Peter Kuppens

22.7k total citations · 8 hit papers
242 papers, 14.0k citations indexed

About

Peter Kuppens is a scholar working on Experimental and Cognitive Psychology, Clinical Psychology and Social Psychology. According to data from OpenAlex, Peter Kuppens has authored 242 papers receiving a total of 14.0k indexed citations (citations by other indexed papers that have themselves been cited), including 161 papers in Experimental and Cognitive Psychology, 86 papers in Clinical Psychology and 83 papers in Social Psychology. Recurrent topics in Peter Kuppens's work include Mental Health Research Topics (137 papers), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (47 papers) and Behavioral Health and Interventions (44 papers). Peter Kuppens is often cited by papers focused on Mental Health Research Topics (137 papers), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (47 papers) and Behavioral Health and Interventions (44 papers). Peter Kuppens collaborates with scholars based in Belgium, United States and Netherlands. Peter Kuppens's co-authors include Francis Tuerlinckx, Peter Koval, Marlies Houben, Madeline Pe, Nicholas B. Allen, Lisa Sheeber, Philippe Verduyn, Eva Ceulemans, Iven Van Mechelen and John B. Nezlek and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Personality and Social Psychology and Psychological Bulletin.

In The Last Decade

Peter Kuppens

230 papers receiving 13.5k citations

Hit Papers

The relation between short-term emotion dynamics and psyc... 2011 2026 2016 2021 2015 2013 2013 2013 2011 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The relation between short-term emotion dynamics and psychological well-being: A meta-analysis.
    2015 667 citations Peter Kuppens et al. profile →
  2. Critical slowing down as early warning for the onset and termination of depression
    2013 492 citations Marieke Wichers, Angélique O. J. Cramer et al. profile →
  3. A Network Approach to Psychopathology: New Insights into Clinical Longitudinal Data
    2013 435 citations Laura F. Bringmann, Marieke Wichers et al. PLoS ONE profile →
  4. The regulation of negative and positive affect in daily life.
    2013 401 citations Peter Koval, Peter Kuppens et al. Emotion profile →
  5. Categories versus dimensions in personality and psychopathology: a quantitative review of taxometric research
    2011 363 citations Peter Kuppens et al. Psychological Medicine profile →
  6. Complex affect dynamics add limited information to the prediction of psychological well-being
    2019 279 citations Egon Dejonckheere, Merijn Mestdagh et al. profile →
  7. Psychopathological networks: Theory, methods and practice
    2021 152 citations Laura F. Bringmann, Casper J. Albers et al. Behaviour Research and Therapy profile →
  8. m-Path: an easy-to-use and highly tailorable platform for ecological momentary assessment and intervention in behavioral research and clinical practice
    2023 73 citations Merijn Mestdagh, Stijn Verdonck et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Kuppens Belgium 63 8.0k 5.0k 4.2k 2.8k 2.5k 242 14.0k
Jürgen Margraf Germany 65 5.1k 0.6× 7.2k 1.4× 3.0k 0.7× 2.5k 0.9× 2.0k 0.8× 461 14.6k
J. David Creswell United States 46 3.9k 0.5× 7.9k 1.6× 3.2k 0.8× 1.6k 0.6× 1.5k 0.6× 83 12.1k
Peter F. Lovibond Australia 40 4.8k 0.6× 7.8k 1.6× 3.8k 0.9× 4.5k 1.6× 1.4k 0.6× 118 16.8k
Joshua M. Smyth United States 62 3.5k 0.4× 6.3k 1.3× 4.5k 1.1× 1.4k 0.5× 3.1k 1.2× 315 15.7k
Richard E. Zinbarg United States 54 5.6k 0.7× 6.4k 1.3× 2.7k 0.6× 2.3k 0.8× 1.0k 0.4× 196 12.5k
Carl W. Lejuez United States 81 7.1k 0.9× 11.7k 2.3× 3.5k 0.8× 3.3k 1.2× 5.0k 2.0× 324 22.1k
Christopher W. Kahler United States 70 4.0k 0.5× 6.3k 1.3× 2.3k 0.5× 1.7k 0.6× 5.5k 2.2× 343 19.1k
Sacha Epskamp Netherlands 40 11.1k 1.4× 3.9k 0.8× 2.2k 0.5× 5.8k 2.1× 1.3k 0.5× 93 15.6k
Robert J. DeRubeis United States 58 6.3k 0.8× 7.9k 1.6× 3.2k 0.8× 1.5k 0.5× 2.1k 0.9× 197 15.0k
Eiko I. Fried Netherlands 51 9.9k 1.2× 4.1k 0.8× 1.9k 0.4× 5.0k 1.8× 1.3k 0.5× 143 13.5k

