The three-step theory of suicide (3ST) proposes that suicidal ideation (SI) and behavior develops in the context of unbearable pain and hopelessness (Step 1), low social connection (Step 2) and acquired capability (Step 3 - not assessed in this study; Klonsky et al., 2016). Distress disclosure is one way a person may utilize their social network to mitigate feelings of distress and can be a critical measure of social connectedness. Building on efforts to diversify measurement of social connectedness in the 3ST, a sample of 549 college students (mean age = 19.27, SD = 1.28; 56.6% reporting history of SI) completed measures of physical and psychological pain (Patient Health Questionnaire – Revised; Unbearable Psychache Scale-3), hopelessness (State Hopelessness Scale; Beck Hopelessness Scale-4), social connectedness (Interpersonal Needs Questionnaire; Social Connectedness Scale – Revised; Distress Disclosure Index), and suicidal ideation (Depression Severity Index; Suicide Cognitions Scale – Shortened). Structural equation modeling was used to evaluate steps one and two of the 3ST and the utility of incorporating distress disclosure into this framework. In line with the 3ST, the structural model including pain, hopelessness, and social connectedness was supported and the direct effects of these variables on SI was significant (p < .05). In contrast to the 3ST, the interaction between pain and hopelessness did not predict SI (p = .385), nor was the moderating role of social connectedness supported (p = .133). Although distress disclosure was a significant indicator of social connectedness (p = .001), this variable did not contribute additional variance over other measures of connectedness. The results provide partial support for core features of the 3ST, however further research is needed to verify the theoretical assumptions of Step 2. Additionally, although disclosure is associated with SI, it may not be a critical measure of social connectedness when considered alongside traditional measures.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1393 |
| Date | 01 January 2024 |
| Creators | Ruiz, Jessica A |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Thesis and Dissertation 2023-2024 |
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