Institution
University of South Australia
Education•Adelaide, South Australia, Australia•
About: University of South Australia is a education organization based out in Adelaide, South Australia, Australia. It is known for research contribution in the topics: Population & Context (language use). The organization has 10086 authors who have published 32587 publications receiving 913683 citations. The organization is also known as: The University of South Australia & UniSA.
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23 Sep 2015TL;DR: The stability of aggregate-level preferences in longitudinal discrete choice experiments Towhidul Islam and Jordan J. Louviere show that best-worst analysis using delivered pizza and toothpaste examples is an alternative to ratings data.
Abstract: Preface Acknowledgments Theory and Methods: 1. Introduction and overview of the book 2. The BWS object case 3. The BWS profile case 4. The BWS multi-profile case 5. Basic models 6. Looking forward Applications - Case 1: 7. BWS object case application: attitudes towards end-of-life care Terry N. Flynn, Elisabeth Huynh and Charles Corke 8. How consumers choose wine: using best-worst scaling across countries Larry Lockshin and Eli Cohen 9. Best-worst scaling: an alternative to ratings data Geoffrey N. Soutar, Jillian C. Sweeney and Janet R. McColl-Kennedy Applications - Case 2: 10. When the ayes don't have it: supplementing an accept/reject DCE with a case 2 best-worst scaling task Richard T. Carson and Jordan J. Louviere 11. BWS profile case application: preferences for treatment in dentistry Emma McIntosh and Terry N. Flynn 12. BWS profile case application: preferences for quality of life in Australia Terry N. Flynn and Elisabeth Huynh Applications - Case 3: 13. The stability of aggregate-level preferences in longitudinal discrete choice experiments Towhidul Islam and Jordan J. Louviere 14. Case 3 best-worst analysis using delivered pizza and toothpaste examples Bart D. Frischknecht and Jordan J. Louviere 15. Using alternative-specific DCE designs and best and worst choices to model choices Jordan J. Louviere References Subject index Author index.
411 citations
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TL;DR: This study investigated whether KCNQ2/3 mutations are a frequent cause of epileptic encephalopathies with an early onset and whether a recognizable phenotype exists.
Abstract: OBJECTIVE: KCNQ2 and KCNQ3 mutations are known to be responsible for benign familial neonatal seizures (BFNS). A few reports on patients with a KCNQ2 mutation with a more severe outcome exist, but a definite relationship has not been established. In this study we investigated whether KCNQ2/3 mutations are a frequent cause of epileptic encephalopathies with an early onset and whether a recognizable phenotype exists. METHODS: We analyzed 80 patients with unexplained neonatal or early-infantile seizures and associated psychomotor retardation for KCNQ2 and KCNQ3 mutations. Clinical and imaging data were reviewed in detail. RESULTS: We found 7 different heterozygous KCNQ2 mutations in 8 patients (8/80; 10%); 6 mutations arose de novo. One parent with a milder phenotype was mosaic for the mutation. No KCNQ3 mutations were found. The 8 patients had onset of intractable seizures in the first week of life with a prominent tonic component. Seizures generally resolved by age 3 years but the children had profound, or less frequently severe, intellectual disability with motor impairment. Electroencephalography (EEG) at onset showed a burst-suppression pattern or multifocal epileptiform activity. Early magnetic resonance imaging (MRI) of the brain showed characteristic hyperintensities in the basal ganglia and thalamus that later resolved. INTERPRETATION: KCNQ2 mutations are found in a substantial proportion of patients with a neonatal epileptic encephalopathy with a potentially recognizable electroclinical and radiological phenotype. This suggests that KCNQ2 screening should be included in the diagnostic workup of refractory neonatal seizures of unknown origin.
410 citations
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TL;DR: In this article, the concept of value and its relationship to service quality, satisfaction and behavioural intentions was studied in a sample of 218 sports and leisure centre customers, using structural equation modelling.
409 citations
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TL;DR: 11 recommendations for MSK pain care are identified to ensure care is patient centred, screen for red flag conditions, assess psychosocial factors, use imaging selectively, undertake a physical examination, monitor patient progress, and provide education/information to improve the quality of care.
