Negative and Positive Affect Regulation in a Transdiagnostic Internet-Based Protocol for Emotional Disorders: Randomized Controlled Trial
Abstract
Background Emotional disorders (EDs) are among the most prevalent mental disorders. Existing evidence-based psychological treatments are not sufficient to reduce the disease burden of mental disorders. It is therefore essential to implement innovative solutions to achieve a successful dissemination of psychological treatment protocols, and in this regard, the use of information and communication technologies such as the internet can be very useful. Furthermore, the literature suggests that not everyone with an ED receives the appropriate treatment. This situation has led to the development of new intervention proposals based on the transdiagnostic perspective, which attempts to address the underlying processes common to EDs. Most of these transdiagnostic interventions focus primarily on downregulating negative affectivity (NA), and less attention has been paid to strengths and the upregulation of positive affectivity, despite its importance for well-being and mental health. Objective This study aims to evaluate the efficacy of a transdiagnostic internet-based treatment for EDs in a community sample. Methods A 3-armed randomized controlled trial was conducted. A total of 216 participants were randomly assigned to a transdiagnostic internet-based protocol (TIBP), a TIBP+ positive affect (PA) component, or a waiting list (WL) control group. The treatment protocol contained core components mainly addressed to downregulate NA (ie, present-focused emotional awareness and…
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. Reported size: 216 participants or records.
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.