38 research outputs found

    Social-ecological, motivational and volitional factors for initiating and maintaining physical activity in the context of HIV

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    Sport and exercise can have several health benefits for people living with HIV. These benefits can be achieved through different types of physical activity, adapting to disease progression, motivation and social-ecological options. However, physical activity levels and adherence to exercise are generally low in people living with HIV. At the same time, high drop-out rates in intervention studies are prevalent; even though they often entail more favourable conditions than interventions in the natural settings. Thus, in the framework of an intervention study, the present study aims to explore social-ecological, motivational and volitional correlates of South African women living with HIV with regard to physical activity and participation in a sport and exercise health promotion programme. The qualitative data was produced in the framework of a non-randomised pre-post intervention study that evaluated structure, processes and outcomes of a 10-week sport and exercise programme. All 25 participants of the programme were included in this analysis, independent of compliance. Data was produced through questionnaires, participatory group discussions, body image pictures, research diaries and individual semi-structured interviews. All participants lived in a low socioeconomic, disadvantaged setting. Hence, the psychological correlates are contextualised and social-ecological influences on perception and behaviour are discussed. The results show the importance of considering social-cultural and environmental influences on individual motives, perceptions and expectancies, the fear of disclosure and stigmatisation, sport and exercise-specific group dynamics and self-supporting processes. Opportunities and strategies to augment physical activity and participation in sport and exercise programmes in the context of HIV are discussed.Scopu

    Experimental progress in positronium laser physics

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    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
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