Background. A growing emphasis on biological and genetic explanations of mental illness has been shown to negatively shape motivations and beliefs about prognosis and treatment. Past research suggests that biogenetic explanations of mental illness may distort perceptions of prognostic outcomes, thereby impeding patient motivation, a potent predictor of treatment engagement and efficacy. The current study investigated the effect of biogenetic messaging about depression on self-reported perceptions of treatment expectancy and emotion regulation. Its effects on neurophysiological correlates of cognition will be explored in subsequent analyses.
Methods. Following a sham saliva test, 43 participants with a history of depression were randomly assigned to receive feedback that they either have (n=21) or do not have (n=22) a genetic predisposition to depression. Brain activity was recorded with high-density electroencephalogram (EEG) and self-reports assessed perceived prognosis, treatment credibility/expectancy and state emotion regulation. Error positivity (Pe) was assessed before and after the saliva test. We expected biogenetic messaging to  increase the perception of medication as being more effective than psychotherapy,  increase ruminative default mode network (DMN) activity and  increase Pe amplitude.
Results. There were no significant effects of condition on treatment expectancy or emotion regulation in the full sample nor when analyses were restricted to those who found the test credible (n=12 in each group). Paradoxically, genetic feedback numerically (but non- significantly) increased participants’ expectations that treatment would alleviate negative mood and allow them to adaptively cope with adverse events. As data collection and analysis is ongoing, changes in DMN and Pe amplitude will be reported in the final poster presentation.
Conclusions. Contrary to previous literature, these findings suggest that patient beliefs and expectations toward prognosis and treatment may not be impacted by this particular biogenetic explanation of depression. Ongoing data collection will allow us to test our hypotheses with appropriate statistical power in future analyses.
Live Zoom Session – April 21st
Steven J. Lamontagne, MSc, Hans S. Schroder, PhD, Jessica M. Duda, BA, Saira Madarasmi, BA, Vaughn Rogers, Esther Yu, Diego A. Pizzagalli, PhD