A Meta-Analysis and Systematic Review of Single-Session Interventions for Eating Disorders
Abstract
Background: There is a critical gap between the need for eating disorder (ED) treatment and provider availability. Single-Session Interventions (SSIs) are structured programs intentionally designed for a single client encounter and show promise for filling ED-treatment and prevention gaps by enhancing accessibility of evidence-based intervention. Recent studies have started to examine the efficacy of SSIs for various ED concerns, ranging from prevention to symptom reduction. A robust examination of the efficacy of SSIs in addressing ED concerns is thus needed.
Objective: This review assessed whether, and to what degree, ED SSIs are efficacious. Further, this study examined whether the efficacy of SSIs was moderated by SSI function (i.e., treatment versus prevention), SSI implementation format (i.e., self-guided versus provider delivered), SSI administration method (i.e., remote versus in-person), and follow-up duration after SSI completion.
Method: Systematic review and meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. A multi-level random effects meta-analysis using a restricted maximum likelihood estimator was conducted to synthesize effect sizes from 22 primary studies (k = 331 effect sizes). Multi-level meta-regression was conducted to test moderators of ED SSI efficacy. Findings from non-randomized trial design studies were qualitatively synthesized.
Results: Overall Hedge's g effect size…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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.