Journal of anxiety disorders · 2020
Typical symptom change patterns and their predictors in patients with social anxiety disorder: A latent class analysis.
СтатьяРандомизированное исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Altmann Uwe, Gawlytta Romina, Hoyer Jürgen, Leichsenring Falk, Leibing Eric, Beutel Manfred, Willutzki Ulrike, Herpertz Stephan, Strauss Bernhard
Аннотация
OBJECTIVES: The use of trajectories and analysis of change patterns is a promising way toward better differentiation of subgroups in psychotherapy studies. Research on change patterns in social anxiety disorder (SAD) are still rare, although SAD is one of the most common mental disorders. In a secondary analysis of data from the SOPHO-NET-trial (ISRCTN53517394) this study aimed to investigate change patterns and their predictors in a sample of SAD patients.
METHODS: Patients with SAD (N = 357) were randomly assigned to cognitive-behavioral or psychodynamic therapy. The Liebowitz Social Anxiety Scale (LSAS) was assessed at 1st session (pre), 8th session, 15th session and at the end of treatment (post). We used latent state variables and latent class analysis for the classification of change patterns and logistic regression for the identification of different predictors.
RESULTS: Analyses revealed three typical patterns: (i.) responders with a high initial impairment (N = 57), (ii.) responders with a moderate initial impairment (N = 225), and (iii.) patients with a high initial impairment and no remission (N = 75). Among other significant predicators, patient´s attachment anxiety and therapeutic alliance at session eight contributed to the prediction of change patterns.
DISCUSSION: Psychotherapy of SAD should consider patient's attachment and focus on the establishment of a solid therapeutic alliance in an early therapy stage.
METHODS: Patients with SAD (N = 357) were randomly assigned to cognitive-behavioral or psychodynamic therapy. The Liebowitz Social Anxiety Scale (LSAS) was assessed at 1st session (pre), 8th session, 15th session and at the end of treatment (post). We used latent state variables and latent class analysis for the classification of change patterns and logistic regression for the identification of different predictors.
RESULTS: Analyses revealed three typical patterns: (i.) responders with a high initial impairment (N = 57), (ii.) responders with a moderate initial impairment (N = 225), and (iii.) patients with a high initial impairment and no remission (N = 75). Among other significant predicators, patient´s attachment anxiety and therapeutic alliance at session eight contributed to the prediction of change patterns.
DISCUSSION: Psychotherapy of SAD should consider patient's attachment and focus on the establishment of a solid therapeutic alliance in an early therapy stage.