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The predictive role of symptoms in COVID-19 diagnostic models: A longitudinal insight
- Olivia Bird, Eva P. Galiza, David Neil Baxter, Marta Boffito, Duncan Browne, Fiona Burns, David R. Chadwick, Rebecca Clark, Catherine A. Cosgrove, James Galloway, Anna L. Goodman, Amardeep Heer, Andrew Higham, Shalini Iyengar, Christopher Jeanes, Philip A. Kalra, Christina Kyriakidou, Judy M. Bradley, Chigomezgo Munthali, Angela M. Minassian, Fiona McGill, Patrick Moore, Imrozia Munsoor, Helen Nicholls, Orod Osanlou, Jonathan Packham, Carol H. Pretswell, Alberto San Francisco Ramos, Dinesh Saralaya, Ray P. Sheridan, Richard Smith, Roy L. Soiza, Pauline A. Swift, Emma C. Thomson, Jeremy Turner, Marianne Elizabeth Viljoen, Paul T. Heath, Irina Chis Ster
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- Journal:
- Epidemiology & Infection / Volume 152 / 2024
- Published online by Cambridge University Press:
- 22 January 2024, e37
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To investigate the symptoms of SARS-CoV-2 infection, their dynamics and their discriminatory power for the disease using longitudinally, prospectively collected information reported at the time of their occurrence. We have analysed data from a large phase 3 clinical UK COVID-19 vaccine trial. The alpha variant was the predominant strain. Participants were assessed for SARS-CoV-2 infection via nasal/throat PCR at recruitment, vaccination appointments, and when symptomatic. Statistical techniques were implemented to infer estimates representative of the UK population, accounting for multiple symptomatic episodes associated with one individual. An optimal diagnostic model for SARS-CoV-2 infection was derived. The 4-month prevalence of SARS-CoV-2 was 2.1%; increasing to 19.4% (16.0%–22.7%) in participants reporting loss of appetite and 31.9% (27.1%–36.8%) in those with anosmia/ageusia. The model identified anosmia and/or ageusia, fever, congestion, and cough to be significantly associated with SARS-CoV-2 infection. Symptoms’ dynamics were vastly different in the two groups; after a slow start peaking later and lasting longer in PCR+ participants, whilst exhibiting a consistent decline in PCR- participants, with, on average, fewer than 3 days of symptoms reported. Anosmia/ageusia peaked late in confirmed SARS-CoV-2 infection (day 12), indicating a low discrimination power for early disease diagnosis.
Injection fears and COVID-19 vaccine hesitancy
- Daniel Freeman, Sinéad Lambe, Ly-Mee Yu, Jason Freeman, Andrew Chadwick, Cristian Vaccari, Felicity Waite, Laina Rosebrock, Ariane Petit, Samantha Vanderslott, Stephan Lewandowsky, Michael Larkin, Stefania Innocenti, Helen McShane, Andrew J. Pollard, Bao Sheng Loe
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- Journal:
- Psychological Medicine / Volume 53 / Issue 4 / March 2023
- Published online by Cambridge University Press:
- 11 June 2021, pp. 1185-1195
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Background
When vaccination depends on injection, it is plausible that the blood-injection-injury cluster of fears may contribute to hesitancy. Our primary aim was to estimate in the UK adult population the proportion of COVID-19 vaccine hesitancy explained by blood-injection-injury fears.
MethodsIn total, 15 014 UK adults, quota sampled to match the population for age, gender, ethnicity, income and region, took part (19 January–5 February 2021) in a non-probability online survey. The Oxford COVID-19 Vaccine Hesitancy Scale assessed intent to be vaccinated. Two scales (Specific Phobia Scale-blood-injection-injury phobia and Medical Fear Survey–injections and blood subscale) assessed blood-injection-injury fears. Four items from these scales were used to create a factor score specifically for injection fears.
