Implementing policies and predictive stochastic models to attend to borderline personality disorder crises: the dysthymia-suicide cycle
C. G. Lazzari

TL;DR
This paper proposes stochastic models and policies to predict and manage crises in borderline personality disorder patients, aiming to improve UK healthcare outcomes.
Contribution
A novel stochastic framework combining logical-mathematical models to predict BPD crisis stages and forecast NHS resource demands.
Findings
Model I accurately predicts the dysthymia-rumination-suicide cycle with 96.87% truth density.
Model II forecasts a national shortage of healthcare resources with 56.25% accuracy.
Combined models predict BPD crisis outcomes in the UK NHS with 73.81% accuracy.
Abstract
UK healthcare is undergoing significant challenges in facing borderline personality disorder (BPD) and accommodating the increased demand to allocate sufficient care and carers to deal with BPD’s growing number and emotional and suicidal crises. To generate forecasting models and preventive policies to deal with BPD crises and improve the effectiveness of the UK National Healthcare Service in suicide prevention (NHS). The underlying analysis framework is stochastic forecasting. We used current knowledge and data to complete systematic future predictions extracted from recent trends. A logical-mathematical model generated the required expressions. The software for logic prediction and annotation was Wolfram Alpha (Wolframalpha.com). Persons with BPD become suicidal because the team cannot comprehend and address the cycle of dysthymia, rumination and suicide. The BPD crises start from…
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Taxonomy
TopicsPersonality Disorders and Psychopathology · Mental Health Research Topics · Suicide and Self-Harm Studies
