Kassi Shave

781 citations
14 papers · 534 · h-index 11

Impact in

Papers in

Kassi Shave

14 papers receiving 522 citations

Peers

Kassi Shave
Comparison fields: 5 of 114
  • Statistics, Probability and Uncertainty 59
  • Health 48
  • Pediatrics, Perinatology and Child Health 93
  • Clinical Psychology 63
  • Applied Psychology 14
Replace Patricia Marsh with:
Patricia Marsh United Kingdom
Jessica L. Markham United States
Vincent Dufort United States
Kerry Bell United Kingdom
Maria Bailey Ireland
Yvonne Joosten United States
Gordon Forbes United Kingdom
Heather Coats United States
Zoë Darwin United Kingdom
Emily Walsh United States
Kassi Shave relative to Patricia Marsh United Kingdom Patricia Marsh's profile →
Citations per field
00.5×9.3×
Patricia Marsh · 1×
Citations per year

Countries citing papers authored by Kassi Shave

Since Specialization
Citations

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

Fields of papers citing papers by Kassi Shave

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kassi Shave. 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 Kassi Shave. The network helps show where Kassi Shave may publish in the future.

Co-authors

The 19 scholars most cited alongside Kassi Shave, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kassi Shave Line = papers co-authored together Kassi Shave links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2017232
2 201677
3 201737
4 201937
5 201837
6 201730
7 201718
8 201516
9 201715
10 201815
11 201514
12 20163
13 20172
14 20161

About Kassi Shave

Kassi Shave is a scholar working on Health, Pediatrics, Perinatology and Child Health, Clinical Psychology, Radiological and Ultrasound Technology and Sociology and Political Science, having authored 14 papers that have together received 534 indexed citations. Recurring topics across this work include Social Media in Health Education (3 papers), Pediatric Pain Management Techniques (3 papers), Family and Disability Support Research (2 papers), Meta-analysis and systematic reviews (1 paper), Infant Development and Preterm Care (1 paper), Urinary Tract Infections Management (1 paper), Family Support in Illness (1 paper) and Child Welfare and Adoption (1 paper). The work is most often cited by research in Statistics, Probability and Uncertainty (59 citations), Health (48 citations), Pediatrics, Perinatology and Child Health (93 citations), Clinical Psychology (63 citations) and Applied Psychology (14 citations). Kassi Shave has collaborated with scholars based in Canada, Portugal and Australia. Frequent co-authors include Lisa Hartling, Robin Featherstone, Ben Vandermeer, Megan Nuspl, Donna M Dryden, Shannon D. Scott, Samina Ali, Bonnie Lashewicz, Allison Gates and Ricardo M. Fernandes. Their work appears in journals such as BMJ Open, Systematic Reviews, Journal of Medical Internet Research, BMC Medical Research Methodology and BMC Pediatrics.

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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