Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Older Adults’ Internet Use for Health Information: Digital Divide by Race/Ethnicity and Socioeconomic Status
2018269 citationsHyunwoo Yoon, Yuri Jang et al.Journal of Applied Gerontologyprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Phillip W. Vaughan
Since
Specialization
Citations
This map shows the geographic impact of Phillip W. Vaughan'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 Phillip W. Vaughan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phillip W. Vaughan more than expected).
Fields of papers citing papers by Phillip W. Vaughan
This network shows the impact of papers produced by Phillip W. Vaughan. 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 Phillip W. Vaughan. The network helps show where Phillip W. Vaughan may publish in the future.
Co-authorship network of co-authors of Phillip W. Vaughan
This figure shows the co-authorship network connecting the top 25 collaborators of Phillip W. Vaughan.
A scholar is included among the top collaborators of Phillip W. Vaughan 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 Phillip W. Vaughan. Phillip W. Vaughan is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Vaughan, Phillip W., et al.. (2020). Gender Differences in Student Attitudes towards Science in Secondary School Classrooms with and without NSF GK-12 Resident Scientists. 24(4). 50–68.6 indexed citations
Yoon, Hyunwoo, Yuri Jang, Phillip W. Vaughan, & Michael A. Garcia. (2018). Older Adults’ Internet Use for Health Information: Digital Divide by Race/Ethnicity and Socioeconomic Status. Journal of Applied Gerontology. 39(1). 105–110.269 indexed citations breakdown →
9.
Brown‐Devlin, Natalie, Michael B. Devlin, & Phillip W. Vaughan. (2017). Why Fans Act That Way. Communication & Sport. 6(4). 395–417.16 indexed citations
Vaughan, Phillip W., et al.. (2009). Measuring the Relationship between Attributions for "The Gap" and Educational Policy Attitudes: Introducing the Attributions for Scholastic Outcomes Scale-Black. The Journal of Negro Education. 78(2). 146.3 indexed citations
McDougall, Graham J., Heather Becker, Carol L. Delville, Phillip W. Vaughan, & Taylor W. Acee. (2007). Alcohol use and older adults: A little goes a long way. International Journal on Disability and Human Development. 6(4). 431–431.7 indexed citations
18.
McDougall, Graham J., Phillip W. Vaughan, Taylor W. Acee, & Heather Becker. (2007). Managing cardiovascular risk factors in high-risk African Americans.. PubMed. 17(2). 414–414.1 indexed citations
19.
McDougall, Graham J., Phillip W. Vaughan, Taylor W. Acee, & Heather Becker. (2007). Memory performance and mild cognitive impairment in Black and White community elders.. PubMed. 17(2). 381–8.18 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.