Daniel K. Kajdasz
- Pharmacology top 0.5%
- Psychiatry and Mental health top 1%
- Physiology top 5%
- Cognitive Neuroscience top 5%
- Experimental and Cognitive Psychology top 5%
- Co-authors
- Amy S. ChappellDaniel WalkerMadelaine M. WohlreichPhilip J. MeaseMichael J. DetkeLesley M. ArnoldJoel RaskinJoachim Wernicke
- Topics
- Treatment of Major Depression (18 papers)Pain Management and Placebo Effect (11 papers)Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (9 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Daniel K. Kajdasz
40 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 104
- Pharmacology 1.1k
- Psychiatry and Mental health 821
- Physiology 426
- Cognitive Neuroscience 321
- Experimental and Cognitive Psychology 221
Countries citing papers authored by Daniel K. Kajdasz
This map shows the geographic impact of Daniel K. Kajdasz'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 Daniel K. Kajdasz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel K. Kajdasz more than expected).
Fields of papers citing papers by Daniel K. Kajdasz
This network shows the impact of papers produced by Daniel K. Kajdasz. 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 Daniel K. Kajdasz. The network helps show where Daniel K. Kajdasz may publish in the future.
Co-authorship network of co-authors of Daniel K. Kajdasz
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel K. Kajdasz. A scholar is included among the top collaborators of Daniel K. Kajdasz 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 Daniel K. Kajdasz. Daniel K. Kajdasz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 20 | |
| 2 | 106 | |
| 3 | 21 | |
| 4 | 53 | |
| 5 | 24 | |
| 6 | 9 | |
| 7 | 21 | |
| 8 | 16 | |
| 9 | 286 | |
| 10 | 22 | |
| 11 | 60 | |
| 12 | 100 | |
| 13 | 15 | |
| 14 | 23 | |
| 15 | 9 | |
| 16 | 99 | |
| 17 | 24 | |
| 18 | 63 | |
| 19 | 39 | |
| 20 | 1 |
About Daniel K. Kajdasz
Daniel K. Kajdasz is a scholar working on Pharmacology, Psychiatry and Mental health and Experimental and Cognitive Psychology, having authored 41 papers that have together received 1.9k indexed citations. Recurring topics across this work include Treatment of Major Depression (18 papers), Pain Management and Placebo Effect (11 papers) and Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (9 papers). The work is most often cited by research in Pharmacology (1.1k citations), Psychiatry and Mental health (821 citations) and Biological Psychiatry (114 citations). Daniel K. Kajdasz has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Amy S. Chappell, Daniel Walker, Madelaine M. Wohlreich, Philip J. Mease, Michael J. Detke, Lesley M. Arnold, Joel Raskin, Joachim Wernicke, Timothy R. Smith and D. Desaiah. Their work appears in journals such as American Journal of Epidemiology, Pain and Anesthesiology.
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.