This map shows the geographic impact of Mark DeBeliso'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 Mark DeBeliso with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark DeBeliso more than expected).
This network shows the impact of papers produced by Mark DeBeliso. 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 Mark DeBeliso. The network helps show where Mark DeBeliso may publish in the future.
Co-authorship network of co-authors of Mark DeBeliso
This figure shows the co-authorship network connecting the top 25 collaborators of Mark DeBeliso.
A scholar is included among the top collaborators of Mark DeBeliso 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 Mark DeBeliso. Mark DeBeliso is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Davis, Dustin W., et al.. (2021). Validity of Average Heart Rate and Energy Expenditure in Polar OH1 and Verity Sense While Self-Paced Walking. TopSCHOLAR (Western Kentucky University). 14(1). 69.2 indexed citations
7.
Larson, Abigail, et al.. (2020). Levels of Anxiety: Practice vs. Competition among NCAA Division I Women Gymnasts. 10(5). 117–122.
8.
DeBeliso, Mark, et al.. (2020). The Relationship Between Back Squat Strength and Sprint Times Among Male NCAA Track Athletes. 10(2). 38–42.1 indexed citations
Walsh, Jared P., et al.. (2018). Psychological factors in competitive masters athletes in the context of body mass index. ePublications@SCU (Southern Cross University).2 indexed citations
11.
Walsh, Joe, et al.. (2018). Comparison of obesity prevalence across 28 world masters games sports. ePublications@SCU (Southern Cross University). 11(1). 30–36.5 indexed citations
12.
DeBeliso, Mark, et al.. (2017). Investigation of the Psychological Motivating Factors Behind Competition (Masters Sport) in the Context of Body Mass Index. 10(2). 9–13.1 indexed citations
13.
DeBeliso, Mark, et al.. (2017). The Reliability of the Standing Long Jump in NCAA Track and Field Athletes. 7(6). 233–238.6 indexed citations
14.
Harris, Chad, et al.. (2017). Determination of Trials Needed for Measurement Consistency of Standing Long Jump in Female Collegiate Volleyball Athletes: A Brief Report. 7(1). 1–5.6 indexed citations
15.
DeBeliso, Mark, et al.. (2014). The Validity and Reliability of Push-Ups as a Measure of Upper Body Strength for 11-12 Year-Old Females. USC Research Bank (University of the Sunshine Coast).1 indexed citations
16.
DeBeliso, Mark, et al.. (2013). Metabolic response to repetitive lifting tasks: predetermined vs. self-selected pace. ePublications@SCU (Southern Cross University).2 indexed citations
17.
Walsh, Joe, et al.. (2012). Obesity prevalence for athletes participating in soccer at the World Masters Games. International sportmed journal for FIMS. 13(2). 76–84.7 indexed citations
18.
Walsh, Joe, et al.. (2011). Variations in body mass index with age in masters athletes. World academy of science, engineering and technology.1 indexed citations
19.
DeBeliso, Mark, et al.. (2004). The relation between trunk strength measures and lumbar disc deformation during stoop type lifting. ePublications@SCU (Southern Cross University).1 indexed citations
20.
DeBeliso, Mark, et al.. (2004). THE EFFECTS OF KINESIO TAPING ON PROPRIOCEPTION AT THE ANKLE. SHILAP Revista de lepidopterología.20 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.