60 research outputs found

    The role of metrology in axSpA : does it provide unique information in assessing patients and predicting outcome? Results from the BSRBR-AS registry

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    ACKNOWLEDGMENTS We thank the staff who contributed to running the BSRBR-AS register and we also thank the recruiting staff at the clinical centers, details of which are available at: www.abdn.ac.uk/bsrbr-as.Peer reviewedPostprin

    Childbearing intentions in a low fertility context: the case of Romania

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    This paper applies the Theory of Planned Behaviour (TPB) to find out the predictors of fertility intentions in Romania, a low-fertility country. We analyse how attitudes, subjective norms and perceived behavioural control relate to the intention to have a child among childless individuals and one-child parents. Principal axis factor analysis confirms which items proposed by the Generation and Gender Survey (GGS 2005) act as valid and reliable measures of the suggested theoretical socio-psychological factors. Four parity-specific logistic regression models are applied to evaluate the relationship between the socio-psychological factors and childbearing intentions. Social pressure emerges as the most important aspect in fertility decision-making among childless individuals and one-child parents, and positive attitudes towards childbearing are a strong component in planning for a child. This paper also underlines the importance of the region-specific factors when studying childbearing intentions: planning for the second child significantly differs among the development regions, representing the cultural and socio-economic divisions of the Romanian territory

    Climate, human behaviour or environment: individual-based modelling of Campylobacter seasonality and strategies to reduce disease burden

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    Acknowledgements: We thank colleagues within the Modelling, Evidence and Policy Research Group for useful feedback on this manuscript. Competing interests: The authors declare that they have no competing interests. Availability of data and materials: The R code used in this research is available at https://gitlab.com/rasanderson/campylobacter-microsimulation; it is platform independent, R version 3.3.0 and above. Funding: This research was funded by Medical Research Council Grant, Natural Environment Research Council, Economic and Social Research Council, Biotechnology and Biological Sciences Research Council, and the Food Standards Agency through the Environmental and Social Ecology of Human Infectious Diseases Initiative (Sources, seasonality, transmission and control: Campylobacter and human behaviour in a changing environment (ENIGMA); Grant Reference G1100799-1). PRH, SJO’B, and IRL are funded in part by the NIHR Health Protection Research Unit in Gastrointestinal Infection, at the University of Liverpool. PRH and IRL are also funded in part by the NIHR Health Protection Research Unit in Emergency Preparedness and Response, at King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health or Public Health England.Peer reviewedPublisher PD
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