Response to Uncertainty and Social Threat: Impact on Mental Health (RUSH) Study Protocol

Abstract

Background: Depression is frequently treatment-resistant, and its etiological underpinnings remain poorly understood. Chronic systemic inflammation may drive difficult-to-treat cases, yet prospective naturalistic studies among non-depressed individuals are needed to inform etiology and prevention. This protocol describes the R esponse to U ncertainty and S ocial Threat: Impact on Mental H ealth (RUSH) Study, a multi-week naturalistic stress paradigm comparing current sorority members (controls) to recruits experiencing social-evaluative threat—representing the first naturalistic test of the Social Signal Transduction Theory of Depression. Wave 1 (n=30) is complete; here we present feasibility data and Wave 2 modifications. Methods: Participants completed four visits: one before recruitment, one before and one after a single recruitment day (to assess acute reactivity), and one post-recruitment. At each visit, they completed surveys, a dried blood spot (DBS) to assess inflammatory markers, and a saliva sample to assess cortisol. Before and after the single recruitment day, they completed a computerized social approach/avoidance task. Ecological momentary assessments (EMAs) were completed five times daily for 4 days before and after recruitment and twice daily during the recruitment period (12 days), alongside continuous Oura Ring physiological monitoring. Results: No participant withdrew after Visit 1. Participants rated staff highly and all expressed willingness to participate again. A DBS was obtained in 98.2% of attempts; among these, sessions yielded a mean of 4.32 of five spots per session. Sufficient saliva was obtained in 89.0% of attempts. The overall EMA compliance rate was 79.7% (SD=20.8%), with recruits (M=87.7%, SD=14.6%) outperforming members (M=74.4%, SD=22.9%). However, participants found the pre- and post-recruitment EMA frequency to be burdensome, prompting consolidation in Wave 2. Ninety-seven percent submitted support figure photos, and AI-generated stranger photos were largely indistinguishable from real photographs.

The authors' abstract, as published at the source. Psychosomatic Medicine, 2026 · DOI ↗