The primary goal of our research is to understand why people engage in behaviors that are harmful to themselves and to translate the knowledge gained into better methods for assessing and treating harmful behaviors. Our research is multidisciplinary and we use a range of complementary methodological approaches (e.g., epidemiologic surveys, laboratory-based experiments, clinic-based studies, and real-time monitoring) to better understand how these behaviors develop, how to predict them, and how to prevent their occurrence.

Understanding the Nature of Suicidal Behavior

One of the greatest obstacles to studying suicidal behavior has been that although it is a leading cause of death, it occurs at a fairly low base-rate in the general population. As a result, very large samples of people are required to study suicidal behavior in a detailed way. Because virtually all prior studies have used small, selective samples (e.g., clinic patients)—mostly in Western countries— even the most basic characteristics of suicidal behavior have remained unknown. Understanding who is most at risk for suicide and how these behaviors develop is an essential first step in understanding the nature of this problem.

To overcome this long-standing challenge, we are studying the prevalence, characteristics, and risk & protective factors for suicidal behaviors (i.e., suicidal thoughts, plans, and attempts) in the largest, most representative study of suicidal behaviors ever conducted. This research is being carried out as part of the WHO World Mental Health Survey Initiative - a series of nationally representative surveys conducted in 28 countries around the globe. Our primary questions include: What is the prevalence of suicidal behaviors around the world? When do these behaviors typically begin? What factors increase the risk of suicidal behaviors? This study provides an unprecedented opportunity to learn about the nature of this leading cause of death. 

Sample publications:

Nock, M. K., Millner, A.J., Joiner, T. E., Gutierrez, P. M., Han, G., Hwang, I., King, A., Naifeh, J. A., Sampson, N.A., Zaslavsky, A. M., Stein, M. B., Ursano, R. J, & Kessler, R.C. (2018). Risk factors for the transition from suicide ideation to suicide attempt: Results from the Army study to assess risk and resilience in servicemembers (Army STARRS). Journal of Abnormal Psychology, 127, 139-49.

Nock, M.K., Han, G., Millner, A.J., Gutierrez, P.M., Joiner, T.J., Hwang, I., King, A., Naifeh, J.A., Sampson, N.A., Zaslavsky, A.M., Stein, M.B., Ursano, R.J., & Kessler, R.C. (2018). Patterns and predictors of persistence of suicide ideation: Results from the Army study to assess risk and resilience in servicemembers (Army STARRS). Journal of Abnormal Psychology, 127, 650-658.

Nock, M.K., Green, J.G., Hwang, I., McLaughlin, K.A., Sampson, N.A., Zaslavsky, A.M., & Kessler, R.C. (2013). Prevalence, correlates and treatment of lifetime suicidal behavior among adolescents: Results from the National Comorbidity Survey Replication – Adolescent Supplement (NCS-A). JAMA Psychiatry, 70, 300-310. (Paper)

Nock, M. K., Borges, G., & Ono, Y. (Eds.), (2012), Suicide: Global perspectives from the WHO World Mental Health Surveys. New York: Cambridge University Press. (Book)

Capturing the Real-Time Occurrence of Suicidal & Self-Injurious Behavior

Real Time Monitoring Figure

Another major and long-standing challenge to understanding self-harm is that because these behaviors are transient in nature and cannot be induced for study in the laboratory for ethical reasons, they have never been observed in a single research study! Obtaining data on the actual occurrence of a phenomenon is essential for understanding why it occurs, but has not previously been done in the case of suicidal/self-injurious behaviors. Toward this end, we are conducting studies using electronic diaries and ambulatory physiological monitoring methods to measure suicidal/self-injurious thoughts and behaviors as they naturally occur in real-time. In this work we also are examining the experience of other self-destructive behaviors, such as: bingeing/purging, alcohol/substance use, and risky sexual behaviors. This research is funded by the National Institute of Mental Health's U01 grant, the American Foundation for Suicide PreventionStar-Friedman Challenge for Promising Scientific ResearchThe Tommy Fuss Fund, S. Sydney DeYoung Foundation, the Chet and Will Griswold Suicide Prevention Fund, the Foundations of Human Behavior Initiative at Harvard University, and the For the Love of Travis Fund . Some of this work was described in an article by Nature, on an episode of PBS Newshour, and in the articles below.

