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Background: The experiences of professionals in well-established recovery-oriented programs are valuable for professionals in similar practice settings. This study explored professionals’ experiences with providing recovery-oriented services in community psychiatric rehabilitation organizations. Methods: Semi-structured interviews were conducted with 14 professionals from five recovery-oriented psychiatric rehabilitation organizations in Taiwan. The interviews were recorded and transcribed verbatim. Thematic analysis was used for the qualitative data analysis. Results: The analyses documented three main themes with 13 subthemes. Recovery-oriented service implementation included seven subthemes: Enabling clients to set their own goals and make decisions, using a strengths-based approach, establishing partnerships with clients, improving individuals’ self-acceptance, encouraging community participation, seeking family, peer, and organizational support, and building team collaboration. Problems with implementing recovery-oriented services included limited policy and organizational support, a lack of understanding of recovery among professionals, stigma, clients’ lack of motivation or self-confidence in their own ability to achieve recovery, and passive or overprotective family members. Strategies to resolve implementation problems included policy changes and organizational support, improving the recovery competence and confidence of professionals, and family and public education. Conclusions: To date, this is the first known study examining the perspectives of mental health professionals who have experience implementing recovery-oriented services in Asia. The participants identified family collaboration, anti-stigma efforts, and changes in policy and attitudes as critical to successful implementation and delivery of recovery-oriented services. [ABSTRACT FROM AUTHOR]

Background: The genetic factors leading to hypertension have been extensively studied, and large numbers of research papers have been published on the subject. One of hypertension researchers' primary research tasks is to locate key hypertension-related genes in abstracts. However, gathering such information with existing tools is not easy: (1) Searching for articles often returns far too many hits to browse through. (2) The search results do not highlight the hypertension-related genes discovered in the abstract. (3) Even though some text mining services mark up gene names in the abstract, the key genes investigated in a paper are still not distinguished from other genes. To facilitate the information gathering process for hypertension researchers, one solution would be to extract the key hypertension-related genes in each abstract. Three major tasks are involved in the construction of this system: (1) gene and hypertension named entity recognition, (2) section categorization, and (3) gene-hypertension relation extraction. Results: We first compare the retrieval performance achieved by individually adding template features and position features to the baseline system. Then, the combination of both is examined. We found that using position features can almost double the original AUC score (0.8140vs.0.4936) of the baseline system. However, adding template features only results in marginal improvement (0.0197). Including both improves AUC to 0.8184, indicating that these two sets of features are complementary, and do not have overlapping effects. We then examine the performance in a different domain--diabetes, and the result shows a satisfactory AUC of 0.83. Conclusion: Our approach successfully exploits template features to recognize true hypertension-related gene mentions and position features to distinguish key genes from other related genes. Templates are automatically generated and checked by biologists to minimize labor costs. Our approach integrates the advantages of machine learning models and pattern matching. To the best of our knowledge, this the first systematic study of extracting hypertension-related genes and the first attempt to create a hypertension-gene relation corpus based on the GAD database. Furthermore, our paper proposes and tests novel features for extracting key hypertension genes, such as relative position, section, and template features, which could also be applied to key-gene extraction for other diseases. [ABSTRACT FROM AUTHOR]