Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
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Behavioural brain research
Targeting the prefrontal-supplementary motor network with online and offline tDCS to modulate disgust: A single-blind and sham-controlled study
In certain individuals, disgust experience is abnormally high. This heightened sensitivity serves as a cognitive component that can lead to dysfunction in neural circuits related to emotion processing and psychological disorders such as contamination-based obsessive-compulsive disorder. In this single-blind study, 36 individuals with high disgust sensitivity were randomly assigned to three groups: online, offline, and sham. The online group received intensified and repetitive transcranial direct current stimulation (tDCS) while performing a disgust image watching task, whereas the offline and sham groups performed the task at two time points: immediately before (pre-test) and immediately after (post-test) the stimulation session. The offline group received active tDCS, whereas the sham group received placebo tDCS to control for the interval duration. Anodal and cathodal stimulation was applied to the left dorsolateral prefrontal cortex (l-DLPFC; F3) and pre-supplementary motor area (pre-SMA; FC2), respectively. The intervention consisted of 10 sessions of tDCS (2 sessions per day) over 5 days, with a stimulation intensity of 2 mA for 20 min and a 20-minute interval between sessions. The results showed a significant decrease in disgust experience in the online group compared to the offline group, while there was no significant difference between the online and sham groups. Although these findings suggest potential effects of tDCS combined with a task, further studies are necessary to confirm its efficacy.
1 May 2026
Read appraisal →Brain imaging and behavior
Meta-analysis and meta-regression of diagnostic test accuracy of connectome-based predictive modeling in OCD
Functional magnetic resonance imaging studies have reported disruptions in functional connectivity within brain networks, known as connectomes. Researchers have tested connectomes to see whether they serve as biomarkers for various psychiatric conditions. This meta-analysis aims to evaluate the diagnostic test accuracy of predictive models of connectomes derived from resting-state fMRI in diagnosing obsessive-compulsive disorder. A systematic review and meta-analysis were conducted on previous studies assessing the sensitivity, specificity, and accuracy of connectome-based diagnostic models in obsessive-compulsive disorder and healthy controls. Eight studies were identified, comprising 563 individuals with obsessive-compulsive disorder and 564 healthy controls. The results revealed robust diagnostic performance with a pooled sensitivity of 0.827 (95% CI: 0.779-0.867) and specificity of 0.794 (95% CI: 0.759-0.826). Connectome-based diagnostic models demonstrated excellent clinical utility, with an area under the curve of 87% (95% CI: 84%-90%), and significant predictive power as indicated by positive (4.15) and negative (0.21) likelihood ratios, as well as strong diagnostic odds ratio of 18.69 (95% CI: 11.84-29.49). The results highlight the potential of functional connectome-based predictive modeling as a robust tool for accurately diagnosing obsessive-compulsive disorder, with possibility of future implications for early diagnosis, monitoring treatment-related changes, involving in decision modeling, and understanding the biological mechanisms underlying obsessive-compulsive disorder.
20 Apr 2026
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