Integrating a functional view on suicide risk into idiographic statistical models.

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Publisher: Elsevier Science Publishers
Document Type: Report; Brief article
Length: 351 words

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Keywords Suicide risk; Borderline personality disorder; Idiographic models; Ecological; Momentary assessment; Group iterative multiple model estimation Highlights * Acute suicide risk results from volatile, contextualized dynamic processes. * Idiographic models depict within-person dynamics of suicide risk. * Models reveal high levels of heterogeneity across individuals. * More work is needed before personalized models can be applied in clinical settings. Abstract Acute risk of death by suicide manifests in heightened suicidal ideation in certain contexts and time periods. These increases are thought to emerge from complex and mutually reinforcing relationships between dispositional vulnerability factors and individually suicidogenic short-term stressors. Together, these processes inform clinical safety planning and our therapeutic tools accommodate a reasonable degree of idiosyncrasy when we individualize interventions. Unraveling these multifaceted factors and processes on a quantitative level, however, requires estimation frameworks capable of representing idiosyncrasies relevant to intervention and psychotherapy. Using, data from a 21-day ambulatory assessment protocol that included six random prompts per day, we developed personalized (i.e., idiographic) models of interacting risk factors and suicidal ideation via Group Iterative Multiple Model Estimation (GIMME) in a sample of people diagnosed with borderline personality disorder (N = 95) stratified for a history of high lethality suicide attempts. Our models revealed high levels of heterogeneity in state risk factors related to suicidal ideation, with no features shared among the majority of participants or even among relatively homogenous clusters of participants (i.e., empirically derived subgroups). We discuss steps toward clinical implementation of personalized models, which can eventually capture suicidogenic changes in proximal risk factors and inform safety planning and interventions. Author Affiliation: (a) Faculty of Health/School of Psychology and Psychiatry, Witten/Herdecke University, Witten, Germany (b) Department of Psychiatry, University of Pittsburgh School of Medicine, USA (c) Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, USA (d) Department of Psychology, University of Pittsburgh, USA * Corresponding author. Faculty of Health/School of Psychology and Psychiatry, Witten/Herdecke University, Witten, Germany. Article History: Received 15 April 2021; Revised 11 November 2021; Accepted 27 November 2021 Byline: Aleksandra Kaurin [aleksandra.kaurin@uni-wh.de] (a,*), Alexandre Y. Dombrovski (b), Michael N. Hallquist (c), Aidan G.C. Wright (d)

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Gale Document Number: GALE|A692744298