Search

Your search keyword '"Hood, Christina"' showing total 137 results
Start Over Author "Hood, Christina"
137 results on '"Hood, Christina"'

6. PRAISE-HK: A personalized real-time air quality informatics system for citizen participation in exposure and health risk management

Author

Che, Wenwei, Frey, H. Christopher, Fung, Jimmy C.H., Ning, Zhi, Qu, Huamin, Lo, Hong Kam, Chen, Lei, Wong, Tze-Wai, Wong, Michelle K.M., Lee, Ophelia C.W., Carruthers, David, Cheung, Freeman, Chan, Jimmy W.M., Yeung, David W., Fung, Yik Him, Zhang, Xuguo, Stocker, Jenny, Hood, Christina, Hohenberger, Tilman Leo, Leung, King Wai, Louie, Phillip Y.K., Li, Alison T.Y., Sun, Li, Wei, Peng, Li, Zhiyuan, Zhang, Yumiao, Wang, Meilan, Shen, Qiaomu, Huang, Wei, Lee, Enoch, Patwary, Ashraf, Lei, Xiayu, Cheng, Steven, Shakhaoat Hossain, Md, Tang, Kimberly Tasha Jiayi, Lao, XiangQian, Leung, Rae, Chan, Denise, Li, Ying, Yuan, Zibing, and Lau, Alexis K.H.

Published
2020
Full Text
View/download PDF

7. Double counting and the Paris Agreement rulebook

Author

Schneider, Lambert, Duan, Maosheng, Stavins, Robert, Kizzier, Kelley, Broekhoff, Derik, Jotzo, Frank, Winkler, Harald, Lazarus, Michael, Howard, Andrew, and Hood, Christina

Published
2019

9. Characterization of high finesse mirrors: loss, phase shifts and mode structure in an optical cavity

Author

Hood, Christina J., Kimble, H. J., and Ye, Jun

Subjects
Quantum Physics
Abstract

An extensive characterization of high finesse optical cavities used in cavity QED experiments is described. Different techniques in the measurement of the loss and phase shifts associated with the mirror coatings are discussed and their agreement shown. Issues of cavity field mode structure supported by the dielectric coatings are related to our effort to achieve the strongest possible coupling between an atom and the cavity., Comment: 8 pages, 4 figures

Published
2001
Full Text
View/download PDF

10. Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Akeredolu, Alimatu-Sadia, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Aojula, Sonam, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Chatterjee, Shaunak, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, De Waal, Hanelie, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Hussain, Ifrah, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Sopian, Aninditya Salma, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Van Den Tooren, Harriet, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Published
2020
Full Text
View/download PDF

11. The Analysis of Teaching of Medical Schools (AToMS) survey: an analysis of 47,258 timetabled teaching events in 25 UK medical schools relating to timing, duration, teaching formats, teaching content, and problem-based learning

Author

Devine, Oliver Patrick, Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Akeredolu, Alimatu-Sadia, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Aojula, Sonam, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Chatterjee, Shaunak, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, De Waal, Hanelie, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Hussain, Ifrah, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Sopian, Aninditya Salma, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Van Den Tooren, Harriet, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and McManus, I. C.

Published
2020
Full Text
View/download PDF

12. Modelling Street-Scale Resolution Air Quality for the West Midlands (UK) Using the ADMS-Urban RML System

Author

Mensink, Clemens, Jorba, Oriol, Zhong, Jian, Hood, Christina, Johnson, Kate, Stocker, Jenny, Handley, Jonathan, Wolstencroft, Mark, Mazzeo, Andrea, Cai, Xiaoming, Bloss, William James, Mensink, Clemens, Jorba, Oriol, Zhong, Jian, Hood, Christina, Johnson, Kate, Stocker, Jenny, Handley, Jonathan, Wolstencroft, Mark, Mazzeo, Andrea, Cai, Xiaoming, and Bloss, William James

Abstract

Air pollution is a major environmental concern in urban areas, causing substantial adverse effects on human health. This study simulated street-scale resolution air quality for the West Midlands region in the UK using a regional-to-local coupled system, which combined the regional CMAQ model with the local ADMS-Urban model, without double-counting emissions. CMAQ was used to represent dispersion on large temporal and spatial scales, while ADMS-Urban represents the local short-term dispersion from explicit point and road sources. Both models were evaluated against observations with reasonable performance, i.e. CMAQ captured measured air pollutant concentrations at background sites, while coupled ADMS-Urban RML (Regional Model Link) also captured air pollution concentrations at roadside sites, where local effects were important. Street scale air quality maps were produced from the ADMS-Urban RML, which can be linked to health-related exposure studies. The coupled air quality modelling system for WM serves as an effective tool to evaluate potential regional and local air pollution mitigation policies.

