Probabilistic pathways from chronic pain to suicidal ideation in Qatar: a Bayesian-Network study

Abstract

Chronic pain frequently co-occurs with depressive and anxiety symptoms and doubles or triples the risk of suicidal ideation. Yet the joint probabilistic associations linking these conditions remain under-explored in Middle Eastern settings. This study analyzed questionnaire data from 2,363 Qatari adults from the Qatar Biobank using a data-driven Bayesian Network approach with hill-climbing and Bayesian Information Criterion scoring. Domain-knowledge constraints designated demographic variables as exogenous and suicidal ideation as terminal. The final network contained 46 directed edges; bootstrap resampling confirmed 38 as stable. Self-regret and psychomotor changes emerged as strongest direct probabilistic associates of suicidal thoughts. A symptom cluster (sleep problems progressing to anhedonia to depression) showed elevated suicide risk linkage. Fatigue associated with both all-body pain and self-regret, illustrating physical–psychological co-occurrence. Age and gender moderated associations, with younger women demonstrating the highest conditional probability of complete symptom clustering. Because the design is cross-sectional, causal directionality remains unestablished; longitudinal validation is needed.