Modelling Depression, Anxiety, and Stress Among Inmates in North Central Nigeria: A Comparison of Baseline and Interaction-Based Multivariate Ordinal Regression Models

The global correctional system faces a severe mental health crisis, with inmates suffering disproportionately from depression, anxiety, and stress (DAS). In low-resource settings like Nigeria, this crisis is acute. Traditional statistical models often inadequately capture the ordinal nature of standard mental health scales and the correlations between these co- occurring conditions. This study addresses these methodological gaps by developing and comparing two advanced models to assess DAS among inmates in North Central Nigeria. Using a cross-sectional design, data were collected from 830 inmates across six facilities with the DASS-42 questionnaire and a socio-demographic form. The baseline multivariate ordinal probit model was first fitted to jointly model the three correlated outcomes. To overcome its limitation of assuming constant predictor effects, a novel interaction-based multivariate ordinal model was developed incorporating theoretically-grounded interaction terms. The interaction-based model demonstrated a superior fit (AIC = 8791.96) over the baseline (AIC = 8811.23), revealing critical effect heterogeneities. For instance, the impact of marital status on depression differed by gender. Predictions from the superior model indicated alarming prevalence rates, with 46.9% of inmates likely experiencing extremely severe anxiety and 42.4% severe depression. Distinct joint DAS profiles were identified, highlighting significant co-morbidity. This study concludes that the interaction-based multivariate ordinal model provides a robust and detailed framework for understanding inmate mental health, enabling the precise identification of high-risk subgroups for targeted, efficient, and effective clinical interventions and resource allocation within correctional systems.