Personalized Network Modeling in Psychopathology: The Importance of Contemporaneous and Temporal Connections
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Recent literature has introduced (a) the network perspective to psychology and (b) collection of time series data to capture symptom fluctuations and other time varying factors in daily life. Combining these trends allows for the estimation of intraindividual network structures. We argue that these networks can be directly applied in clinical research and practice as hypothesis generating structures. Two networks can be computed: a temporal network, in which one investigates if symptoms (or other relevant variables) predict one another over time, and a contemporaneous network, in which one investigates if symptoms predict one another in the same window of measurement. The contemporaneous network is a partial correlation network, which is emerging in the analysis of cross-sectional data but is not yet utilized in the analysis of time series data. We explain the importance of partial correlation networks and exemplify the network structures on time series data of a psychiatric patient.
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Initial case studies have shown that person-specific networks were feasible, well-received by patients, and provided clinically relevant information.
“Several initial case studies, which collected data through ESM and created PSNs for individual patients, have shown that PSNs were feasible, well-received by patients, and provided clinically relevant information [24–27].”
From Using person-specific networks in psychotherapy: challenges, limitations, and how we could use them anyway (2020) · cites this paper as [25]
Proof-of-principle studies applying person-specific networks have made different choices in creating them.
“This is illustrated by the fact that proof-of-principle studies applying PSNs have made different choices in creating PSNs [24–27].”
From Using person-specific networks in psychotherapy: challenges, limitations, and how we could use them anyway (2020) · cites this paper as [25]
Person-specific networks capture processes that occur on short time scales, in the order of minutes, because such processes are traceable in contemporaneous associations.
“PSNs capture processes that occur on short time scales (e.g., in the order of minutes), because such processes are traceable in contemporaneous associations [25].”
From Using person-specific networks in psychotherapy: challenges, limitations, and how we could use them anyway (2020) · cites this paper as [25]
The use of PSNs in psychotherapy has mostly been framed as exploratory, providing suggestions rather than answers.
“Although some researchers have proposed that PSNs could yield such firm conclusions [22, 23], the use of PSNs in psychotherapy has mostly been framed as exploratory [25, 44]—providing suggestions rather than answers.”
From Using person-specific networks in psychotherapy: challenges, limitations, and how we could use them anyway (2020) · cites this paper as [25]
Even when a node has no impact on other variables in the temporal network, it still can have an impact on subsequent variables by being central in the contemporaneous network.
“Moreover, even when a node has no impact on other variables in the temporal network, it still can have an impact on subsequent variables by being central in the contemporaneous network (Epskamp et al., 2018).”
From Modelling suicide ideation from beep to beep: application of network analysis to ecological momentary assessment data (2019) · cites this paper as Epskamp et al., 2018
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Schellekens, M. P. J., Bootsma, T. I., Van Woezik, R. A. M., & Van der Lee, M. L. (2021) · Journal for Person-Oriented Research · doi:10.17505/jpor.2021.23447 · Cited by 9 · see citing works
Butler, R. M., Williams, B., Fitterman-Harris, H., Sala, M., Roos, C. R., & Levinson, C. A. (2024) · Mindfulness · doi:10.1007/s12671-024-02394-7 · Cited by 4 · see citing works
- Authors
- Epskamp, S., van Borkulo, C. D., van der Veen, D. C., Servaas, M. N., Isvoranu, A.-M., Riese, H., & Cramer, A. O. J.
- Affiliations
- University of Amsterdam (NL)
- Department of Psychological Methods, University of Amsterdam
- Department of Psychiatry, Interdisciplinary Center for Psychopathology and Emotion Regulation, University Medical Center Groningen, University of Groningen
- University Medical Center Groningen (NL)
- Corresponding author
- Epskamp, Sacha
- Venue
- Clinical Psychological Science
- Publisher
- SAGE Publications
- Published
- 2018-01-19
- Volume
- 6
- Issue
- 3
- Pages
- 416-427
- ISSN
- 2167-7026 (ISSN-L)
- 2167-7034
- PMC
- PMC5952299
- OpenAlex
- W2768795110
- Cited by
- 448
- References
- 76
- Citations by year
- 2026: 55 · 2025: 66 · 2024: 65 · 2023: 59 · 2022: 50 · 2021: 44 · 2020: 57 · 2019: 32 · 2018: 18 · 2017: 1 · 2014: 1
- FWCI
- 49.45
- Type
- journal article
- Language
- en
- Update notices
- correction (2019-06-10)
- Open access
- hybrid
- doi.org
- Locations
- Clinical Psychological Science (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- Research portal (Tilburg University) (publishedVersion, other-oa)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion, cc-by-nc)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by-nc)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- network modeling, psychopathology, dynamic networks, partial correlation networks, time series, symptom fluctuation, hypothesis generation, psychiatric patients
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