The impact of communicating personal mental ill-health risk: Arandomized controlled non-inferiority trial.

Abstract

Risk algorithms predicting personal mental ill-health will form an important component of digital and personalized preventive interventions, yet it is unknown whether informing people of personal risk may cause unintended harm. This trial evaluated the comparative effect of communicating personal mental ill-health risk profiles on psychological distress. Australian participants using a mood-monitoring app were randomly allocated to receiving their current personal mental ill-health risk profile (n=119), their achievable personal risk profile (n=118) or to a control group (n=118) in which no risk information was communicated, in a non-inferiority trial design. The primary outcome was psychological distress at four-weeks as assessed on the Kessler Psychological Distress Scale. There was high attrition in the trial with 64% of data missing at follow up. Per-protocol (completer) analysis found that the lower bounds of the confidence intervals of the estimated mean change of the current risk (m=0.19, 95% CI: -2.59- 2.98) and achievable risk (m=-0.09, 95% CI: -2.84 to 2.66) groups were within the non-inferiority margin of the control group's mean at follow up. Supplementary intention-to-treat analysis using Multivariate Imputation by Chained Equations (MICE) found that 98/100 imputed datasets of the current risk profile group, and all imputed datasets of the achievable risk profile group showed non-inferiority to the control group. This study provides preliminary support that providing personal mental health risk profiles does not lead to unacceptable worsening of distress compared to no risk feedback, although this needs to be replicated in a fully powered RCT.