The Sunny Side of the Network Approach to Psychopathology: Comparing Nodes as Either Problems or Strengths
Jakob Schenström1, Marie De Mey1, Matthis Andreasson2
1Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Sweden & Stockholm Health Care Services, Region Stockholm, Sweden, mariegdemey@gmail.com.
Objectives:
Personalized symptom networks are emerging as a tool to enhance psychiatric case conceptualizations. However, applications of the approach have so far focused on illness-causing (pathogenic) factors and their relationships with each other, whereas it is possible that a useful case conceptualization needs to include health-promoting (salutogenic) factors. The aim of this study was to investigate adolescents' and clinicians' evaluations of pathogenic and salutogenic idiographic networks.
Methods:
Networks were created for nine adolescent women by using the PECAN (Perceived Causal Networks) method. For every participant two networks were produced: one consisted of symptoms, such as "stuck in negative thoughts" as nodes (pathogenetic), the other health-promoting factors, such as "can let go of negative thoughts" as nodes (salutogenic). The same nine adolescents (Study I) and twenty therapists (Study II) evaluated these networks.
Results:
Adolescents evaluated their salutogenic networks as easier to define and create, but their pathogenic network as more useful. Therapists considered both methods to be clinically useful, but in general rated the salutogenic networks to be more informative. Both adolescents and therapists stressed the complementary use of salutogenic and pathogenic networks.
Conclusions:
Future studies should explore ways to integrate pathogenic and salutogenic nodes in the same network, and compare whether patients collecting longitudinal data might be differentially impacted by a focus on either symptoms or strengths.
Practice Implications:
Person-specific networks could complement traditional case conceptualization by integrating both symptoms and resilience factors.
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