ResultsIn total, 3927 (26.2%) screened positive for blood-injection-injury phobia. Individuals screening positive (22.0%) were more likely to report COVID-19 vaccine hesitancy compared to individuals screening negative (11.5%), odds ratio = 2.18, 95% confidence interval (CI) 1.97–2.40, p < 0.001. The population attributable fraction (PAF) indicated that if blood-injection-injury phobia were absent then this may prevent 11.5% of all instances of vaccine hesitancy, AF = 0.11; 95% CI 0.09–0.14, p < 0.001. COVID-19 vaccine hesitancy was associated with higher scores on the Specific Phobia Scale, r = 0.22, p < 0.001, Medical Fear Survey, r = 0.23, p = <0.001 and injection fears, r = 0.25, p < 0.001. Injection fears were higher in youth and in Black and Asian ethnic groups, and explained a small degree of why vaccine hesitancy is higher in these groups.
ConclusionsAcross the adult population, blood-injection-injury fears may explain approximately 10% of cases of COVID-19 vaccine hesitancy. Addressing such fears will likely improve the effectiveness of vaccination programmes.
COVID-19 vaccine hesitancy in the UK: the Oxford coronavirus explanations, attitudes, and narratives survey (Oceans) II
- Daniel Freeman, Bao S. Loe, Andrew Chadwick, Cristian Vaccari, Felicity Waite, Laina Rosebrock, Lucy Jenner, Ariane Petit, Stephan Lewandowsky, Samantha Vanderslott, Stefania Innocenti, Michael Larkin, Alberto Giubilini, Ly-Mee Yu, Helen McShane, Andrew J. Pollard, Sinéad Lambe
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- Journal:
- Psychological Medicine / Volume 52 / Issue 14 / October 2022
- Published online by Cambridge University Press:
- 11 December 2020, pp. 3127-3141
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Background
Our aim was to estimate provisional willingness to receive a coronavirus 2019 (COVID-19) vaccine, identify predictive socio-demographic factors, and, principally, determine potential causes in order to guide information provision.
MethodsA non-probability online survey was conducted (24th September−17th October 2020) with 5,114 UK adults, quota sampled to match the population for age, gender, ethnicity, income, and region. The Oxford COVID-19 vaccine hesitancy scale assessed intent to take an approved vaccine. Structural equation modelling estimated explanatory factor relationships.
Results71.7% (n=3,667) were willing to be vaccinated, 16.6% (n=849) were very unsure, and 11.7% (n=598) were strongly hesitant. An excellent model fit (RMSEA=0.05/CFI=0.97/TLI=0.97), explaining 86% of variance in hesitancy, was provided by beliefs about the collective importance, efficacy, side-effects, and speed of development of a COVID-19 vaccine. A second model, with reasonable fit (RMSEA=0.03/CFI=0.93/TLI=0.92), explaining 32% of variance, highlighted two higher-order explanatory factors: ‘excessive mistrust’ (r=0.51), including conspiracy beliefs, negative views of doctors, and need for chaos, and ‘positive healthcare experiences’ (r=−0.48), including supportive doctor interactions and good NHS care. Hesitancy was associated with younger age, female gender, lower income, and ethnicity, but socio-demographic information explained little variance (9.8%). Hesitancy was associated with lower adherence to social distancing guidelines.
ConclusionsCOVID-19 vaccine hesitancy is relatively evenly spread across the population. Willingness to take a vaccine is closely bound to recognition of the collective importance. Vaccine public information that highlights prosocial benefits may be especially effective. Factors such as conspiracy beliefs that foster mistrust and erode social cohesion will lower vaccine up-take.