Published
2023

15. Improving NOX emissions in Beijing using network observations and a novel perturbed emissions ensemble

Author

Yuan, Le, Popoola, Olalekan, Hood, Christina, Carruthers, David, Jones, Roderic L., Sun, Haitong Zhe, Liu, Huan, Zhang, Qiang, and Archibald, Alexander T.

Abstract

Emissions inventories are crucial inputs to air quality simulations and represent a major source of uncertainty. Various methods have been adopted to optimise emissions inventories, yet in most cases the methods were only applied to total anthropogenic emissions. We have developed a new approach that updates a priori emission estimates by source sector, which are particularly relevant for policy interventions. At its core is a perturbed emissions ensemble (PEE), constructed by perturbing parameters in an a priori emissions inventory within their respective uncertainty ranges. This PEE is then input to an air quality model to generate an ensemble of forward simulations. By comparing the simulation outputs with observations from a dense network, the initial uncertainty ranges are constrained and a posteriori emission estimates are derived. Using this approach, we were able to derive the transport sector NOX emissions for a study area centred around Beijing in 2016 based on a priori emission estimates for 2013. The absolute emissions were found to be 1.5–9 × 104 Mg, corresponding to a 57–93 % reduction from the 2013 levels, yet the night-time fraction of the emissions was 67–178 % higher. These results provide robust and independent evidence of the trends of traffic emission in the study area between 2013 and 2016 reported by previous studies. We also highlighted the impacts of the chemical mechanisms in the underlying model on the emission estimates derived, which is often neglected in emission optimisation studies. This work paves forward the route for rapid analysis and update of emissions inventories using air quality models and routine in situ observations, underscoring the utility of dense observational networks. It also highlights some gaps in the current distribution of monitoring sites in Beijing which result in an underrepresentation of large point sources of NOX.

Published
2022

16. Modelling the Impact of National vs. Local Emission Reduction on PM2.5 in the West Midlands, UK Using WRF-CMAQ

Author

Mazzeo, Andrea, Zhong, Jian, Hood, Christina, Smith, Stephen, Stocker, Jenny, Cai, Xiaoming, Bloss, William, Mazzeo, Andrea, Zhong, Jian, Hood, Christina, Smith, Stephen, Stocker, Jenny, Cai, Xiaoming, and Bloss, William

Abstract

Ambient air pollution from PM2.5 is a major risk to human and environmental health, with significant impacts on mortality and morbidity. Mitigation policies—which may be regional or national in extent—need to consider both primary and secondary particles to be effective, balancing within-region emissions and longer-range transport phenomena. The modelling system WRF-CMAQ was used to simulate the impact of emissions reductions in the West Midlands region of the UK, evaluating the change in total PM2.5 and in its primary and secondary components. Domestic combustion, road transport and agriculture emissions were reduced individually or in combination, at a national or at local level. Combined reduction of road transport and agriculture emissions showed the strongest reduction (29%) in average PM2.5 if applied at national level. At the local level, reductions from domestic combustion were shown to be the most effective policy (13.4% on average). Secondary inorganic fractions of PM2.5 are the most abundant, with 25% NO3− 21% SO42− and 13% NH4+ on average. Scenario analysis shows that the contribution of secondary components to the fractional change of PM2.5 dominates for national policies (up to 0.86 for NO3−) when road transport and agriculture activities are reduced, while at the regional level the elemental and organic carbon fractional changes are dominant (up to 0.64 for organic carbon).

Published
2022

28. Air quality simulations for London using a coupled regional-to-local modelling system

Author

Hood, Christina, MacKenzie, Ian, Stocker, Jenny, Johnson, Kate, Carruthers, David, Vieno, Massimo, and Doherty, Ruth

Subjects
lcsh:Chemistry, lcsh:QD1-999, lcsh:Physics, lcsh:QC1-999, Atmospheric Sciences
Abstract

A coupled regional-to-local modelling system comprising a regional chemistry–climate model with 5 km horizontal resolution (EMEP4UK) and an urban dispersion and chemistry model with explicit road source emissions (ADMS-Urban) has been used to simulate air quality in 2012 across London. The study makes use of emission factors for NOx and NO2 and non-exhaust emission rates of PM10 and PM2.5 which have been adjusted compared to standard factors to reflect real-world emissions, with increases in total emissions of around 30 % for these species. The performance of the coupled model and each of the two component models is assessed against measurements from background and near-road sites in London using a range of metrics concerning annual averages, high hourly average concentrations and diurnal cycles. The regional model shows good performance compared to measurements for background sites for these metrics, but under-predicts concentrations of all pollutants except O3 at near-road sites due to the low resolution of input emissions and calculations. The coupled model shows good performance at both background and near-road sites, which is broadly comparable with that of the urban model that uses measured concentrations as regional background, except for PM2.5 where the under-prediction of the regional model causes the coupled model to also under-predict concentrations. Using the coupled model, it is estimated that 13 % of the area of London exceeded the EU limit value of 40 µg m−3 for annual average NO2 in 2012, whilst areas of exceedances of the annual average limit values of 40 and 25 µg m−3 for PM10 and PM2.5 respectively were negligible.

