Nada M. Goodrum

47 total papers · 559 total citations
34 papers, 360 citations indexed

About

Nada M. Goodrum is a scholar working on General Health Professions, Clinical Psychology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Nada M. Goodrum has authored 34 papers receiving a total of 360 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in General Health Professions, 19 papers in Clinical Psychology and 9 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Nada M. Goodrum's work include Adolescent Sexual and Reproductive Health (11 papers), Child Abuse and Trauma (10 papers) and Maternal Mental Health During Pregnancy and Postpartum (9 papers). Nada M. Goodrum is often cited by papers focused on Adolescent Sexual and Reproductive Health (11 papers), Child Abuse and Trauma (10 papers) and Maternal Mental Health During Pregnancy and Postpartum (9 papers). Nada M. Goodrum collaborates with scholars based in United States and South Africa. Nada M. Goodrum's co-authors include Anthony O. Ahmed, Denis G. Birgenheir, Deborah J. Jones, Jessica Cuellar, Justin Parent, Carlye Kincaid, Lisa Armistead, Angela D. Moreland, Rex Forehand and Nicole Fenton and has published in prestigious journals such as Child Development, Journal of Abnormal Psychology and Clinical Psychology Review.

In The Last Decade

Nada M. Goodrum

30 papers receiving 345 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Nada M. Goodrum	224	103	79	59	51	34	360
Michael S. Dunn	129 0.6×	116 1.1×	57 0.7×	21 0.4×	61 1.2×	23	374
Hong Ngo	170 0.8×	101 1.0×	130 1.6×	31 0.5×	50 1.0×	20	357
Leyla Küçük	246 1.1×	58 0.6×	94 1.2×	36 0.6×	45 0.9×	40	390
Mihoko Maru	131 0.6×	168 1.6×	47 0.6×	29 0.5×	36 0.7×	18	331
Anne Mbwayo	190 0.8×	78 0.8×	124 1.6×	13 0.2×	22 0.4×	38	341
Laurence Fond‐Harmant	189 0.8×	109 1.1×	29 0.4×	95 1.6×	32 0.6×	33	361
Mélanie Vachon	169 0.8×	81 0.8×	37 0.5×	19 0.3×	64 1.3×	35	365
Steven C. Schlozman	127 0.6×	66 0.6×	36 0.5×	39 0.7×	52 1.0×	31	302
Élodie Charbonnier	211 0.9×	68 0.7×	46 0.6×	17 0.3×	38 0.7×	36	331
Karen Machin	169 0.8×	178 1.7×	51 0.6×	26 0.4×	33 0.6×	25	314

Countries citing papers authored by Nada M. Goodrum

Since Specialization

Citations

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

Fields of papers citing papers by Nada M. Goodrum

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nada M. Goodrum. 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 Nada M. Goodrum. The network helps show where Nada M. Goodrum may publish in the future.

Co-authorship network of co-authors of Nada M. Goodrum

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

All Works

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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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