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Suicide and Self-Injury

Latent profile analysis of urges for suicidal and self-harming behavior: The role of social support instability

(PS2-A24) Latent Profile Analysis of Urges for Suicidal and Self-harming Behavior: The Role of Social Support Instability

Friday, November 18, 2022

10:30 AM – 11:30 AM EST

Location: Westside Ballroom, 5th Floor

Author(s)

Joseph S. Maimone, B.A.

Senior Clinical Research Coordinator
Massachusetts General Hospital
Dorchester, Massachusetts

Co-Author(s)

Allison K. Ruork, Ph.D.

Postdoctoral Associate
Rutgers University
Piscataway, New Jersey
KB

Kate Bentley, Ph.D.

Assistant Professor
Massachusetts General Hospital
Boston, Massachusetts
EK

Evan Kleiman, Ph.D.

Assistant Professor
Rutgers University
Piscataway, New Jersey

Suicide rates in the past 20 years have steadily increased in the United States despite over 50 years of research dedicated to the subject, clearly demonstrating a need for novel approaches to understanding and treating it. Given the prominent role that social functioning holds in prevailing theories of suicide, one potential avenue is in deepening our understanding of social factors and their relationship to suicide, where there has been little empirical evaluation to date. Moreover, ambulatory assessment methods demonstrate promise for understanding how suicide risk unfolds in daily life and are well-suited to capture nuanced aspects of interpersonal functioning in an individual’s natural environment. As a result, this study used data from an eight-week ecological momentary assessment (EMA) protocol to explore whether day-to-day perceptions of social support could inform unique understanding of risk for self-injurious thoughts and behaviors (SITBs), operationalized as urges (a) to die by suicide and (b) engage in non-suicidal self-injury (NSSI). These outcomes were used as a proxy for suicide risk in this study given their well-documented role as prominent risk factors for this life-threatening outcome. Latent profile analysis (LPA) was used in a sample of undergraduates (n = 371) to identify groups of individuals based on their perceptions of social support. The indicators for the LPA were a set of participant-level features of daily measures of support and momentary measures of rejection (e.g., mean; root mean square of successive differences [RMSSD] as a measure of instability from one timepoint to the next). The best fitting LPA had three profiles: high average support + low instability (Profile 1; n = 159; 42.9% of the sample), medium average support + low instability (Profile 2; n = 172; 46.4% of the sample), and low average support + high instability (Profile 3; n = 40; 10.8% of the sample). We examined whether the profiles differed in momentary ratings of and person-level variability in urges to (a) die by suicide and (b) engage in NSSI. Results of contrast-coded multi-level modeling showed that profile 1 and 3 had significantly higher momentary ratings of urges to die by suicide and engage in NSSI (p < .001). One-way ANOVAs indicated that all three profiles significantly differed in RMSSD in urges to die by suicide and engage in NSSI in the same manner (3 > 2 > 1, all ps < .001). These findings suggest that the combination of low average perceived support along with high instability (greater day-to-day fluctuations in perceived support) leave individuals more vulnerable to SITBs. The findings from this study may contribute greater understanding to how an individual internally represents their support network and how it changes over short time spans. Understanding this, especially in a sample of those experiencing suicidal thoughts and behaviors, may inform specific understanding of the ways that an individual’s social support breaks down or bolsters their mental health. To our knowledge, this is the first study to examine how patterns of real-time social support form subgroups and evaluate how those subgroups map onto self-injurious outcomes.