Contributor affiliations
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- By Frank Andrasik, Melissa R. Andrews, Ana Inés Ansaldo, Evangelos G. Antzoulatos, Lianhua Bai, Ellen Barrett, Linamara Battistella, Nicolas Bayle, Michael S. Beattie, Peter J. Beek, Serafin Beer, Heinrich Binder, Claire Bindschaedler, Sarah Blanton, Tasia Bobish, Michael L. Boninger, Joseph F. Bonner, Chadwick B. Boulay, Vanessa S. Boyce, Anna-Katharine Brem, Jacqueline C. Bresnahan, Floor E. Buma, Mary Bartlett Bunge, John H. Byrne, Jeffrey R. Capadona, Stefano F. Cappa, Diana D. Cardenas, Leeanne M. Carey, S. Thomas Carmichael, Glauco A. P. Caurin, Pablo Celnik, Kimberly M. Christian, Stephanie Clarke, Leonardo G. Cohen, Adriana B. Conforto, Rory A. Cooper, Rosemarie Cooper, Steven C. Cramer, Armin Curt, Mark D’Esposito, Matthew B. Dalva, Gavriel David, Brandon Delia, Wenbin Deng, Volker Dietz, Bruce H. Dobkin, Marco Domeniconi, Edith Durand, Tracey Vause Earland, Georg Ebersbach, Jonathan J. Evans, James W. Fawcett, Uri Feintuch, Toby A. Ferguson, Marie T. Filbin, Diasinou Fioravante, Itzhak Fischer, Agnes Floel, Herta Flor, Karim Fouad, Richard S. J. Frackowiak, Peter H. Gorman, Thomas W. Gould, Jean-Michel Gracies, Amparo Gutierrez, Kurt Haas, C.D. Hall, Hans-Peter Hartung, Zhigang He, Jordan Hecker, Susan J. Herdman, Seth Herman, Leigh R. Hochberg, Ahmet Höke, Fay B. Horak, Jared C. Horvath, Richard L. Huganir, Friedhelm C. Hummel, Beata Jarosiewicz, Frances E. Jensen, Michael Jöbges, Larry M. Jordan, Jon H. Kaas, Andres M. Kanner, Noomi Katz, Matthew S. Kayser, Annmarie Kelleher, Gerd Kempermann, Timothy E. Kennedy, Jürg Kesselring, Fary Khan, Rachel Kizony, Jeffery D. Kocsis, Boudewijn J. Kollen, Hubertus Köller, John W. Krakauer, Hermano I. Krebs, Gert Kwakkel, Bradley Lang, Catherine E. Lang, Helmar C. Lehmann, Angelo C. Lepore, Glenn S. Le Prell, Mindy F. Levin, Joel M. Levine, David A. Low, Marilyn MacKay-Lyons, Jeffrey D. Macklis, Margaret Mak, Francine Malouin, William C. Mann, Paul D. Marasco, Christopher J. Mathias, Laura McClure, Jan Mehrholz, Lorne M. Mendell, Robert H. Miller, Carol Milligan, Beth Mineo, Simon W. Moore, Jennifer Morgan, Charbel E-H. Moussa, Martin Munz, Randolph J. Nudo, Joseph J. Pancrazio, Theresa Pape, Alvaro Pascual-Leone, Kristin M. Pearson-Fuhrhop, P. Hunter Peckham, Tamara L. Pelleshi, Catherine Verrier Piersol, Thomas Platz, Marcus Pohl, Dejan B. Popović, Andrew M. Poulos, Maulik Purohit, Hui-Xin Qi, Debbie Rand, Mahendra S. Rao, Josef P. Rauschecker, Aimee Reiss, Carol L. Richards, Keith M. Robinson, Melvyn Roerdink, John C. Rosenbek, Serge Rossignol, Edward S. Ruthazer, Arash Sahraie, Krishnankutty Sathian, Marc H. Schieber, Brian J. Schmidt, Michael E. Selzer, Mijail D. Serruya, Himanshu Sharma, Michael Shifman, Jerry Silver, Thomas Sinkjær, George M. Smith, Young-Jin Son, Tim Spencer, John D. Steeves, Oswald Steward, Sheela Stuart, Austin J. Sumner, Chin Lik Tan, Robert W. Teasell, Gareth Thomas, Aiko K. Thompson, Richard F. Thompson, Wesley J. Thompson, Erika Timar, Ceri T. Trevethan, Christopher Trimby, Gary R. Turner, Mark H. Tuszynski, Erna A. van Niekerk, Ricardo Viana, Difei Wang, Anthony B. Ward, Nick S. Ward, Stephen G. Waxman, Patrice L. Weiss, Jörg Wissel, Steven L. Wolf, Jonathan R. Wolpaw, Sharon Wood-Dauphinee, Ross D. Zafonte, Binhai Zheng, Richard D. Zorowitz
