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Sudden gains in routine clinical care: application of a permutation test for trauma-focused cognitive behavioural therapy.

Sascha KuckThomas EhringAnne DyerAndre PittigJana PeikenkampNexhmedin MorinaGeorg W AlpersAntje Krüger-Gottschalk
Published in: European journal of psychotraumatology (2024)
Background: Sudden gains, defined as large and stable improvements of psychopathological symptoms, are a ubiquitous phenomenon in psychotherapy. They have been shown to occur across several clinical contexts and to be associated with better short-term and long-term treatment outcome. However, the approach of sudden gains has been criticized for its tautological character: sudden gains are included in the computation of treatment outcomes, ultimately resulting in a circular conclusion. Furthermore, some authors criticize sudden gains as merely being random fluctuations. Objective: Use of efficient methods to evaluate whether the amount of sudden gains in a given sample lies above chance level. Method: We used permutation tests in a sample of 85 patients with posttraumatic stress disorder (PTSD) treated with trauma-focused cognitive behaviour therapy in routine clinical care. Scores of self-reported PTSD symptom severity were permuted 10.000 times within sessions and between participants to receive a random distribution. Results: Altogether, 18 participants showed a total of 24 sudden gains within the first 20 sessions. The permutation test yielded that the frequency of sudden gains was not beyond chance level. No significant predictors of sudden gains were identified and sudden gains in general were not predictive of treatment outcome. However, subjects with early sudden gains had a significantly lower symptom severity after treatment. Conclusions: Our data suggest that a significant proportion of sudden gains are due to chance. Further research is needed on the differential effects of early and late sudden gains.
Keyphrases
  • posttraumatic stress disorder
  • healthcare
  • palliative care
  • quality improvement
  • chronic pain
  • depressive symptoms
  • artificial intelligence
  • deep learning
  • affordable care act