Clinical effectiveness, cost-effectiveness and process evaluation of group schema therapy for eating disorders: study protocol for a multicenter randomized controlled trial
Abstract
Background: Eating disorders (EDs), such as (atypical) Anorexia (AN) and Bulimia Nervosa (BN), are difficult to treat, causing socioeconomic impediments. Although enhanced cognitive behavioral therapy (CBT-E) is widely considered clinically effective, it may not be the most beneficial treatment for (atypical) AN and BN patients who do not show a rapid response after the first 4 weeks (8 sessions) of a CBT-E treatment. Alternatively, group schema therapy (GST) may be a valuable treatment for this ED population. Even though GST for EDs has yielded promising preliminary findings, the current body of evidence requires expansion. On top of that, data on cost-effectiveness is lacking. In light of these gaps, we aim to describe a protocol to examine whether GST is more (1) clinically effective and (2) cost-effective than CBT-E for (atypical) AN and BN patients, who do not show a rapid response after the first 4 weeks of treatment. Additionally, we will conduct (3) process evaluations for both treatments.
Methods: Using a multicenter RCT design, 232 Dutch (atypical) AN and BN patients with a CBT-E referral will be recruited from five treatment centers. Clinical effectiveness and cost-effectiveness will be measured before treatment, directly after treatment, at 6 and at 12 months follow-up. In order to rate process evaluation, patient experiences and the degree to which treatments are implemented according to protocol will be measured. In order to assess the quality of life and the…
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.