Published
2018
Full Text
View/download PDF

38. Improving NOX emissions in Beijing using network observations and a novel perturbed emissions ensemble.

Author

Yuan, Le, Popoola, Olalekan A.M., Hood, Christina, Carruthers, David, Jones, Roderic L., Sun, Haitong Zhe, Liu, Huan, Zhang, Qiang, and Archibald, Alexander T.

Abstract

Emissions inventories are crucial inputs to air quality simulations and represent a major source of uncertainty. Various methods have been adopted to optimise emissions inventories, yet in most cases the methods were only applied to total anthropogenic emissions. We have developed a new approach that updates a priori emission estimates by source sector, which are particularly relevant for policy interventions. At its core is a perturbed emissions ensemble (PEE), constructed by perturbing parameters in an a priori emissions inventory within their respective uncertainty ranges. This PEE is then input to an air quality model to generate an ensemble of forward simulations. By comparing the simulation outputs with observations from a dense network, the initial uncertainty ranges are constrained and a posteriori emission estimates are derived. Using this approach, we were able to derive the transport sector NOx emissions for a study area centred around Beijing in 2016 based on a priori emission estimates for 2013. The absolute emissions were found to be 1.5-9x104 Mg, corresponding to a 57-93% reduction from the 2013 levels, yet the night-time fraction of the emissions was 67-178% higher. These results provide robust and independent evidence of the trends of traffic emission in the study area between 2013 and 2016 reported by previous studies. We also highlighted the impacts of the chemical mechanisms in the underlying model on the emission estimates derived, which is often neglected in emission optimisation studies. This work paves forward the route for rapid analysis and update of emissions inventories using air quality models and routine in situ observations, underscoring the utility of dense observational networks. It also highlights some gaps in the current distribution of monitoring sites in Beijing which result in an underrepresentation of large point sources of NOx. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

39. Modelling the Impact of National vs. Local Emission Reduction on PM 2.5 in the West Midlands, UK Using WRF-CMAQ.

Author

Mazzeo, Andrea, Zhong, Jian, Hood, Christina, Smith, Stephen, Stocker, Jenny, Cai, Xiaoming, and Bloss, William J.

Subjects
GREENHOUSE gas mitigation, ENVIRONMENTAL health, AIR pollution, TRANSPORT theory, ENVIRONMENTAL risk
Abstract

Ambient air pollution from PM2.5 is a major risk to human and environmental health, with significant impacts on mortality and morbidity. Mitigation policies—which may be regional or national in extent—need to consider both primary and secondary particles to be effective, balancing within-region emissions and longer-range transport phenomena. The modelling system WRF-CMAQ was used to simulate the impact of emissions reductions in the West Midlands region of the UK, evaluating the change in total PM2.5 and in its primary and secondary components. Domestic combustion, road transport and agriculture emissions were reduced individually or in combination, at a national or at local level. Combined reduction of road transport and agriculture emissions showed the strongest reduction (29%) in average PM2.5 if applied at national level. At the local level, reductions from domestic combustion were shown to be the most effective policy (13.4% on average). Secondary inorganic fractions of PM2.5 are the most abundant, with 25% NO3− 21% SO42− and 13% NH4+ on average. Scenario analysis shows that the contribution of secondary components to the fractional change of PM2.5 dominates for national policies (up to 0.86 for NO3−) when road transport and agriculture activities are reduced, while at the regional level the elemental and organic carbon fractional changes are dominant (up to 0.64 for organic carbon). [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

40. Additional file 4 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 4. Graphs 1 to 210 (pages 1 to 35).

Published
2020
Full Text
View/download PDF

41. Additional file 7 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 7. Graphs 631 to 840 (pages 106 to 140).

Published
2020
Full Text
View/download PDF

42. Additional file 6 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 6. Graphs 421 to 630 (pages 71 to 105).

Published
2020
Full Text
View/download PDF

43. Additional file 8 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 8. Graphs 841 to 1050 (pages 141 to 175).

Published
2020
Full Text
View/download PDF

44. Additional file 1 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 1. Figures S1 to S10, and additional text on the causal ordering of variables.

Published
2020
Full Text
View/download PDF

45. Additional file 5 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 5. Graphs 211 to 420 (pages 36 to 70).

Published
2020
Full Text
View/download PDF

46. Additional file 3 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 3. Index and notes on supplementary graphs 1 to 205 (page 1 to 205).

Published
2020
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results