informed consent forms that were available for review.Of the seven consent forms, four had less than half of the basic elements of informed consent. None contained any information regarding whether genetic information relevant to health would be disclosed, whether participants may share in commercial products, the extent of confidentiality protections, and the inclusion of additional consent forms for future storage and use of tissue samples. Information regarding genetic risks and withdrawal of samples were rarely mentioned (1/7), whereas limits on future use of samples were mentioned in 3 of 7 consent forms.Ultimately, consent forms are not likely to address key issues regarding genetic research that have been recommended by research ethics guidelines. We recommend enhanced educational efforts to increase awareness, on the part of researchers, of information that should be included in consent forms. (shrink)

The appropriate understanding and fast processing of lengthy legal documents are computationally challenging problems. Designing efficient automatic summarization techniques can potentially be the key to deal with such issues. Extractive summarization is one of the most popular approaches for forming summaries out of such lengthy documents, via the process of summary-relevant sentence selection. An efficient application of this approach involves appropriate scoring of sentences, which helps in the identification of more informative and essential sentences from the document. In this work, (...) a novel sentence scoring approach DCESumm is proposed which consists of supervised sentence-level summary relevance prediction, as well as unsupervised clustering-based document-level score enhancement. Experimental results on two legal document summarization datasets, BillSum and Forum of Information Retrieval Evaluation (FIRE), reveal that the proposed approach can achieve significant improvements over the current state-of-the-art approaches. More specifically it achieves ROUGE metric F1-score improvements of (1−6)% and (6−12)% for the BillSum and FIRE test sets respectively. Such impressive summarization results suggest the usefulness of the proposed approach in finding the gist of a lengthy legal document, thereby providing crucial assistance to legal practitioners. (shrink)