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Methodological and Statistical Practices of Using Symptom Networks to Evaluate Mental Health Interventions: A Review and Reflections.
Schumacher, Lea; Burger, Julian; Echterhoff, Jette; Kriston, Levente.
Afiliação
  • Schumacher L; Department of Medical Psychology, University Medical Center Hamburg-Eppendorf.
  • Burger J; Department of Psychological Methods, University of Amsterdam.
  • Echterhoff J; University Medical Center Groningen, University of Groningen.
  • Kriston L; Centre for Urban Mental Health, University of Amsterdam.
Multivariate Behav Res ; : 1-14, 2024 May 11.
Article em En | MEDLINE | ID: mdl-38733300
ABSTRACT
The network approach to psychopathology, which assesses associations between individual symptoms, has recently been applied to evaluate treatments for mental disorders. While various options for conducting network analyses in intervention research exist, an overview and an evaluation of the various approaches are currently missing. Therefore, we conducted a review on network analyses in intervention research. Studies were included if they constructed a symptom network, analyzed data that were collected before, during or after treatment of a mental disorder, and yielded information about the treatment effect. The 56 included studies were reviewed regarding their methodological and analytic strategies. About half of the studies based on data from randomized trials conducted a network intervention analysis, while the other half compared networks between treatment groups. The majority of studies estimated cross-sectional networks, even when repeated measures were available. All but five studies investigated networks on the group level. This review highlights that current methodological practices limit the information that can be gained through network analyses in intervention research. We discuss the strength and limitations of certain methodological and analytic strategies and propose that further work is needed to use the full potential of the network approach in intervention research.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Multivariate Behav Res Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Multivariate Behav Res Ano de publicação: 2024 Tipo de documento: Article