A temporal network analysis of risk factors for suicide : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Clinical Psychology at Massey University, Manawatū, New Zealand
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Date
2024-03-19
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Massey University
Figures 3 & 4 are reused with permission.
Figures 3 & 4 are reused with permission.
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Abstract
Suicide is a major public health concern in New Zealand, with the number of lives lost due to suicide increasing almost every year. The factors influencing a person’s decision to take their own life are numerous and often complex. Some of these factors are dynamic, fluctuating over short periods of time and ultimately altering a person’s risk for suicide. Network analysis is a novel statistical technique that can be used to explore complex causal associations in systems of variables, such as risk factors for suicide. The present study used temporal network analysis to explore the associations between dynamic risk factors for suicide over time. Data collection involved ecological momentary assessment, where a general community sample of 39 adult participants completed a brief survey five times per day for ten days, resulting in 1420 completed surveys. Each survey assessed participants’ momentary experience of suicidal ideation, depressed mood, hopelessness, social support, self-esteem, thwarted belongingness, perceived burdensomeness, anhedonia, worthlessness, alcohol intoxication, and fatigue. All variables fluctuated from measurement to measurement at least some of the time, highlighting the dynamic nature of suicide risk. Temporal, contemporaneous, and between-persons networks of the 11 measured variables were estimated using temporal network analysis. In the temporal network, hopelessness was the only variable that predicted an increase in suicidal ideation at the subsequent measurement. Multiple nodes were estimated to be positively associated with suicidal ideation in the contemporaneous network, including depressed mood, thwarted belongingness, perceived burdensomeness, and worthlessness, while self-esteem was negatively associated with suicidal ideation in this network. In the between-persons network, hopelessness was the only variable with a significant association with suicidal ideation. The results of this study highlight the importance of continuously assessing changes in suicide risk factors given their dynamic nature. Hopelessness may be an especially important risk factor to assess given its temporal association with increased suicidal ideation. Regarding future research opportunities, experimental N=1 network studies about the effectiveness of personalised interventions based on node centrality are an important next step in determining whether individualised networks have a place in personalised treatment for suicidality.
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Keywords
Suicide, Risk factors, Risk assessment, New Zealand, Social sciences, Network analysis, temporal network analysis, ecological momentary asssessment