# Intensive longitudinal study of suicidal behaviors and related health outcomes

> **NIH NIH U01** · HARVARD UNIVERSITY · 2022 · $169,000

## Abstract

PROJECT SUMMARY/ABSTRACT
Many leading causes of death have declined significantly over the past 100 years (e.g., tuberculosis,
pneumonia/influenza, gastritis); however, the suicide rate is virtually identical to what it was 100 years ago. Lack
of progress in the prevention of suicide is due in large part to the limited understanding of this problem. Suicidal
thoughts and behaviors (STBs), like other behavior problems (e.g., alcohol use, substance use, eating
disorders), rarely occur in the research lab where they can be carefully probed and cannot be ethically induced
in the lab. As a result, experts lack a firm understanding of the fundamental properties of STBs, and of how, why,
and when they unfold in nature. The purpose of this study is to address this enormous gap by using newly
developed smartphone and wearable biosensor technologies to conduct an intensive longitudinal study that will
advance the understanding and prediction of STBs and related behaviors. This study will monitor 600 people
(300 adults and 300 adolescents) at elevated risk of STBs (i.e., those presenting to a psychiatric hospital with
suicide ideation and/or a recent suicide attempt) during a high risk time period (i.e., post-hospitalization). The
first aim of this study is to identify digital phenotypes of STBs using data collected both actively/subjectively using
repeated smartphone surveys and passively/objectively using continuous data from smartphones (e.g., GPS,
accelerometer, communications data) and wearable biosensors (e.g., electrodermal activity, accelerometer).
The second aim is to map the dynamic trajectories of STBs over time. The third aim is to identify short-term
predictors of STBs during the 6 months post-hospital discharge. Ongoing research by the proposed team
demonstrates the feasibility of: recruiting and retaining the proposed samples, intensively monitoring them over
time using digital devices, and using analyses of these rich data streams to make discoveries about how STBs
and related behaviors unfold in nature. The data collected in this study will provide a rich data source that will be
used by our research team and collaborative researchers to advance the understanding, prediction, and ultimate
prevention of STBs and related outcomes.

## Key facts

- **NIH application ID:** 10629711
- **Project number:** 3U01MH116928-04S1
- **Recipient organization:** HARVARD UNIVERSITY
- **Principal Investigator:** MATTHEW K NOCK
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $169,000
- **Award type:** 3
- **Project period:** 2022-08-22 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10629711

## Citation

> US National Institutes of Health, RePORTER application 10629711, Intensive longitudinal study of suicidal behaviors and related health outcomes (3U01MH116928-04S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10629711. Licensed CC0.

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