IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i12p7131-d835889.html
   My bibliography  Save this article

The Mereology of Depression—Networks of Depressive Symptoms during the Course of Psychotherapy

Author

Listed:
  • Inken Höller

    (Department of Clinical Psychology, University of Duisburg-Essen, 45141 Essen, Germany
    These authors contributed equally to this work.)

  • Dajana Schreiber

    (Department of Clinical Psychology, University of Duisburg-Essen, 45141 Essen, Germany
    These authors contributed equally to this work.)

  • Fionneke Bos

    (Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University Medical Center Groningen, University of Groningen, 9700RB Groningen, The Netherlands
    Psychiatric Hospital Mental Health Services Drenthe, Outpatient Clinics, 9401LA Assen, The Netherlands)

  • Thomas Forkmann

    (Department of Clinical Psychology, University of Duisburg-Essen, 45141 Essen, Germany)

  • Tobias Teismann

    (Mental Health Research and Treatment Center, Faculty of Psychology, Ruhr-Universität Bochum, 44787 Bochum, Germany)

  • Jürgen Margraf

    (Mental Health Research and Treatment Center, Faculty of Psychology, Ruhr-Universität Bochum, 44787 Bochum, Germany)

Abstract

(1) Background: Research has shown that it is important to examine depressive symptoms in the light of the mereology (the ratio between one symptom and the whole disorder). The goal of this study was to examine changes in the symptom interrelations of patients undergoing cognitive behavioral therapy treatment (CBT) via network analyses. (2) Method: Outpatients with depressive symptoms ( N = 401) were assessed with the Beck Depression Inventory three times (pretreatment, after 12 sessions, and post-treatment) during CBT. Gaussian graphical models were used to estimate the relationships among symptoms. (3) Results: The severity of depressive symptoms significantly decreased over the course of therapy, but connectivity in the networks significantly increased. Communities of symptoms changed during treatment. The most central and predictable symptom was worthlessness at baseline and after 12 sessions, and loss of energy and self-dislike at post-treatment. (4) Conclusion: The results indicate that the severity of depressive symptoms decreased during cognitive behavior therapy, while network connectivity increased. Furthermore, the associations among symptoms and their centrality changed during the course of therapy. Future studies may investigate individual differences and their impact on the planning of psychotherapeutic treatment.

