Daniel E. Schoth

1.2k total citations
37 papers, 837 citations indexed

About

Daniel E. Schoth is a scholar working on Pharmacology, Cognitive Neuroscience and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Daniel E. Schoth has authored 37 papers receiving a total of 837 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Pharmacology, 19 papers in Cognitive Neuroscience and 17 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Daniel E. Schoth's work include Musculoskeletal pain and rehabilitation (22 papers), Pain Management and Placebo Effect (18 papers) and Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (17 papers). Daniel E. Schoth is often cited by papers focused on Musculoskeletal pain and rehabilitation (22 papers), Pain Management and Placebo Effect (18 papers) and Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (17 papers). Daniel E. Schoth collaborates with scholars based in United Kingdom, Germany and Australia. Daniel E. Schoth's co-authors include Christina Liossi, Vanessa Delgado Nunes, H. J. Godwin, Simon P. Liversedge, Glyn D. Williams, Brendan P. Bradley, Karin Mogg, Paul White, Richard F. Howard and Line Caes and has published in prestigious journals such as Pain, Clinical Psychology Review and Health Psychology.

In The Last Decade

Daniel E. Schoth

35 papers receiving 818 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel E. Schoth United Kingdom 16 453 339 327 227 213 37 837
Catarina Tomé‐Pires Spain 18 336 0.7× 262 0.8× 151 0.5× 220 1.0× 243 1.1× 46 931
Jeannie A. Sperry United States 14 304 0.7× 142 0.4× 190 0.6× 77 0.3× 182 0.9× 30 752
Dagfinn Berntzen Norway 5 499 1.1× 383 1.1× 126 0.4× 165 0.7× 217 1.0× 10 898
Rachel V. Aaron United States 17 178 0.4× 140 0.4× 145 0.4× 175 0.8× 374 1.8× 50 917
Lynette A. Menefee United States 11 265 0.6× 191 0.6× 180 0.6× 65 0.3× 148 0.7× 13 789
Caitlin B. Murray United States 19 279 0.6× 122 0.4× 100 0.3× 523 2.3× 141 0.7× 44 1.1k
Julia R. Craner United States 15 303 0.7× 120 0.4× 54 0.2× 91 0.4× 171 0.8× 36 550
Anne Marie Fras United States 11 322 0.7× 119 0.4× 168 0.5× 50 0.2× 159 0.7× 16 822
Tony Iezzi Canada 11 304 0.7× 155 0.5× 43 0.1× 101 0.4× 139 0.7× 22 570
Marie Kanstrup Sweden 15 155 0.3× 115 0.3× 137 0.4× 326 1.4× 113 0.5× 27 749

Countries citing papers authored by Daniel E. Schoth

Since Specialization
Citations

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

Fields of papers citing papers by Daniel E. Schoth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel E. Schoth. 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 E. Schoth. The network helps show where Daniel E. Schoth may publish in the future.

Co-authorship network of co-authors of Daniel E. Schoth

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

All Works

20 of 20 papers shown
1.
Schoth, Daniel E., Markus Blankenburg, Julia Wager, et al.. (2022). Quantitative sensory testing in paediatric patients with chronic pain: a systematic review and meta-analysis. British Journal of Anaesthesia. 129(4). e94–e97. 3 indexed citations
2.
Liossi, Christina, Daniel E. Schoth, Lorna Fraser, et al.. (2021). A Systematic Review of Measures of Breakthrough Pain and Their Psychometric Properties. Journal of Pain and Symptom Management. 62(5). 1041–1064. 9 indexed citations
3.
Holley, Simone, Daniel E. Schoth, Lorna Fraser, et al.. (2020). A protocol for a systematic review and meta-analysis to identify measures of breakthrough pain and evaluate their psychometric properties. BMJ Open. 10(3). e035541–e035541. 12 indexed citations
4.
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Schoth, Daniel E., Markus Blankenburg, Julia Wager, et al.. (2019). Association between quantitative sensory testing and pain or disability in paediatric chronic pain: protocol for a systematic review and meta-analysis. BMJ Open. 9(10). e031861–e031861. 6 indexed citations
7.
8.
Liossi, Christina, et al.. (2019). Effectiveness of interdisciplinary interventions in paediatric chronic pain management: a systematic review and subset meta-analysis. British Journal of Anaesthesia. 123(2). e359–e371. 48 indexed citations
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Schoth, Daniel E. & Christina Liossi. (2017). A Systematic Review of Experimental Paradigms for Exploring Biased Interpretation of Ambiguous Information with Emotional and Neutral Associations. Frontiers in Psychology. 8. 171–171. 65 indexed citations
11.
Schoth, Daniel E. & Christina Liossi. (2016). Biased interpretation of ambiguous information in patients with chronic pain: A systematic review and meta-analysis of current studies.. Health Psychology. 35(9). 944–956. 53 indexed citations
12.
Liossi, Christina, et al.. (2015). Treatment of Female Sexual Pain Disorders: A Systematic Review. Journal of Sex & Marital Therapy. 42(2). 99–142. 14 indexed citations
13.
Schoth, Daniel E., et al.. (2014). Exploring Attentional Bias for Real-World, Pain-related Information in Chronic Musculoskeletal Pain Using a Novel Change Detection Paradigm. Clinical Journal of Pain. 31(8). 680–688. 9 indexed citations
14.
Schoth, Daniel E. & Christina Liossi. (2013). Specificity and Time-Course of Attentional Bias in Chronic Headache. Clinical Journal of Pain. 29(7). 583–590. 18 indexed citations
15.
Liossi, Christina, Daniel E. Schoth, H. J. Godwin, & Simon P. Liversedge. (2013). Using eye movements to investigate selective attention in chronic daily headache. Pain. 155(3). 503–510. 47 indexed citations
16.
Schoth, Daniel E., et al.. (2013). Attentional Bias Modification in People with Chronic Pain: A Proof of Concept Study. Cognitive Behaviour Therapy. 42(3). 233–243. 38 indexed citations
17.
Schoth, Daniel E., Vanessa Delgado Nunes, & Christina Liossi. (2011). Attentional bias towards pain-related information in chronic pain; a meta-analysis of visual-probe investigations. Clinical Psychology Review. 32(1). 13–25. 174 indexed citations
18.
Liossi, Christina, Paul White, & Daniel E. Schoth. (2010). Time-course of attentional bias for threat-related cues in patients with chronic daily headache-tension type: Evidence for the role of anger. European Journal of Pain. 15(1). 92–98. 34 indexed citations
19.
Schoth, Daniel E. & Christina Liossi. (2010). Attentional Bias Toward Pictorial Representations of Pain in Individuals With Chronic Headache. Clinical Journal of Pain. 26(3). 244–250. 45 indexed citations
20.
Liossi, Christina, Daniel E. Schoth, Brendan P. Bradley, & Karin Mogg. (2008). Time‐course of attentional bias for pain‐related cues in chronic daily headache sufferers. European Journal of Pain. 13(9). 963–969. 52 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.

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