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Examining contemporaneous and temporal associations of real-time suicidal ideation using network analysis.
- Source :
-
Psychological Medicine . Sep2024, Vol. 54 Issue 12, p1-9. 9p. - Publication Year :
- 2024
-
Abstract
- Background Suicidal ideation arises from a complex interplay of multiple interacting risk factors over time. Recently, ecological momentary assessment (EMA) has increased our understanding of factors associated with real-time suicidal ideation, as well as those predicting ideation at the level of hours and days. Here we used statistical network methods to investigate which cognitive-affective risk and protective factors are associated with the temporal dynamics of suicidal ideation. Methods The SAFE study is a longitudinal cohort study of 82 participants with current suicidal ideation who completed 4×/day EMA over 21 days. We modeled contemporaneous (t) and temporal (t + 1) associations of three suicidal ideation components (passive ideation, active ideation, and acquired capability) and their predictors (positive and negative affect, anxiety, hopelessness, loneliness, burdensomeness, and optimism) using multilevel vector auto-regression models. Results Contemporaneously, passive suicidal ideation was positively associated with sadness, hopelessness, loneliness, and burdensomeness, and negatively with happiness, calmness, and optimism; active suicidal ideation was positively associated with passive suicidal ideation, sadness, and shame; and acquired capability only with passive and active suicidal ideation. Acquired capability and hopelessness positively predicted passive ideation at t + 1, which in turn predicted active ideation; acquired capability was positively predicted at t + 1 by shame, and negatively by burdensomeness. Conclusions Our findings show that systematic real-time associations exist between suicidal ideation and its predictors, and that different factors may uniquely influence distinct components of ideation. These factors may represent important targets for safety planning and risk detection. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00332917
- Volume :
- 54
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Psychological Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 181064964
- Full Text :
- https://doi.org/10.1017/S003329172400151X