Suggested Citation

  • Inken Höller & Dajana Schreiber & Fionneke Bos & Thomas Forkmann & Tobias Teismann & Jürgen Margraf, 2022. "The Mereology of Depression—Networks of Depressive Symptoms during the Course of Psychotherapy," IJERPH, MDPI, vol. 19(12), pages 1-13, June.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:12:p:7131-:d:835889
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/12/7131/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/12/7131/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Berend Terluin & Michiel R de Boer & Henrica C W de Vet, 2016. "Differences in Connection Strength between Mental Symptoms Might Be Explained by Differences in Variance: Reanalysis of Network Data Did Not Confirm Staging," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-12, November.
    3. 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.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Zhou, Jianhua & Zhang, Lulu & Gong, Xue, 2023. "Longitudinal network relations between symptoms of problematic internet game use and internalizing and externalizing problems among Chinese early adolescents," Social Science & Medicine, Elsevier, vol. 333(C).
    3. Sacha Epskamp, 2020. "Psychometric network models from time-series and panel data," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 206-231, March.
    4. 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.
    5. Paul B. Perrin & Daniela Ramos-Usuga & Samuel J. West & Kritzia Merced & Daniel W. Klyce & Anthony H. Lequerica & Laiene Olabarrieta-Landa & Elisabet Alzueta & Fiona C. Baker & Stella Iacovides & Mar , 2022. "Network Analysis of Neurobehavioral Symptom Patterns in an International Sample of Spanish-Speakers with a History of COVID-19 and Controls," IJERPH, MDPI, vol. 20(1), pages 1-11, December.
    6. Derek De Beurs, 2017. "Network Analysis: A Novel Approach to Understand Suicidal Behaviour," IJERPH, MDPI, vol. 14(3), pages 1-8, February.
    7. Miguel Ángel Castellanos & Berta Ausín & Sara Bestea & Clara González-Sanguino & Manuel Muñoz, 2020. "A Network Analysis of Major Depressive Disorder Symptoms and Age- and Gender-Related Differences in People over 65 in a Madrid Community Sample (Spain)," IJERPH, MDPI, vol. 17(23), pages 1-13, December.
    8. María Guillot-Valdés & Alejandro Guillén-Riquelme & Juan Carlos Sierra & Gualberto Buela-Casal, 2022. "Network and Exploratory Factorial Analysis of the Depression Clinical Evaluation Test," IJERPH, MDPI, vol. 19(17), pages 1-26, August.
    9. Pedro Henrique Ribeiro Santiago & Gustavo Hermes Soares & Lisa Gaye Smithers & Rachel Roberts & Lisa Jamieson, 2022. "Psychological Network of Stress, Coping and Social Support in an Aboriginal Population," IJERPH, MDPI, vol. 19(22), pages 1-22, November.
    10. M. Marsman & K. Huth & L. J. Waldorp & I. Ntzoufras, 2022. "Objective Bayesian Edge Screening and Structure Selection for Ising Networks," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 47-82, March.
    11. Srebrenka Letina & Tessa F. Blanken & Marie K. Deserno & Denny Borsboom, 2019. "Expanding Network Analysis Tools in Psychological Networks: Minimal Spanning Trees, Participation Coefficients, and Motif Analysis Applied to a Network of 26 Psychological Attributes," Complexity, Hindawi, vol. 2019, pages 1-27, February.
    12. Juyeon Lee & Alvin Junus, 2024. "Differences and Similarities in Youth Social-emotional Competence Measurement Between North American and East Asian Countries: Exploratory Graph Analysis using the OECD Survey on Social and Emotional ," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 17(1), pages 57-79, February.
    13. Georgia Mangion & Melanie Simmonds-Buckley & Stephen Kellett & Peter Taylor & Amy Degnan & Charlotte Humphrey & Kate Freshwater & Marisa Poggioli & Cristina Fiorani, 2022. "Modelling Identity Disturbance: A Network Analysis of the Personality Structure Questionnaire (PSQ)," IJERPH, MDPI, vol. 19(21), pages 1-17, October.
    14. Xiao Yang & Nilam Ram & Scott D. Gest & David M. Lydon-Staley & David E. Conroy & Aaron L. Pincus & Peter C. M. Molenaar, 2018. "Socioemotional Dynamics of Emotion Regulation and Depressive Symptoms: A Person-Specific Network Approach," Complexity, Hindawi, vol. 2018, pages 1-14, November.
    15. Lukáš Copuš & Peter Madzík & Helena Šajgalíková & Karol Čarnogurský, 2023. "Is There a Possibility to Characterize an Organizational Culture by Its Selected Cultural Dimensions?," SAGE Open, , vol. 13(4), pages 21582440231, October.
    16. Andrey Nasledov & Sergey Miroshnikov & Liubov Tkacheva & Kirill Miroshnik & Meriam Uld Semeta, 2021. "Application of Psychometric Approach for ASD Evaluation in Russian 3–4-Year-Olds," Mathematics, MDPI, vol. 9(14), pages 1-21, July.
    17. Michael J. Brusco & Douglas Steinley & Ashley L. Watts, 2022. "Disentangling relationships in symptom networks using matrix permutation methods," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 133-155, March.
    18. Denny Borsboom, 2022. "Possible Futures for Network Psychometrics," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 253-265, March.
    19. Jayawickreme, Nuwan & Mootoo, Candace & Fountain, Christine & Rasmussen, Andrew & Jayawickreme, Eranda & Bertuccio, Rebecca F., 2017. "Post-conflict struggles as networks of problems: A network analysis of trauma, daily stressors and psychological distress among Sri Lankan war survivors," Social Science & Medicine, Elsevier, vol. 190(C), pages 119-132.
    20. Mihail Halachev & Viktoria-Eleni Gountouna & Alison Meynert & Gannie Tzoneva & Alan R. Shuldiner & Colin A. Semple & James F. Wilson, 2024. "Regionally enriched rare deleterious exonic variants in the UK and Ireland," Nature Communications, Nature, vol. 15(1), pages 1-14, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:12:p:7131-:d:835889. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.