John J. Sheehan

3.6k total citations · 1 hit paper
110 papers, 2.6k citations indexed

About

John J. Sheehan is a scholar working on Pharmacology, Psychiatry and Mental health and Social Psychology. According to data from OpenAlex, John J. Sheehan has authored 110 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Pharmacology, 28 papers in Psychiatry and Mental health and 19 papers in Social Psychology. Recurrent topics in John J. Sheehan's work include Treatment of Major Depression (34 papers), Mental Health Treatment and Access (19 papers) and Schizophrenia research and treatment (15 papers). John J. Sheehan is often cited by papers focused on Treatment of Major Depression (34 papers), Mental Health Treatment and Access (19 papers) and Schizophrenia research and treatment (15 papers). John J. Sheehan collaborates with scholars based in United States, Ireland and Canada. John J. Sheehan's co-authors include James Carr, Kruti Joshi, Patrick Lefèbvre, Dominic Pilon, Maryia Zhdanava, Wing Chow, Isabelle Ghelerter, Stella E. Tsirka, Ioannis Koktzoglou and Eugene Dunkle and has published in prestigious journals such as Journal of Neuroscience, Gastroenterology and PLoS ONE.

In The Last Decade

John J. Sheehan

102 papers receiving 2.5k citations

Hit Papers

align trajectories

What are hit papers?

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.

The Prevalence and National Burden of Treatment-Resistant Depression and Major Depressive Disorder in the United States

2021 296 citations Maryia Zhdanava, Dominic Pilon et al. The Journal of Clinical Psychiatry profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John J. Sheehan United States	28	567	477	436	346	310	110	2.6k
Jennifer R. Geske United States	33	315 0.6×	793 1.7×	544 1.2×	153 0.4×	268 0.9×	163	3.8k
Zhu Li China	33	320 0.6×	577 1.2×	220 0.5×	209 0.6×	106 0.3×	149	3.7k
Udo Reulbach Germany	38	477 0.8×	440 0.9×	183 0.4×	149 0.4×	201 0.6×	134	4.7k
Cynthia Siu United States	32	517 0.9×	1.3k 2.8×	362 0.8×	221 0.6×	131 0.4×	85	3.5k
Manabu Tashiro Japan	36	696 1.2×	601 1.3×	189 0.4×	76 0.2×	395 1.3×	179	3.9k
Gianluigi Vendemiale Italy	31	125 0.2×	519 1.1×	242 0.6×	264 0.8×	306 1.0×	93	3.1k
Kurt Kletter Austria	40	1.4k 2.5×	319 0.7×	178 0.4×	503 1.5×	718 2.3×	171	4.7k
Jeffrey B. Weilburg United States	25	650 1.1×	568 1.2×	356 0.8×	84 0.2×	109 0.4×	55	2.6k
Nathaniel L. Baker United States	32	171 0.3×	253 0.5×	488 1.1×	210 0.6×	73 0.2×	145	2.9k
Susan Ball United States	40	200 0.4×	798 1.7×	708 1.6×	287 0.8×	296 1.0×	142	5.9k

Countries citing papers authored by John J. Sheehan

Since Specialization

Citations

This map shows the geographic impact of John J. Sheehan'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 John J. Sheehan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John J. Sheehan more than expected).

Fields of papers citing papers by John J. Sheehan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John J. Sheehan. 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 John J. Sheehan. The network helps show where John J. Sheehan may publish in the future.

Co-authorship network of co-authors of John J. Sheehan

This figure shows the co-authorship network connecting the top 25 collaborators of John J. Sheehan. A scholar is included among the top collaborators of John J. Sheehan 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 John J. Sheehan. John J. Sheehan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Peterson, Christopher G., et al.. (2025). Acquired Bernard–Soulier-like syndrome due to a plasma-based inhibitor treated successfully with rituximab. Research and Practice in Thrombosis and Haemostasis. 9(2). 102727–102727.

Zhdanava, Maryia, Dominic Pilon, Kruti Joshi, et al.. (2022). Excess healthcare resource utilization and healthcare costs among privately and publicly insured patients with major depressive disorder and acute suicidal ideation or behavior in the United States. Journal of Affective Disorders. 311. 303–310. 5 indexed citations

Li, Gang, Ling Zhang, Allitia DiBernardo, et al.. (2020). A retrospective analysis to estimate the healthcare resource utilization and cost associated with treatment-resistant depression in commercially insured US patients. PLoS ONE. 15(9). e0238843–e0238843. 15 indexed citations

Shrestha, Anshu, et al.. (2020). Incremental Health Care Burden of Treatment-Resistant Depression Among Commercial, Medicaid, and Medicare Payers. Psychiatric Services. 71(6). 593–601. 6 indexed citations

