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.
Interventions to Improve Adherence to Self-administered Medications for Chronic Diseases in the United States
2012556 citationsMeera Viswanathan, Carol E. Golin et al.Annals of Internal Medicineprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Mahima Ashok'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 Mahima Ashok with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mahima Ashok more than expected).
This network shows the impact of papers produced by Mahima Ashok. 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 Mahima Ashok. The network helps show where Mahima Ashok may publish in the future.
Co-authorship network of co-authors of Mahima Ashok
This figure shows the co-authorship network connecting the top 25 collaborators of Mahima Ashok.
A scholar is included among the top collaborators of Mahima Ashok 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 Mahima Ashok. Mahima Ashok is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Viswanathan, Meera, Carol E. Golin, Christine D. Jones, et al.. (2020). Interventions to Improve Adherence to Self-administered Medications for Chronic Diseases in the United States. Annals of Internal Medicine.6 indexed citations
Feltner, Cynthia, Catherine A. Grodensky, Jennifer Cook Middleton, et al.. (2016). Serological Screening for Genital Herpes: An Evidence Review for the U.S. Preventive Services Task Force. Europe PMC (PubMed Central).1 indexed citations
9.
Feltner, Cynthia, Catherine A. Grodensky, Jennifer Cook Middleton, et al.. (2016). Serologic Screening for Genital Herpes. JAMA. 316(23). 2531–2531.29 indexed citations
10.
Gaynes, Bradley N., Carrie Brown, Linda J Lux, et al.. (2015). Relationship Between Use of Quality Measures and Improved Outcomes in Serious Mental Illness.4 indexed citations
Meleth, Sreelatha, Katherine E. Reeder‐Hayes, Mahima Ashok, et al.. (2014). Technology Assessment of Molecular Pathology Testing for the Estimation of Prognosis for Common Cancers.2 indexed citations
13.
Smith, Lucia Rojas, et al.. (2014). Contextual Frameworks for Research on the Implementation of Complex System Interventions. Europe PMC (PubMed Central).40 indexed citations
14.
Smith, Lucia Rojas, et al.. (2014). Process Redesign Framework.1 indexed citations
Viswanathan, Meera, Carol E. Golin, Christine D. Jones, et al.. (2012). Closing the quality gap: revisiting the state of the science (vol. 4: medication adherence interventions: comparative effectiveness).. PubMed. 1–685.48 indexed citations
Viswanathan, Meera, Carol E. Golin, Christine D. Jones, et al.. (2012). Interventions to Improve Adherence to Self-administered Medications for Chronic Diseases in the United States. Annals of Internal Medicine. 157(11). 785–795.556 indexed citations breakdown →
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.