# Mathematical and computational modeling of suicidal thoughts and behaviors

> **NIH NIH F31** · HARVARD UNIVERSITY · 2022 · $32,814

## Abstract

Project Summary/Abstract
Suicide is a devastating public health concern. More than 40,000 people die by suicide in the US each year,
making it the 10th leading cause of death and responsible for >$30 billion in lost productivity and medical costs.
Unfortunately, whereas scientific advances have led to significant declines in other leading causes of death
(e.g., pneumonia, tuberculosis) over the past century, the current suicide rate is nearly identical to the early
1900s. In order to improve prediction and prevention of suicide, a better mechanistic understanding of risk and
protective processes underlying suicidal thoughts and behaviors is needed. Computational psychiatry holds
such promise for advancing suicide research, particularly through building and testing formal theories.
Although many influential suicide theories have existed for decades, these have all been instantiated verbally,
which renders them underspecified by nature (due to the inherent imprecision of language). On the other hand,
using tools from computational psychiatry, formal theories are instantiated in mathematical equations and
computer code. This requires more specificity and precision of the exact strength, form, and time scale of
theorized effects. Indeed, formal theories have led to significant advances and breakthroughs in other scientific
fields concerned with the understanding and prediction of complex systems (e.g., ecosystems, climate). Thus,
the proposed project aims to address this major gap in suicide research by using mathematical and
computational modeling to build, evaluate, and test a formal theory of suicide. The candidate and mentorship
team, including leading experts in suicide and computational modeling of complex dynamic systems, have
developed a preliminary theory of suicidal thoughts and behaviors encompassing cognitive, affective,
behavioral, and social factors. Aim 1 of the project is to formalize each of these associations using differential
equations (a family of mathematical models that specify the relationship between functions and their
derivatives and are extremely useful for modeling change in complex systems over time). Aim 2 is to transform
these mathematical equations into computer code to simulate artificial data, allowing for direct observation of
the behavior implied by the theory. This step will allow for an evaluation of whether the theory is able to
produce fundamental, known phenomena about suicidal thoughts and behaviors. Finally, Aim 3 will leverage
data from an ongoing NIMH-funded intensive longitudinal study of suicidal thoughts and behaviors (N = 300) to
evaluate the theory-based simulated artificial data against empirical data collected in real-time. The proposed
study’s greatest potential impacts are to develop and evaluate the first formal theory of suicidal thoughts and
behaviors using mathematical and computational modeling, as well as to promote a program of research
uniting the two major NIMH priorities of suicide prev...

## Key facts

- **NIH application ID:** 10437592
- **Project number:** 5F31MH125495-02
- **Recipient organization:** HARVARD UNIVERSITY
- **Principal Investigator:** Shirley B Wang
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $32,814
- **Award type:** 5
- **Project period:** 2021-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10437592

## Citation

> US National Institutes of Health, RePORTER application 10437592, Mathematical and computational modeling of suicidal thoughts and behaviors (5F31MH125495-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10437592. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*