Countries citing papers authored by Peter Kuppens

Since Specialization
Citations

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

Fields of papers citing papers by Peter Kuppens

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Kuppens

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Kuppens. A scholar is included among the top collaborators of Peter Kuppens 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 Peter Kuppens. Peter Kuppens 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.
Tuerlinckx, Francis, Peter Kuppens, Egon Dejonckheere, et al.. (2025). New developments in experience sampling methodology. British Journal of Mathematical and Statistical Psychology. 79(1). 46–65.
2.
3.
Mestdagh, Merijn, et al.. (2023). Combining Experience Sampling and Mobile Sensing for Digital Phenotyping With m-Path Sense: Performance Study. JMIR Formative Research. 7. e43296–e43296. 4 indexed citations
4.
Kuppens, Peter, et al.. (2023). Can action tendencies be counteracted by inducing incompatible emotions? Considering instances of anxiety and anger. Brain and Behavior. 13(11). e3247–e3247. 1 indexed citations
5.
Weermeijer, Jeroen, Ginette Lafit, Glenn Kiekens, et al.. (2022). Applying multiverse analysis to experience sampling data: Investigating whether preprocessing choices affect robustness of conclusions. Behavior Research Methods. 54(6). 2981–2992. 10 indexed citations
6.
Velozo, Joana De Calheiros, Jeroen Habets, Noëmi Hagemann, et al.. (2022). Designing daily-life research combining experience sampling method with parallel data. Psychological Medicine. 54(1). 98–107. 11 indexed citations
7.
Mestdagh, Merijn, et al.. (2021). Tracking Subjective Sleep Quality and Mood With Mobile Sensing: Multiverse Study. Journal of Medical Internet Research. 24(3). e25643–e25643. 10 indexed citations
8.
Bringmann, Laura F., Casper J. Albers, Claudi Bockting, et al.. (2021). Psychopathological networks: Theory, methods and practice. Behaviour Research and Therapy. 149. 104011–104011. 152 indexed citations breakdown →
9.
Mestdagh, Merijn, et al.. (2021). In Search of State and Trait Emotion Markers in Mobile-Sensed Language: Field Study. JMIR Mental Health. 9(2). e31724–e31724. 7 indexed citations
10.
MacCann, Carolyn, Yasemin Erbaş, Egon Dejonckheere, et al.. (2020). Emotional Intelligence Relates to Emotions, Emotion Dynamics, and Emotion Complexity. European Journal of Psychological Assessment. 36(3). 460–470. 23 indexed citations
11.
Gucht, Katleen Van der, Charlotte Sleurs, Ahmed Radwan, et al.. (2020). Effects of a mindfulness‐based intervention on cancer‐related cognitive impairment: Results of a randomized controlled functional magnetic resonance imaging pilot study. Cancer. 126(18). 4246–4255. 44 indexed citations
12.
Mestdagh, Merijn, et al.. (2020). The Affective Ising Model: A computational account of human affect dynamics. PLoS Computational Biology. 16(5). e1007860–e1007860. 16 indexed citations
13.
Erbaş, Yasemin, Peter Kuppens, Elise K. Kalokerinos, & Eva Ceulemans. (2019). Emotion differentiation and emotion regulation in daily life. OSF Preprints (OSF Preprints).
14.
15.
Koval, Peter, Jordan D. X. Hinton, John Gleeson, et al.. (2019). Modeling individual differences in emotion regulation repertoire in daily life with multilevel latent profile analysis.. Emotion. 20(8). 1462–1474. 77 indexed citations
16.
Liu, Siwei, Peter Kuppens, & Laura F. Bringmann. (2019). On the Use of Empirical Bayes Estimates as Measures of Individual Traits. Assessment. 28(3). 845–857. 32 indexed citations
17.
Dejonckheere, Egon, Elise K. Kalokerinos, Brock Bastian, & Peter Kuppens. (2018). Poor emotion regulation ability mediates the link between depressive symptoms and affective bipolarity. Cognition & Emotion. 33(5). 1076–1083. 27 indexed citations
18.
Leersnyder, Jozefien De, Peter Koval, Peter Kuppens, & Batja Mesquita. (2017). Emotions and concerns: Situational evidence for their systematic co-occurrence.. Emotion. 18(4). 597–614. 28 indexed citations
19.
Thompson, Renee J., Peter Kuppens, Jutta Mata, et al.. (2015). Emotional clarity as a function of neuroticism and major depressive disorder.. Emotion. 15(5). 615–624. 37 indexed citations
20.
Rijmen, Frank, Francis Tuerlinckx, Paul De Boeck, & Peter Kuppens. (2003). A nonlinear mixed model framework for item response theory.. Psychological Methods. 8(2). 185–205. 172 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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