Pilon, Dominic, et al.. (2020). Use of home health and other healthcare delivery pathways among privately insured patients with and without treatment-resistant depression. Current Medical Research and Opinion. 36(5). 865–874. 1 indexed citations

Pilon, Dominic, John J. Sheehan, Laura Morrison, et al.. (2019). Is clinician impression of depression symptom severity associated with incremental economic burden in privately insured US patients with treatment resistant depression?. Journal of Affective Disorders. 255. 50–59. 14 indexed citations

Hernández, Luis, et al.. (2019). PMH19 COST-EFFECTIVENESS ANALYSIS OF ESKETAMINE IN TREATMENT-RESISTANT DEPRESSION IN THE UNITED STATES. Value in Health. 22. S228–S229. 5 indexed citations

Sheehan, John J., et al.. (2019). PMH23 BUDGET IMPACT ANALYSIS OF ESKETAMINE IN TREATMENT-RESISTANT DEPRESSION IN THE UNITED STATES. Value in Health. 22. S229–S230. 1 indexed citations

MacEwan, Joanna P., John J. Sheehan, J. Vanderpuye-Orgle, et al.. (2017). The relationship between adherence and total spending among Medicare beneficiaries with type 2 diabetes.. PubMed. 23(4). 248–252. 2 indexed citations

10.

Mukherjee, Jayanti, John J. Sheehan, Alexandra Ward, et al.. (2017). Delays in treatment intensification with oral antidiabetic drugs and risk of microvascular and macrovascular events in patients with poor glycaemic control: A n individual patient simulation study. Diabetes Obesity and Metabolism. 19(7). 1006–1013. 12 indexed citations

11.

Lauffenburger, Julie C., Jennifer Lewey, Saira Jan, et al.. (2017). Rationale and design of the ENhancing outcomes through Goal Assessment and Generating Engagement in Diabetes Mellitus (ENGAGE-DM) pragmatic trial. Contemporary Clinical Trials. 59. 57–63. 6 indexed citations

12.

Bell, Kelly, Arie Katz, & John J. Sheehan. (2016). Quality measure attainment with dapagliflozin plus metformin extended-release as initial combination therapy in patients with type 2 diabetes: a post hoc pooled analysis of two clinical studies. Risk Management and Healthcare Policy. Volume 9. 231–241. 6 indexed citations

13.

Dunlop, Boadie W., et al.. (2014). How well do clinicians and patients agree on depression treatment outcomes? Implications for personalized medicine. Human Psychopharmacology Clinical and Experimental. 29(6). 528–536. 8 indexed citations

14.

Stewart, T. D., et al.. (2014). Effect of symptom severity on efficacy and safety of aripiprazole adjunctive to antidepressant monotherapy in major depressive disorder: A pooled analysis. Journal of Affective Disorders. 162. 20–25. 14 indexed citations

15.

Casey, Dympna, Kimberly K. Laubmeier, James M. Eudicone, et al.. (2014). Response and remission rates with adjunctive aripiprazole in patients with major depressive disorder who exhibit minimal or no improvement on antidepressant monotherapy. International Journal of Clinical Practice. 68(11). 1301–1308. 4 indexed citations

16.

Findling, Robert L., Raymond Mankoski, Robert D. McQuade, et al.. (2014). A Randomized Controlled Trial Investigating the Safety and Efficacy of Aripiprazole in the Long-Term Maintenance Treatment of Pediatric Patients With Irritability Associated With Autistic Disorder. The Journal of Clinical Psychiatry. 75(1). 22–30. 67 indexed citations

17.

Sheehan, John J., et al.. (2012). Management of antipsychotic treatment discontinuation and interruptions using model-based simulations. Clinical Pharmacology Advances and Applications. 4. 25–25. 21 indexed citations

18.

Kino, Aya, Aoife N. Keeling, Cormac Farrelly, et al.. (2010). Assessment of left ventricular myocardial scar in infiltrative and non-ischemic cardiac diseases by free breathing three dimensional phase sensitive inversion recovery (PSIR) TurboFLASH. International journal of cardiac imaging. 27(4). 527–537. 11 indexed citations

19.

Koktzoglou, Ioannis, John J. Sheehan, Eugene Dunkle, Felix Breuer, & Robert R. Edelman. (2010). Highly accelerated contrast‐enhanced MR angiography: Improved reconstruction accuracy and reduced noise amplification with complex subtraction. Magnetic Resonance in Medicine. 64(6). 1843–1848. 16 indexed citations

20.

Nijm, G.M., Alan V. Sahakian, Steven Swiryn, et al.. (2008). Comparison of self‐gated cine MRI retrospective cardiac synchronization algorithms. Journal of Magnetic Resonance Imaging. 28(3). 767–772. 29 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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