Pei‐Ling Wu

32 papers receiving 355 citations

Peers

Pei‐Ling Wu
Comparison fields: 5 of 101
  • Research and Theory 27
  • Leadership and Management 8
  • Reproductive Medicine 38
  • Issues, ethics and legal aspects 4
  • Obstetrics and Gynecology 18
Replace Mercedes Martínez-Marcos with:
Mercedes Martínez-Marcos Spain
Rizwana Roomaney South Africa
Cara A. Liebert United States
Dorothy A. Whyte United Kingdom
Kathleen J.H. Sparbel United States
Leslie Ann Sadownik Canada
Annalise Weckesser United Kingdom
Susanne Marie Lindqvist United Kingdom
Sachiko Makabe Japan
Laura Vail United Kingdom
Pei‐Ling Wu relative to Mercedes Martínez-Marcos Spain Mercedes Martínez-Marcos's profile →
Citations per field
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Mercedes Martínez-Marcos · 1×
Citations per year

Countries citing papers authored by Pei‐Ling Wu

Since Specialization
Citations

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

Fields of papers citing papers by Pei‐Ling Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pei‐Ling Wu. 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 Pei‐Ling Wu. The network helps show where Pei‐Ling Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside Pei‐Ling Wu, 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 Pei‐Ling Wu Line = papers co-authored together Pei‐Ling Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201887
2 200439
3 201830
4 202130
5 201823
6
Motors of COVID-19 Vaccination Acceptance Scale (MoVac-COVID19S): Evidence of Measurement Invariance Across Five Countries
202222
7 202417
8 202115
9 202113
10 201412
11 201311
12 20229
13 20246
14 20175
15 20215
16 20235
17 20214
18 20214
19 20233
20 20243

About Pei‐Ling Wu

Pei‐Ling Wu is a scholar working on Research and Theory, Leadership and Management, Pulmonary and Respiratory Medicine, Clinical Biochemistry and Pediatrics, Perinatology and Child Health, having authored 36 papers that have together received 361 indexed citations. Recurring topics across this work include Neonatal Respiratory Health Research (5 papers), Nursing education and management (5 papers), Parkinson's Disease Mechanisms and Treatments (2 papers), Healthcare Education and Workforce Issues (2 papers), Simulation-Based Education in Healthcare (2 papers), Glycogen Storage Diseases and Myoclonus (1 paper), Healthcare professionals’ stress and burnout (1 paper) and Gender Diversity and Inequality (1 paper). The work is most often cited by research in Research and Theory (27 citations), Leadership and Management (8 citations), Reproductive Medicine (38 citations), Issues, ethics and legal aspects (4 citations) and Obstetrics and Gynecology (18 citations). Pei‐Ling Wu has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Hsiang‐Chu Pai, Chao‐Chin Hsu, Bei‐Chang Yang, Meng‐Hsing Wu, Wen‐Jiuan Yen, Bih‐O Lee, Yung‐Ning Yang, San‐Nan Yang, Po-Fu Lee and Chien‐Chang Ho. Their work appears in journals such as Journal of Clinical Nursing, Nurse Education Today, International Journal of Nursing Studies, Applied Sciences and Teaching and learning in nursing.

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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