Nadia Inglis

624 total citations · 1 hit paper
9 papers, 425 citations indexed

About

Nadia Inglis is a scholar working on General Health Professions, Health and Epidemiology. According to data from OpenAlex, Nadia Inglis has authored 9 papers receiving a total of 425 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in General Health Professions, 4 papers in Health and 4 papers in Epidemiology. Recurrent topics in Nadia Inglis's work include Influenza Virus Research Studies (4 papers), COVID-19 epidemiological studies (2 papers) and Obesity, Physical Activity, Diet (2 papers). Nadia Inglis is often cited by papers focused on Influenza Virus Research Studies (4 papers), COVID-19 epidemiological studies (2 papers) and Obesity, Physical Activity, Diet (2 papers). Nadia Inglis collaborates with scholars based in United Kingdom, Australia and Taiwan. Nadia Inglis's co-authors include Shirley Large, John Powell, Katie Newby, Jo Parsons, Margaret Thorogood, Sarah Stewart‐Brown, Wendy Robertson, Thomas House, Gillian Smith and Babatunde Olowokure and has published in prestigious journals such as Journal of Medical Internet Research, BMC Medicine and Epidemiology and Infection.

In The Last Decade

Nadia Inglis

9 papers receiving 410 citations

Hit Papers

The Characteristics and Motivations of Online Health Info... 2011 2026 2016 2021 2011 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nadia Inglis United Kingdom 6 266 142 84 58 53 9 425
Helen Monkman Canada 11 238 0.9× 187 1.3× 119 1.4× 57 1.0× 34 0.6× 63 513
Norliza Ahmad Malaysia 12 123 0.5× 127 0.9× 64 0.8× 124 2.1× 69 1.3× 55 443
Nor Afiah Mohd Zulkefli Malaysia 12 112 0.4× 139 1.0× 54 0.6× 85 1.5× 130 2.5× 59 566
Carys Batcup Australia 11 183 0.7× 137 1.0× 132 1.6× 145 2.5× 30 0.6× 27 514
Shan Lu China 10 165 0.6× 63 0.4× 55 0.7× 39 0.7× 55 1.0× 26 438
Andriy Melnyk Italy 7 123 0.5× 144 1.0× 115 1.4× 69 1.2× 29 0.5× 17 417
Valeria Puleo Italy 6 127 0.5× 144 1.0× 116 1.4× 67 1.2× 29 0.5× 7 399
Umaira Ansari Mexico 9 143 0.5× 137 1.0× 69 0.8× 33 0.6× 31 0.6× 19 364
Hilde van Keulen Netherlands 12 194 0.7× 143 1.0× 61 0.7× 99 1.7× 129 2.4× 42 543
Jill Darling United States 15 256 1.0× 115 0.8× 100 1.2× 54 0.9× 32 0.6× 28 582

Countries citing papers authored by Nadia Inglis

Since Specialization
Citations

This map shows the geographic impact of Nadia Inglis's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nadia Inglis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nadia Inglis more than expected).

Fields of papers citing papers by Nadia Inglis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nadia Inglis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nadia Inglis. The network helps show where Nadia Inglis may publish in the future.

Co-authorship network of co-authors of Nadia Inglis

This figure shows the co-authorship network connecting the top 25 collaborators of Nadia Inglis. A scholar is included among the top collaborators of Nadia Inglis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nadia Inglis. Nadia Inglis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Parsons, Jo, Katie Newby, David French, Elizabeth Bailey, & Nadia Inglis. (2021). The development of a digital intervention to increase influenza vaccination amongst pregnant women. Digital Health. 7. 569655840–569655840. 7 indexed citations
2.
Newby, Katie, et al.. (2016). Identifying strategies to increase influenza vaccination in GP practices: a positive deviance approach. Family Practice. 33(3). 318–323. 17 indexed citations
3.
Inglis, Nadia, Kamila Janmohamed, Sultan Suleman, et al.. (2013). Measuring the effect of influenza A(H1N1)pdm09: the epidemiological experience in the West Midlands, England during the ‘containment’ phase. Epidemiology and Infection. 142(2). 428–437. 6 indexed citations
4.
Fowler, Tom, et al.. (2013). Estimating the positive predictive value of opportunistic population testing for gonorrhoea as part of the English Chlamydia Screening Programme. International Journal of STD & AIDS. 24(3). 185–191. 3 indexed citations
5.
House, Thomas, Nadia Inglis, Joshua V. Ross, et al.. (2012). Estimation of outbreak severity and transmissibility: Influenza A(H1N1)pdm09 in households. BMC Medicine. 10(1). 117–117. 29 indexed citations
6.
Powell, John, et al.. (2011). The Characteristics and Motivations of Online Health Information Seekers: Cross-Sectional Survey and Qualitative Interview Study. Journal of Medical Internet Research. 13(1). e20–e20. 337 indexed citations breakdown →
7.
Robertson, Wendy, et al.. (2011). Two‐year follow‐up of the ‘Families for Health’ programme for the treatment of childhood obesity. Child Care Health and Development. 38(2). 229–236. 24 indexed citations
8.
Inglis, Nadia, et al.. (2011). The Public Health Specialist and Access to Public Health Advice. InnovAiT Education and inspiration for general practice. 4(12). 719–728. 1 indexed citations
9.
Inglis, Nadia, Andrea Docherty, & Rachel Pryke. (2009). Evaluation of the ‘Mealtime Magic’ brief leaflet-based intervention in general practice. Primary Health Care Research & Development. 11(2). 166–166. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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