Sample publications:

Bentley, K., Kleiman, E. M., Elliott, G., Huffman, J. C., & Nock, M. K. (2019). Real-time monitoring technology in single-case experimental design research: Opportunities and challenges. Behaviour Research and Therapy.

Coppersmith, D. D. L, Kleiman, E. M., Glenn, C. R., Millner, A. J., & Nock, M. K. (2018). The dynamics of social support among suicide attempters: A smartphone-based daily diary study. Behaviour Research and Therapy.

Kleiman, E. M., Turner, B. J., Fedor, S., Beale, E. E., Picard, R. W., Huffman, J. C., & Nock, M. K. (2018). Digital phenotyping of suicidal thoughts. Depression and Anxiety, 35, 601-608.

Understanding the Psychological Processes that Lead to Suicidal & Self-Injurious Behavior

ImageIn addition to describing the nature of and risk factors for suicidal/self-injurious behaviors, we are developing and testing theoretical models that explain why people intentionally hurt themselves, with a special focus on understanding the psychological factors that influence the development and maintenance of these behaviors. We test different aspects of our explanatory model in laboratory-based studies of factors that we believe work together to cause suicidal and self-injurious behaviors, including: high emotional/physiological reactivity to stressful life events, poor distress tolerance, and poor social problem-solving and decision-making skills. 

Sample publications:

Millner, A.J., den Ouden, H.E.M., Gershman, S.J., Glenn, C.R., Kearns, J., Bornstein, A.M., Marx, B.P., Keane, T.M., & Nock, M.K. (2019). Suicidal thoughts and behaviors are associated with an increased decision-making bias for active responses to escape aversive states. Journal of Abnormal Psychology.

Cha, C.B., O'Connor, R.C., Kirtley, O., Cleare, S., Wetherall, K., Eschle, S., Tezanos, K.M., & Nock, M.K. (2018). Testing mood-activated psychological markers for suicidal ideation. Journal of Abnormal Psychology, 127, 448-457.

Glenn, J.J., Werntz, A.J., Slama, S.J.K., Steinman, S.A., Teachman, B.A., & Nock, M.K. (2017). Suicide and self-injury-related implicit cognition: A large-scale examination and replication. Journal of Abnormal Psychology, 126, 199-211.

Developing New Methods of Measuring & Modifying Clinical Behavior Problems

We ultimately are interested in using what we learn to help individuals struggling with suicidal/self-injurious thoughts and behaviors. Therefore, we are conducting several projects aimed at developing new approaches to the measurement and modification of these problems. One example is our work conducted in local hospital emergency departments and inpatient units in which we are using performance-based cognitive tests developed in our laboratory to measure the cognitive state of people at risk for suicidal behavior. This work can help us to better understand the psychological state that leads to suicidal behavior and is expected to help us improve methods for detecting and predicting suicidal thoughts and behaviors in the future.

Sample publications:

Kleiman, E.M., Millner, A.J., Joyce, V.W., Nash, C.C., Buonopane, R.J., & Nock, M.K. (2019). Feasibility and acceptability of using weable physiological monitors with suicidal adolescent inpatients. JMIR mHealth and uHealth. [Epub ahead of print July 13].

Jaroszewski, A.C., Morris, R., & Nock, M.K. (2019). Randomized controlled trial of an online machine learning-driven risk assessment and intervention platform for increasing the use of crisis services. Journal of Consulting and Clinical Psychology, 87, 370-379. 

Cha, C. B., Augenstein, T. M.,  Frost, K. H., Gallagher, K. D'Angelo, E. J., & Nock, M. K. (2016). Using implicit and explicit measures to predict nonsuicidal self-injury among adolescent inpatients. Journal of the American Academy of Child and Adolescent Psychiatry, 55(1), 62-68.