# Moving beyond the Pain-Suicidality Link: An Investigation of Fluctuations in Social Threat and Neural Response to Social Threat in Momentary Pain and Proximal Risk for Suicidal Ideation in Adolescence

> **NIH NIH R01** · RESEARCH TRIANGLE INSTITUTE · 2024 · $783,370

## Abstract

PROJECT SUMMARY/ABSTRACT
Suicide rates are the second leading cause of death in adolescence. Suicidal ideation (SI) typically develops
in adolescence. The onset of SI is a developmental inflection point associated with pathways toward
persistent and worsening SI and other self-injurious thoughts and behaviors. SI is also associated with
significant health care costs, morbidity, and risk for mortality. Rates of physical pain increase in adolescence
alongside the developmental increase in suicide risk. The presence of physical pain is associated with a 2- to
3-fold increase in SI risk, prompting several major organizations (e.g., World Health Organization, American
Psychiatric Association, and American Foundation for Suicide Prevention) to highlight physical pain
conditions as a serious risk factor for suicide in adults and children ages 10 years and older. Multiple suicide
theories posit that suicidal thoughts and behaviors arise from the desire to escape unbearable pain, including
physical pain. However, research on the pain–suicidality link has heavily relied on cross-sectional studies
focusing on pain diagnoses (e.g., chronic pain) as a single risk factor. Yet, most individuals with a pain
diagnosis do not have SI. There is a need for longitudinal studies investigating how multiple risk factors work
together to influence SI. There is also a need to identify proximal risk for SI (e.g., over hours) given that SI
often fluctuates rapidly over short periods. We will move beyond the pain–suicidality link by investigating
factors that may influence dynamic changes in physical pain and proximal risk for SI among adolescents. We
will investigate the effects of short-term effect of social threat (threat to social status or relationships)
and individual differences in neural response to social threat on momentary increases in physical pain and
proximal risk for SI. We focus on social threat because this is an especially developmentally salient type of
threat in adolescence and has been shown to influence pain. Social threat, like physical threat, also activates
pain-related brain regions involved in a “neural alarm system” to warn against danger. Social threat is also a
robust longitudinal predictor of SI in adolescence. To address major gaps in knowledge of the role of social
threat in the pain–suicidality link, we will test components of an overarching model positing that exposure to
social threat predicts momentary increases in pain (particularly pain unpleasantness). Pain in turn is
a proximal predictor of SI. Heightened neural activation in pain-related brain regions to social threat
amplifies pain and risk for SI in the moments when social threat occurs. We will conduct a longitudinal
study of 200 youth ages 14–17 with recurrent musculoskeletal pain in limbs, back, or neck, which is common
in adolescents and associated with suicide risk. We will recruit youth with a range of pain severity, but will
oversample for high levels of pain to enrich for r...

## Key facts

- **NIH application ID:** 10878701
- **Project number:** 5R01MH132602-02
- **Recipient organization:** RESEARCH TRIANGLE INSTITUTE
- **Principal Investigator:** Caroline Oppenheimer
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $783,370
- **Award type:** 5
- **Project period:** 2023-07-01 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10878701

## Citation

> US National Institutes of Health, RePORTER application 10878701, Moving beyond the Pain-Suicidality Link: An Investigation of Fluctuations in Social Threat and Neural Response to Social Threat in Momentary Pain and Proximal Risk for Suicidal Ideation in Adolescence (5R01MH132602-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10878701. Licensed CC0.

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