- Edited by Michael Selzer, Stephanie Clarke, Leonardo Cohen, Gert Kwakkel, Robert Miller, Case Western Reserve University, Ohio
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- Textbook of Neural Repair and Rehabilitation
- Published online:
- 05 May 2014
- Print publication:
- 24 April 2014, pp ix-xvi
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- By Frank Andrasik, Melissa R. Andrews, Ana Inés Ansaldo, Evangelos G. Antzoulatos, Lianhua Bai, Ellen Barrett, Linamara Battistella, Nicolas Bayle, Michael S. Beattie, Peter J. Beek, Serafin Beer, Heinrich Binder, Claire Bindschaedler, Sarah Blanton, Tasia Bobish, Michael L. Boninger, Joseph F. Bonner, Chadwick B. Boulay, Vanessa S. Boyce, Anna-Katharine Brem, Jacqueline C. Bresnahan, Floor E. Buma, Mary Bartlett Bunge, John H. Byrne, Jeffrey R. Capadona, Stefano F. Cappa, Diana D. Cardenas, Leeanne M. Carey, S. Thomas Carmichael, Glauco A. P. Caurin, Pablo Celnik, Kimberly M. Christian, Stephanie Clarke, Leonardo G. Cohen, Adriana B. Conforto, Rory A. Cooper, Rosemarie Cooper, Steven C. Cramer, Armin Curt, Mark D’Esposito, Matthew B. Dalva, Gavriel David, Brandon Delia, Wenbin Deng, Volker Dietz, Bruce H. Dobkin, Marco Domeniconi, Edith Durand, Tracey Vause Earland, Georg Ebersbach, Jonathan J. Evans, James W. Fawcett, Uri Feintuch, Toby A. Ferguson, Marie T. Filbin, Diasinou Fioravante, Itzhak Fischer, Agnes Floel, Herta Flor, Karim Fouad, Richard S. J. Frackowiak, Peter H. Gorman, Thomas W. Gould, Jean-Michel Gracies, Amparo Gutierrez, Kurt Haas, C.D. Hall, Hans-Peter Hartung, Zhigang He, Jordan Hecker, Susan J. Herdman, Seth Herman, Leigh R. Hochberg, Ahmet Höke, Fay B. Horak, Jared C. Horvath, Richard L. Huganir, Friedhelm C. Hummel, Beata Jarosiewicz, Frances E. Jensen, Michael Jöbges, Larry M. Jordan, Jon H. Kaas, Andres M. Kanner, Noomi Katz, Matthew S. Kayser, Annmarie Kelleher, Gerd Kempermann, Timothy E. Kennedy, Jürg Kesselring, Fary Khan, Rachel Kizony, Jeffery D. Kocsis, Boudewijn J. Kollen, Hubertus Köller, John W. Krakauer, Hermano I. Krebs, Gert Kwakkel, Bradley Lang, Catherine E. Lang, Helmar C. Lehmann, Angelo C. Lepore, Glenn S. Le Prell, Mindy F. Levin, Joel M. Levine, David A. Low, Marilyn MacKay-Lyons, Jeffrey D. Macklis, Margaret Mak, Francine Malouin, William C. Mann, Paul D. Marasco, Christopher J. Mathias, Laura McClure, Jan Mehrholz, Lorne M. Mendell, Robert H. Miller, Carol Milligan, Beth Mineo, Simon W. Moore, Jennifer Morgan, Charbel E-H. Moussa, Martin Munz, Randolph J. Nudo, Joseph J. Pancrazio, Theresa Pape, Alvaro Pascual-Leone, Kristin M. Pearson-Fuhrhop, P. Hunter Peckham, Tamara L. Pelleshi, Catherine Verrier Piersol, Thomas Platz, Marcus Pohl, Dejan