Abstract: Objectives To identify common recommendations for high-quality care for the most common musculoskeletal (MSK) pain sites encountered by clinicians in emergency and primary care (spinal (lumbar, thoracic and cervical), hip/knee (including osteoarthritis [OA] and shoulder) from contemporary, high-quality clinical practice guidelines (CPGs). Design Systematic review, critical appraisal and narrative synthesis of MSK pain CPG recommendations. Eligibility criteria Included MSK pain CPGs were written in English, rated as high quality, published from 2011, focused on adults and described development processes. Excluded CPGs were for: traumatic MSK pain, single modalities (eg, surgery), traditional healing/medicine, specific disease processes (eg, inflammatory arthropathies) or those that required payment. Data sources Four scientific databases (MEDLINE, Embase, CINAHL and Physiotherapy Evidence Database) and four guideline repositories. Results 6232 records were identified, 44 CPGs were appraised and 11 were rated as high quality (low back pain: 4, OA: 4, neck: 2 and shoulder: 1). We identified 11 recommendations for MSK pain care: ensure care is patient centred, screen for red flag conditions, assess psychosocial factors, use imaging selectively, undertake a physical examination, monitor patient progress, provide education/information, address physical activity/exercise, use manual therapy only as an adjunct to other treatments, offer high-quality non-surgical care prior to surgery and try to keep patients at work. Conclusion These 11 recommendations guide healthcare consumers, clinicians, researchers and policy makers to manage MSK pain. This should improve the quality of care of MSK pain.
408 citations
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University of Washington1, Creighton University2, Central South University3, Huazhong University of Science and Technology4, Radboud University Nijmegen5, Karolinska Institutet6, Katholieke Universiteit Leuven7, Leiden University Medical Center8, University of Adelaide9, South Australia Pathology10, Boston Children's Hospital11, University of South Australia12, University of Antwerp13, University of California, San Diego14, University of California, Davis15, University of Melbourne16, Florey Institute of Neuroscience and Mental Health17, Howard Hughes Medical Institute18
TL;DR: Twenty-five genes showing a bias for autism versus intellectual disability and a network associated with high-functioning autism are highlighted, and clinical follow-up for NAA15, KMT5B, and ASH1L highlighted new syndromic and nonsyndromic forms of disease.
Abstract: Gene-disruptive mutations contribute to the biology of neurodevelopmental disorders (NDDs), but most of the related pathogenic genes are not known. We sequenced 208 candidate genes from >11,730 cases and >2,867 controls. We identified 91 genes, including 38 new NDD genes, with an excess of de novo mutations or private disruptive mutations in 5.7% of cases. Drosophila functional assays revealed a subset with increased involvement in NDDs. We identified 25 genes showing a bias for autism versus intellectual disability and highlighted a network associated with high-functioning autism (full-scale IQ >100). Clinical follow-up for NAA15, KMT5B, and ASH1L highlighted new syndromic and nonsyndromic forms of disease.
404 citations
Authors
Showing all 10298 results
Name | H-index | Papers | Citations |
---|---|---|---|
Andrew P. McMahon | 162 | 415 | 90650 |
Timothy P. Hughes | 145 | 831 | 91357 |
Jeremy K. Nicholson | 141 | 773 | 80275 |
Peng Shi | 137 | 1371 | 65195 |
Daniel Thomas | 134 | 846 | 84224 |
Jian Li | 133 | 2863 | 87131 |
Matthew Jones | 125 | 1161 | 96909 |
Ulrich S. Schubert | 122 | 2229 | 85604 |
Elaine Holmes | 119 | 560 | 58975 |
Arne Astrup | 114 | 866 | 68877 |
Richard Gray | 109 | 808 | 78580 |
John B. Furness | 103 | 597 | 37668 |
Thomas J. Jentsch | 101 | 238 | 32810 |
Ben W.J. Mol | 101 | 1485 | 47733 |
John C. Lindon | 99 | 488 | 44063 |