ArticleBMC psychiatry2025
Prevalence, associated factors, and nomogram model of suicidality among incarcerated individuals: a developmental adaptation perspective for targeted prevention strategies.
Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundSuicide remains one of the primary causes of death in people in prison, highlighting the urgent need for effective prevention strategies. This study investigated the prevalence and characteristics of suicidality (suicidal ideation, suicidal planning and suicidal attempts) among incarcerated individuals and examined both distal and proximal associated factors using the developmental adaptation framework. Additionally, three predictive models were constructed to assess suicide risk within this population.
methodsA total of 1,700 incarcerated individuals participated in the study, providing data through self-report questionnaires covering demographic variables, distal influences (e.g., childhood adversity, family history), and proximal indicators (e.g., mental health status, alexithymia, hopelessness). Logistic regressions were used to identify significant factors, which informed the construction and validation of nomograms for suicide risk assessment. The models' performance were evaluated in terms of discrimination, accuracy, practical application, and generalizability.
resultsThe findings revealed that 13.4% reported suicidal ideation, 7.8% reported suicide planning, and 6.1% reported suicide attempts. Proximal factors such as hopelessness, anxiety, and depression were strongly associated with suicidality, while childhood trauma emerged as important distal contributors. Three nomograms were developed to predict the risk of suicidal ideation, planning, and attempts, each demonstrating good discrimination and calibration. The AUCs ranged from 0.774 to 0.787 in training cohorts and from 0.764 to 0.829 in validation cohorts. Further validation confirmed their reliability, clinical relevance, and applicability across different gender groups.
conclusionThe predictive models developed in this study offer an effective tool for early detection of suicide risk among incarcerated individuals, supporting correctional staff in timely identification and intervention for high-risk individuals.
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