A SMART approach to personalized care: preliminary data on how to select and sequence skills in transdiagnostic CBT.
Shannon Sauer-ZavalaMatthew W SouthwardNicole E StumppStephen A SemchoCaitlyn O HoodAnna GarlockAlex UrsPublished in: Cognitive behaviour therapy (2022)
Given that over 20 million adults each year do not receive care for their mental health difficulties, it is imperative to improve system-level capacity issues by increasing treatment efficiency. The present study aimed to collect feasibility/acceptability data on two strategies for increasing the efficiency of cognitive behavioral therapy: (1) personalized skill sequences and (2) personalized skill selections. Participants (N = 70) with anxiety and depressive disorders were enrolled in a pilot sequential multiple assignment randomized trial (SMART). Patients were randomly assigned to receive skill modules from the Unified Protocol in one of three sequencing conditions: standard, sequences that prioritized patients' relative strengths, and sequences that prioritized relative deficits. Participants also underwent a second-stage randomization to either receive 6 sessions or 12 sessions of treatment. Participants were generally satisfied with the treatment they received, though significant differences favored the Capitalization and Full duration conditions. There were no differences in trajectories of improvement as a function of sequencing condition. There were also no differences in end-of-study outcomes between brief personalized treatment and full standard treatment. Thus, it may be feasible to deliver CBT for personalized durations, though this may not substantially impact trajectories of change in anxiety or depressive symptoms.
Keyphrases
- depressive symptoms
- mental health
- end stage renal disease
- randomized controlled trial
- ejection fraction
- newly diagnosed
- palliative care
- traumatic brain injury
- electronic health record
- adipose tissue
- peritoneal dialysis
- clinical trial
- machine learning
- metabolic syndrome
- physical activity
- prognostic factors
- quality improvement
- obsessive compulsive disorder
- pain management
- weight loss
- deep learning
- amino acid