Methodological limitations in the measurement and statistical modeling of violence among adults with mental illness

Methodological limitations of extant research hinder the development of effective violence risk screening, assessment, and management strategies for adults with mental illness. This study quantifies the effects of three common limitations: (a) insensitive measurement of violence that results in violence classification with high levels of information bias, (b) use of cross-sectional data, and (c) use of data lacking spatiotemporal contiguity.

We utilize secondary data (N = 3,000 participants; N = 10,017 observations) and parametric and nonparametric bootstrap simulation methodologies.

Not utilizing self-reported violence data increases information bias. Furthermore, cross-sectional data that exclude self-reported violence produce biased associations between substance use and psychiatric symptoms and violence. Associations between baseline variables and subsequent violence attenuate over longer time lags and, when paired with high levels of violence information bias, result in fewer significant effects than should be present. Moreover, the true direction of the simulated relationship of some significant effects is reversed.

Our findings suggest that the validity of conclusions from some extant research on violence among adults with mental illness should be questioned. Efforts are needed to improve both the measurement of violence, through inclusion of self-report, and the statistical modeling of violence, using lagged rather than nonlagged models with improved spatiotemporal contiguity.