B. Popović, Andrew M. Poulos, Maulik Purohit, Hui-Xin Qi, Debbie Rand, Mahendra S. Rao, Josef P. Rauschecker, Aimee Reiss, Carol L. Richards, Keith M. Robinson, Melvyn Roerdink, John C. Rosenbek, Serge Rossignol, Edward S. Ruthazer, Arash Sahraie, Krishnankutty Sathian, Marc H. Schieber, Brian J. Schmidt, Michael E. Selzer, Mijail D. Serruya, Himanshu Sharma, Michael Shifman, Jerry Silver, Thomas Sinkjær, George M. Smith, Young-Jin Son, Tim Spencer, John D. Steeves, Oswald Steward, Sheela Stuart, Austin J. Sumner, Chin Lik Tan, Robert W. Teasell, Gareth Thomas, Aiko K. Thompson, Richard F. Thompson, Wesley J. Thompson, Erika Timar, Ceri T. Trevethan, Christopher Trimby, Gary R. Turner, Mark H. Tuszynski, Erna A. van Niekerk, Ricardo Viana, Difei Wang, Anthony B. Ward, Nick S. Ward, Stephen G. Waxman, Patrice L. Weiss, Jörg Wissel, Steven L. Wolf, Jonathan R. Wolpaw, Sharon Wood-Dauphinee, Ross D. Zafonte, Binhai Zheng, Richard D. Zorowitz
- Edited by Michael E. Selzer, Stephanie Clarke, Leonardo G. Cohen, Gert Kwakkel, Robert H. Miller, Case Western Reserve University, Ohio
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- Textbook of Neural Repair and Rehabilitation
- Published online:
- 05 June 2014
- Print publication:
- 24 April 2014, pp ix-xvi
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2 - Recent Shifts in the Relationship between the Internet and Democratic Engagement in Britain and the United States
- Edited by Eva Anduiza, Michael James Jensen, Laia Jorba
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- Digital Media and Political Engagement Worldwide
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- 05 July 2012
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- 29 June 2012, pp 39-55
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Summary
Introduction
The internet is evolving into one the most significant enablers of political innovation since the emergence of mass democracy. Over the past decade, few areas of social and political life have escaped its influence. Because of the potentially huge scope of the internet (see Chadwick and Howard 2009b; Chadwick 2006), this chapter has two interrelated objectives. First, following a brief explication of concepts, it discusses significant recent shifts in what we know, or should seek to know, about the internet's role in promoting political knowledge and political engagement, with reference to some important strands of literature from the United States and Britain. Second, it generates some hypotheses about the likely effects of recent changes in the online environment, through discussion of British and U.S. examples of what is widely called web.2.0. The broad argument is that continuing to frame research in this area in terms of traditional understandings of engagement, participation, and deliberative democracy risks missing the significance of three key forces in the contemporary political context of these two countries: granularity, informational exuberance, and by-product political learning.
