Lilly Derby

13 papers receiving 73 citations

Peers

Lilly Derby
Comparison fields: 5 of 41
  • Applied Psychology 5
  • Pediatrics, Perinatology and Child Health 16
  • Medical Laboratory Technology 1
  • Statistics and Probability 5
  • Family Practice 1
Replace Jennifer McCormack with:
Jennifer McCormack United States
Alyssandra Chee-A-Tow Canada
Phillipp Schwarzfischer Germany
Lara Thomas United States
Maren Galarce United States
Ali Janati Iran
Elisabeth Jentschke Germany
Akemi Shirado Naito Japan
Kerry Milaszewski United States
Gillian Mayersohn United States
Lilly Derby relative to Jennifer McCormack United States Jennifer McCormack's profile →
Citations per field
00.5×3.4×
Jennifer McCormack · 1×
Citations per year

Countries citing papers authored by Lilly Derby

Since Specialization
Citations

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

Fields of papers citing papers by Lilly Derby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 202020
2 202012
3 20219
4 20198
5 20216
6 20226
7 20253
8 20242
9 20212
10 20242
11 20241
12 20241
13 20251
14 20230
15
Science Of Behavior Change Research Network
20170

About Lilly Derby

Lilly Derby is a scholar working on Social Psychology, Applied Psychology, Psychiatry and Mental health, Cardiology and Cardiovascular Medicine and Clinical Psychology, having authored 15 papers that have together received 73 indexed citations. Recurring topics across this work include Psychosomatic Disorders and Their Treatments (2 papers), Psychological Well-being and Life Satisfaction (1 paper), Behavioral Health and Interventions (1 paper), Mental Health and Psychiatry (1 paper), Paranormal Experiences and Beliefs (1 paper), Cardiac Health and Mental Health (1 paper), Child Abuse and Trauma (1 paper) and Posttraumatic Stress Disorder Research (1 paper). The work is most often cited by research in Applied Psychology (5 citations), Pediatrics, Perinatology and Child Health (16 citations), Medical Laboratory Technology (1 citation), Statistics and Probability (5 citations) and Family Practice (1 citation). Lilly Derby has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Johannes Haushofer, Talea Cornelius, Donald Edmondson, Samantha G. Farris, Joan Duer-Hefele, Melissa Dong, Karina W. Davidson, Nathalie Moise, Ian M. Kronish and Naihua Duan. Their work appears in journals such as Health Psychology, Social Science & Medicine, General Hospital Psychiatry, BMC Pregnancy and Childbirth and Psychological Bulletin.

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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