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Probabilistic pathways from chronic pain to suicidal ideation in Qatar: a Bayesian-Network study.
Aisha Al-Khinji1, Dhafer Malouche2
1College of Medicine, Qatar University, Doha, Qatar. aalkhinji@qu.edu.qa.
Journal of Translational Medicine
|May 20, 2026
Summary
This study mapped probabilistic links between chronic pain, mental health, and suicidal thoughts in Qatar. Self-regret and psychomotor changes were strongly associated with suicidal ideation, highlighting key targets for integrated screening.
Area of Science:
- Epidemiology
- Mental Health Research
- Computational Psychiatry
Background:
- Chronic pain is linked to increased risk of depressive, anxiety, and suicidal symptoms.
- Understanding these associations in Middle Eastern populations is limited.
- This study addresses the gap by examining probabilistic links in Qatari adults.
Purpose of the Study:
- To map probabilistic interdependencies between chronic pain, mental health symptoms, and demographics in Qatari adults.
- To identify factors associated with suicidal thoughts.
- To inform integrated screening and intervention strategies.
Main Methods:
- Utilized questionnaire data from 2363 Qatari adults (Qatar Biobank).
- Employed data-driven Bayesian Network (BN) modeling with hill-climbing and BIC scoring.
- Constrained BN with domain knowledge and validated arc stability via bootstrap resampling.
Main Results:
- Identified 38 stable directed edges in the BN, revealing complex associations.
- Self-regret (OR=9.45) and psychomotor change (OR=6.68) were strongest direct associates of suicidal thoughts.
- A symptom cluster (sleep problems → anhedonia → depression → self-regret) showed strong links to elevated suicide risk; fatigue linked pain and self-regret.
Conclusions:
- Bayesian Network modeling elucidated complex, non-linear associations between pain, mental health, and suicidality in Qatar.
- Cross-sectional design limits causal inference; longitudinal studies are needed.
- Identified high-risk symptom clusters (self-regret, psychomotor disturbance) as targets for integrated pain-mental health screening, with potential for demographic tailoring.
