# Intensive longitudinal study of suicidal behaviors and related health outcomes

> **NIH NIH U01** · HARVARD UNIVERSITY · 2020 · $501,356

## 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:** 10156794
- **Project number:** 3U01MH116928-03S1
- **Recipient organization:** HARVARD UNIVERSITY
- **Principal Investigator:** MATTHEW K NOCK
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $501,356
- **Award type:** 3
- **Project period:** 2018-09-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10156794

## Citation

> US National Institutes of Health, RePORTER application 10156794, Intensive longitudinal study of suicidal behaviors and related health outcomes (3U01MH116928-03S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10156794. Licensed CC0.

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