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ConNEcT: A Novel Network Approach for Investigating the Co-occurrence of Binary Psychopathological Symptoms Over Time

Author

Listed:
  • Nadja Bodner

    (KU Leuven (University of Leuven))

  • Laura Bringmann

    (University of Groningen
    University of Groningen)

  • Francis Tuerlinckx

    (KU Leuven (University of Leuven))

  • Peter Jonge

    (University of Groningen
    University of Groningen)

  • Eva Ceulemans

    (Leuven (University of Leuven))

Abstract

Network analysis is an increasingly popular approach to study mental disorders in all their complexity. Multiple methods have been developed to extract networks from cross-sectional data, with these data being either continuous or binary. However, when it comes to time series data, most efforts have focused on continuous data. We therefore propose ConNEcT, a network approach for binary symptom data across time. ConNEcT allows to visualize and study the prevalence of different symptoms as well as their co-occurrence, measured by means of a contingency measure in one single network picture. ConNEcT can be complemented with a significance test that accounts for the serial dependence in the data. To illustrate the usefulness of ConNEcT, we re-analyze data from a study in which patients diagnosed with major depressive disorder weekly reported the absence or presence of eight depression symptoms. We first extract ConNEcTs for all patients that provided data during at least 104 weeks, revealing strong inter-individual differences in which symptom pairs co-occur significantly. Second, to gain insight into these differences, we apply Hierarchical Classes Analysis on the co-occurrence patterns of all patients, showing that they can be grouped into meaningful clusters. Core depression symptoms (i.e., depressed mood and/or diminished interest), cognitive problems and loss of energy seem to co-occur universally, but preoccupation with death, psychomotor problems or eating problems only co-occur with other symptoms for specific patient subgroups.

Suggested Citation

  • Nadja Bodner & Laura Bringmann & Francis Tuerlinckx & Peter Jonge & Eva Ceulemans, 2022. "ConNEcT: A Novel Network Approach for Investigating the Co-occurrence of Binary Psychopathological Symptoms Over Time," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 107-132, March.
    • Handle: RePEc:spr:psycho:v:87:y:2022:i:1:d:10.1007_s11336-021-09765-2
    DOI: 10.1007/s11336-021-09765-2
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    References listed on IDEAS

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    1. Epskamp, Sacha & Cramer, Angélique O.J. & Waldorp, Lourens J. & Schmittmann, Verena D. & Borsboom, Denny, 2012. "qgraph: Network Visualizations of Relationships in Psychometric Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i04).
    2. Angélique O J Cramer & Claudia D van Borkulo & Erik J Giltay & Han L J van der Maas & Kenneth S Kendler & Marten Scheffer & Denny Borsboom, 2016. "Major Depression as a Complex Dynamic System," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-20, December.
    3. Racine, Jeff, 2000. "Consistent cross-validatory model-selection for dependent data: hv-block cross-validation," Journal of Econometrics, Elsevier, vol. 99(1), pages 39-61, November.
    4. Stijn de Vos & Klaas J Wardenaar & Elisabeth H Bos & Ernst C Wit & Mara E J Bouwmans & Peter de Jonge, 2017. "An investigation of emotion dynamics in major depressive disorder patients and healthy persons using sparse longitudinal networks," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-18, June.
    5. Eva Ceulemans & Iven Mechelen & Iwin Leenen, 2007. "The Local Minima Problem in Hierarchical Classes Analysis: An Evaluation of a Simulated Annealing Algorithm and Various Multistart Procedures," Psychometrika, Springer;The Psychometric Society, vol. 72(3), pages 377-391, September.
    6. Eva Ceulemans & Iven Mechelen, 2005. "Hierarchical classes models for three-way three-mode binary data: interrelations and model selection," Psychometrika, Springer;The Psychometric Society, vol. 70(3), pages 461-480, September.
    7. Paul Boeck & Seymour Rosenberg, 1988. "Hierarchical classes: Model and data analysis," Psychometrika, Springer;The Psychometric Society, vol. 53(3), pages 361-381, September.
    8. Hudson F Golino & Sacha Epskamp, 2017. "Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-26, June.
    9. Sacha Epskamp & Joost Kruis & Maarten Marsman, 2017. "Estimating psychopathological networks: Be careful what you wish for," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-13, June.
    10. Iven Mechelen & Paul Boeck & Seymour Rosenberg, 1995. "The conjunctive model of hierarchical classes," Psychometrika, Springer;The Psychometric Society, vol. 60(4), pages 505-521, December.
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    1. Denny Borsboom, 2022. "Possible Futures for Network Psychometrics," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 253-265, March.
    2. Maarten Marsman & Mijke Rhemtulla, 2022. "Guest Editors’ Introduction to The Special Issue “Network Psychometrics in Action”: Methodological Innovations Inspired by Empirical Problems," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 1-11, March.

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