Web 2.0, Granularity, and Informational Exuberance
Though widely used, the concept of web 2.0 has eluded precise definition. Originally the creation of Silicon Valley technologists, web 2.0 has long since escaped the business community and is an idea that loosely organizes a variety of concerns across a range of scholarly disciplines. O’Reilly is widely regarded to have been the first to popularize the term in 2003. His technology-focused approach defined web 2.0 in terms of seven key principles: “the web as platform,” “harnessing collective intelligence,” “data is the next ‘Intel inside,’” “the end of the software release cycle,” “lightweight programming models,” “software above the level of a single device,” and “rich user experiences” (O’Reilly 2007, 18, 22, 27, 30, 31, 33, 34). Chadwick and Howard (2009a) begin from these technological principles but explicate their relevance for politics and suggest the following formulation: “the internet as a platform for political discourse; the collective intelligence emergent from political web use; the importance of data over particular software and hardware applications; perpetual experimentalism in the public domain; the creation of small scale forms of political engagement through consumerism; the propagation of political content over multiple applications; and rich user experiences on political websites” (Chadwick and Howard 2009a, 4).
The case for strategic international alliances to harness nutritional genomics for public and personal health†
- Jim Kaput, Jose M. Ordovas, Lynnette Ferguson, Ben van Ommen, Raymond L. Rodriguez, Lindsay Allen, Bruce N. Ames, Kevin Dawson, Bruce German, Ronald Krauss, Wasyl Malyj, Michael C. Archer, Stephen Barnes, Amelia Bartholomew, Ruth Birk, Peter van Bladeren, Kent J. Bradford, Kenneth H. Brown, Rosane Caetano, David Castle, Ruth Chadwick, Stephen Clarke, Karine Clément, Craig A. Cooney, Dolores Corella, Ivana Beatrice Manica da Cruz, Hannelore Daniel, Troy Duster, Sven O. E. Ebbesson, Ruan Elliott, Susan Fairweather-Tait, Jim Felton, Michael Fenech, John W. Finley, Nancy Fogg-Johnson, Rosalynn Gill-Garrison, Michael J. Gibney, Peter J. Gillies, Jan-Ake Gustafsson, John L. Hartman IV, Lin He, Jae-Kwan Hwang, Jean-Philippe Jais, Yangsoo Jang, Hans Joost, Claudine Junien, Mitchell Kanter, Warren A. Kibbe, Berthold Koletzko, Bruce R. Korf, Kenneth Kornman, David W. Krempin, Dominique Langin, Denis R. Lauren, Jong Ho Lee, Gilbert A. Leveille, Su-Ju Lin, John Mathers, Michael Mayne, Warren McNabb, John A. Milner, Peter Morgan, Michael Muller, Yuri Nikolsky, Frans van der Ouderaa, Taesun Park, Norma Pensel, Francisco Perez-Jimenez, Kaisa Poutanen, Matthew Roberts, Wim H.M. Saris, Gertrud Schuster, Andrew N. Shelling, Artemis P. Simopoulos, Sue Southon, E. Shyong Tai, Bradford Towne, Paul Trayhurn, Ricardo Uauy, Willard J. Visek, Craig Warden, Rick Weiss, John Wiencke, Jack Winkler, George L. Wolff, Xi Zhao-Wilson, Jean-Daniel Zucker
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- Journal:
- British Journal of Nutrition / Volume 94 / Issue 5 / November 2005
- Published online by Cambridge University Press:
- 08 March 2007, pp. 623-632
- Print publication:
- November 2005
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Nutrigenomics is the study of how constituents of the diet interact with genes, and their products, to alter phenotype and, conversely, how genes and their products metabolise these constituents into nutrients, antinutrients, and bioactive compounds. Results from molecular and genetic epidemiological studies indicate that dietary unbalance can alter gene–nutrient interactions in ways that increase the risk of developing chronic disease. The interplay of human genetic variation and environmental factors will make identifying causative genes and nutrients a formidable, but not intractable, challenge. We provide specific recommendations for how to best meet this challenge and discuss the need for new methodologies and the use of comprehensive analyses of nutrient–genotype interactions involving large and diverse populations. The objective of the present paper is to stimulate discourse and collaboration among nutrigenomic researchers and stakeholders, a process that will lead to an increase in global health and wellness by reducing health disparities in developed and developing countries.