Symptom network models in depression research: From methodological exploration to clinical application

van Borkulo, C. D. 2018 [Groningen]: University of Groningen. 316 p.

Research output: ThesisThesis fully internal (DIV)

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  • Title and contents

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  • Chapter 1

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  • Chapter 2

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  • Chapter 3

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  • Chapter 4

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  • Chapter 5

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    Embargo ends: 17/01/2019

  • Chapter 6

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  • Chapter 7

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  • Chapter 8

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  • Chapter 9

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    Embargo ends: 17/01/2019

  • Chapter 10

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  • Chapter 11

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  • Appendix A

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  • Appendix B

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  • Appendix C

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  • Appendix D

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  • Appendix E

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  • Bibliography

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  • Nederlandse samenvatting

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  • Curriculum Vitae

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  • List of publications

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  • Dankwoord (acknowledgements)

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  • Complete thesis

    Final publisher's version, 19 MB, PDF-document

    Embargo ends: 17/01/2019

  • Propositions

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According to the network perspective on psychopathology, mental disorders can be viewed as a network of causally interacting symptoms. With the network approach in mind, hypotheses can be formulated about psychopathology and treatment.

The starting point of Claudia van Borkulo’s thesis is based on two central questions: “Why do some people develop a depressive episode, while others do not?” and “Why do some patients recover, while others do not?” She investigated these questions from a network perspective. To be able to do that, she first developed the required methodology: eLasso (implemented in R-package IsingFit) to infer the network structure from binary data and the Network Comparison Test (NCT; implemented in R-package NetworkComparisonTest) to statistically compare networks. In several validation studies, she showed that eLasso is a computational efficient method that performs well under various circumstances in psychology and psychiatry research. Also, NCT can detect differences under various circumstances.

Subsequently, she applied the methods to empirical data. She showed that the density of patients’ symptom network was associated with the course of depression. Also, centrality of the depression symptoms of healthy individuals seems to have a predictive value for developing depression. Although these results pertain to group-level networks – thereby making it unclear what the results mean to an individual – they provide interesting starting points for future research.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Schoevers, Robert, Supervisor
  • Borsboom, Denny, Supervisor, External person
  • Boschloo, Lynn, Co-supervisor
  • Waldorp, Lourens J., Co-supervisor, External person
  • Engelhard, Iris M., Assessment committee, External person
  • Oldehinkel, Tineke, Assessment committee
  • Timmerman, Marieke, Assessment committee
Award date17-Jan-2018
Place of Publication[Groningen]
Print ISBNs978-94-034-0379-3
Electronic ISBNs978-94-034-0378-6
StatePublished - 2018

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