# Network Psychiatry: Using Network Science to Advance Our Understanding of Post-Bereavement Psychopathology

> **NIH NIH K23** · MASSACHUSETTS GENERAL HOSPITAL · 2021 · $33,044

## Abstract

ABSTRACT
Bereavement is a potent and ubiquitous stressor. More than 10 million individuals experience the death a loved
one each year in the United States, increasing risk for numerous psychiatric disorders, including complicated
grief. Despite the substantial burden conferred by these disorders, we know little about their nature and etiology
and, consequently, are limited in our ability to predict, prevent, and treat post-bereavement psychopathology.
Recently, my colleagues and I proposed that bereavement-related mental disorders, such as complicated grief,
are best understood as complex systems of mutually reinforcing symptoms. In two studies, we used the tools of
network science to study the structure of the complicated grief symptom network. These studies allowed us to
identify which symptoms are most central to the complicated grief network and provided some of the earliest
evidence that understanding network topology can inform our understanding of the course of complicated grief.
My core aim for this career development award is to become an expert in network science and to use the
tools of network science to study complicated grief as a complex psychobiological system. The proposed
research study will build on our previous research through four critical innovations. First, we will use intensive
time-series data to estimate the intra-individual network structure for each patient, providing information about
the unique psychobiological processes operating within that individual. Second, we will focus our analyses on
the elements of the complicated grief syndrome that align with bereavement-related Research Domain Criteria
(RDoC) constructs, linking our analyses to the broader effort to understand these individual components of
psychopathology. Third, we will incorporate biological units of analysis into our intra-individual network and
study how individual differences in physiological reactivity contribute to the complicated grief syndrome.
Fourth, we will use intra-individual network parameters to predict the course of complicated grief over time.
The approach taken in this study is innovative because it adopts a novel conceptual framework for
understanding and studying psychiatric disorders that is rooted in the rapidly growing multi-disciplinary field of
network science. It is significant because it will elucidate the patient-specific psychobiological mechanisms
contributing to the development and onset of bereavement-related mental disorders. Moreover, it will introduce
new tools into the field of psychiatry that will allow us to better predict, prevent, and treat psychopathology at
the level of the individual patient, moving us closer to the aim of a precision medicine approach to psychiatry.

## Key facts

- **NIH application ID:** 10208641
- **Project number:** 5K23MH113805-04
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Donald John Robinaugh
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $33,044
- **Award type:** 5
- **Project period:** 2018-07-01 → 2021-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10208641

## Citation

> US National Institutes of Health, RePORTER application 10208641, Network Psychiatry: Using Network Science to Advance Our Understanding of Post-Bereavement Psychopathology (5K23MH113805-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10208641. Licensed CC0.

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