# Predicting populations at-risk of developing pathological hoarding

> **NIH NIH R01** · UNIVERSITY OF FLORIDA · 2021 · $68,363

## Abstract

ABSTRACT
Hoarding Disorder (HD), recognized as an independent illness in the Diagnostic and Statistical Manual of
Mental Disorders for less than a decade, is a debilitating psychiatric disorder with profound socioeconomic
impacts. Emerging data shows that hoarding severity correlates with substantial medical burden. Prevalence of
clinically significant hoarding behavior is estimated to be between 2 and 4%, with a higher burden in the older
population. However, it is believed that hoarding disorder is underdiagnosed. The parent R01MH117114
combines in-person clinical, neuropsychological, and medical frailty assessments with a unique epidemiologic
resource, the online Brain Health Registry (BHR)
17, to assess the extent of disability in older adults suffering with
hoarding symptoms. To date, over 24,000 subjects have taken hoarding-related questionnaires. In addition, 1554
participants have completed additional surveys performed for validation of hoarding symptoms. Moreover, the
BHR includes longitudinal objective and subjective measures of cognition, as well as childhood and medical
history. We will classify longitudinal trends of measures of hoarding symptomatology in a subpopulation of the
BHR with clinical assessments of hoarding disorders and other psychopathologies. We will then project the whole
BHR population to classify longitudinal trends. We will then apply statistical inference and techniques from
artificial intelligence to identify predictors of various trends of hoarding symptomatology to find predictors of
developing severe hoarding symptoms. Ongoing recruitment through the parent R01 will allow for validation of
the predictions made through this work. Moreover, as there is a rapid increase in the number of psychiatric
studies using web-based data collection methods rather than in-person clinical assessments, the importance of
studying the temporal trends and fidelity of these data collection methods extends beyond the scope of the
current study. The present study will provide a proof-of-concept approach for analyzing such data.
 The work will be carried out by a trained mathematician transitioning into systems medicine whose career
goal is to establish an independent career in the field of computational psychiatry. The training provided through
this grant will prepare the supplement candidate to submit an independent K01 award on the interactions
between late life depression and hoarding disorder to the National Institute of Mental Health. This will be done
by providing tailored mentoring by experts in hoarding disorder and systems medicine, access to unique datasets
related to various psychopathologies, structured training in grant writing and responsible conduct in research, a
structured course in psychopathology, and premier computational resources at the University of Florida.

## Key facts

- **NIH application ID:** 10253596
- **Project number:** 3R01MH117114-03S2
- **Recipient organization:** UNIVERSITY OF FLORIDA
- **Principal Investigator:** Robert Scott Mackin
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $68,363
- **Award type:** 3
- **Project period:** 2020-12-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10253596

## Citation

> US National Institutes of Health, RePORTER application 10253596, Predicting populations at-risk of developing pathological hoarding (3R01MH117114-03S2). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10253596. Licensed CC0.

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