Suicide is a leading cause of death worldwide, accounting for nearly 800,000 deaths each year.1,2
Suicide rates continue to increase in the U.S.3 Most research on suicide risk factors has identified static,
dispositional factors.4 These data inform us about groups at actuarial risk, but do very little to predict with useful
precision when people will have suicidal thoughts or act on suicide thoughts. Thus, there is an urgent need to
identify proximal risk factors for suicide risk.
Two of the leading factors distally associated with increased suicide risk are dysfunctional emotional
responses5 and decision-making deficits.6 Suicidal individuals have poorer reinforcement learning,6,7
demonstrating impaired ability to learn and modify behavior in response to reward and punishment. Individuals
at high risk for suicide (i.e., borderline personality disorder) also show difficulties learning from punishment and
reward,8,9 and the PI’s data show that negative emotions uniquely impair learning in such high-risk populations
relative to healthy and clinical controls.10 It is necessary to understand the interactive effects of emotion and
reinforcement learning as factors elevating near-term risk for suicidal thoughts and behaviors.
Therefore, the proposed study examines both emotional and cognitive processes associated with suicidal
thoughts and behaviors among 170 patients with a range of suicidal risk recently treated in an emergency
department for a suicidal crisis. Using innovative ecological momentary assessment methods (EMA), the
proposed study will examine behavioral measures of reinforcement learning and both physiological and
subjective measures of momentary emotions. Aim 1 identifies the main and interactive effects of emotional
responses, reinforcement learning, and emotion-related decrements in learning on recent suicidal thoughts and
behaviors among suicidal patients recently seen in the emergency department. Aim 2 examines how emotions
and learning interact to predict momentary suicidal thoughts and behaviors over four weeks. Aim 3 tests emotion-
related decrements in learning as prospective predictors of future suicide risk over a six-month follow-up.
The research team (PI: Dixon-Gordon, Co-Is: Ammerman, Boudreaux, Rathlev; Consultants: Hackel;
Collaborator: Laws) has access to world-class expertise, with extensive experience recruiting suicidal
participants from medical settings, EMA, computational modeling, and experimental psychopathology.
The most important challenge facing suicide prevention today is unraveling the complex emotional and
cognitive proximal drivers that transform nascent suicide risk into action. Combining state-of-the-art behavioral
measures and EMA, we will tease apart the complex longitudinal relations between dysfunctional emotional
responses, reduced capacity to learn from reward and punishment, and fluctuations in suicidal thoughts and
behaviors. Given the high societal costs of suicide, this work has important health significance. Findings will
inform the development of treatments that target emotion dysfunction and learning in samples at-risk for suicide.