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Cognitive therapy, pioneered by Aaron T. Beck in the 1960s, is a structured approach to addressing psychological distress by focusing on the influence of thoughts on emotions and behaviors. All cognitive therapies involve the basic assumption that human beings have control over their feelings, and that how individuals feel about something depends on how they think about it. Unlike psychoanalytic methods that delve into unconscious processes or humanistic approaches emphasizing...
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Cognitive therapy is a psychological approach designed to address distortions in thinking, which can lead to negative emotions and unrealistic beliefs. These cognitive distortions often influence how individuals interpret and respond to situations, exacerbating emotional distress. Below are some prevalent cognitive distortions, their characteristics, and examples of how they manifest in thought processes.
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The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
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Predicting optimal treatment allocation for cognitive analytic-guided self-help versus cognitive behavioural-guided

Caroline Wojnarowski1, Melanie Simmonds-Buckley1,2, Stephen Kellett1,2

  • 1University of Sheffield, Sheffield, UK.

The British Journal of Clinical Psychology
|October 24, 2024
PubMed
Summary

Personalizing guided self-help (GSH) for anxiety using a patient advantage index (PAI) significantly improves outcomes. Matching patients to their optimal GSH, whether cognitive analytic therapy-guided self-help (CAT-GSH) or cognitive behavioural therapy-guided self-help (CBT-GSH), leads to better anxiety reduction.

Keywords:
anxietycognitive analytic therapycognitive behavioural therapyguided self‐helpmachine learningpatient advantage indexpatient preference

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Area of Science:

  • Psychology
  • Clinical Psychology
  • Mental Health Interventions

Background:

  • Low-intensity guided self-help (GSH) interventions are widely used in routine mental health services.
  • Optimizing patient selection for GSH can enhance organizational efficiency and treatment effectiveness.
  • Identifying which patients benefit most from specific GSH types is crucial for effective treatment matching.

Purpose of the Study:

  • To define patient characteristics that predict optimal response to two distinct types of guided self-help (GSH) for anxiety.
  • To enable better future treatment matching by identifying predictors of success for cognitive analytic therapy-guided self-help (CAT-GSH) and cognitive behavioural therapy-guided self-help (CBT-GSH).

Main Methods:

  • Utilized outcome data from a patient preference trial (N=209) comparing CAT-GSH and CBT-GSH.
  • Employed Elastic Net regularization and Boruta random forest for variable selection.
  • Calculated the patient advantage index (PAI) using regression models to determine the most effective GSH for each patient.

Main Results:

  • Lower baseline depression and anxiety severity were associated with better outcomes for both GSH types.
  • Patients receiving their PAI-indicated optimal GSH showed significantly higher rates of reliable and clinically significant anxiety reduction (35.9% vs. 16.6% post-treatment; 36.6% vs. 19.2% follow-up).
  • No patient with a large PAI achieved reliable and clinically significant anxiety reduction when not receiving their optimal GSH.

Conclusions:

  • Treatment matching algorithms, such as the PAI, show potential for supporting evidence-based selection of GSH interventions.
  • Integrating treatment selection with patient choice is essential for effective mental healthcare.
  • Future research with larger, balanced samples is needed to further investigate the PAI for GSH treatment matching.