Exploring U.S. Natural Disasters and Psychological Distress - From Time Series Trends to Machine Learning Insights on Hurricane Helene

Aug 6, 2026

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This research investigates historical trends in psychological distress in the United States and how they align with natural disaster occurrences. Using long-term datasets, the study examines relationships between disaster frequency and severity and changes in distress levels across U.S. history. Exploratory Data Analysis and time-series methods reveal temporal patterns, while real-time Reddit data on Hurricane Helene are scraped, labeled for sentiment, and used to train machine learning models to interpret emotional responses. Results support applications for crisis response planning and future analysis.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages48

Reading Time2 h 1 min

AccessFree to download

Abstract

Acronyms

List of Figures

Background

Relevant Climate-Mental Health Research

Existing Research and Gaps

Research Objectives

Focus: The Impact of Natural Disasters on Mental Health

Mental Health, Emotional Responses, and Psychological Disorders

Research Questions and Hypotheses

Research Question 1

Research Question 2

Methodology

Research Design

Data Collection from Public Sources

Data Preprocessing

Natural Disaster Dataset

Institute For Health Metrics and Evaluation (IHME) Dataset

National Survey on Drug Use and Health (NSDUH) Dataset

Reddit Dataset

Data Validation

Data Analysis Techniques

Exploratory Data Analysis

Natural Disasters

Frequency and Temporal Trends

Geographic Analysis

NSDUH Population

Years Lived with Disability (YLD)s (Global Burden of Disease (GBD) Study)

Relationships

Time-Series with Statistical Analysis

U.S. Natural Disaster Temporal Trends

Serious Psychological Distress (SPD) Temporal Trends (2004-2022)

Depression and Anxiety Induced YLDs Temporal Trends

Statistically Significant Findings

U.S. Natural Disaster Temporal Trends

SPD Temporal Trends (2004–2022)

Depression and Anxiety-Induced YLD Trends (1990–2021)

Correlations Between Variables

Sentiment Analysis

Tropical Storm and Hurricane Helene on Reddit

Building and Deploying a Reddit Web Scraper

API Setup

Subreddit Selection

Defining Keywords

Keyword Matching and Sentiment Classification

Data Storage

Combining and Cleaning the Data

Text Cleaning

Final Data Preparation

Applications and Benefits

Model Testing and Results

Linear Regression

Deep Learning (LSTM/GRU)

Transformer Models (BERT-based)

Model Selection and Final Approach

Visualizing Sentiments

Results

Support for Alternative Hypothesis (H1)

Potential for Future Analysis

Discussion

Claremont Colleges Scholarship @ Claremont | CMC Senior Theses | CMC Student Scholarship | | --- | --- | | 2024
Exploring U.S. Natural Disasters and Psychological Distress: From Time Series Trends to Machine Learning Insights on Hurricane Helene
Sarah Jane Fullerton
Follow this and additional works at: [https://scholarship.claremont.edu/cmc_theses](https://scholarship.claremont.edu/cmc_theses)
Part of the Data Science Commons | | Recommended Citation Fullerton, Sarah Jane, "Exploring U.S. Natural Disasters and Psychological Distress: From Time Series Trends to Machine Learning Insights on Hurricane Helene" (2024) . CMC Senior Theses. 3756. [https://scholarship.claremont.edu/cmc_theses/3756](https://scholarship.claremont.edu/cmc_theses/3756) This Open Access Senior Thesis is brought to you by Scholarship@Claremont. It has been accepted for inclusion in this collection by an authorized administrator. For more information, please contact [scholarship@claremont.edu](scholarship@claremont.edu). Claremont McKenna College Exploring U.S. Natural Disasters and Psychological Distress: From Time Series Trends to Machine Learning Insights on Hurricane Helene submitted to Professor Mark Huber by Sarah Jane Fullerton for Senior Thesis Fall 2024 December 1st, 2024 1 Abstract This research investigates the historical trends of psychological distress in the U.S. in relation to natural disaster occurrences. By analyzing long-term data, we examine how significant natural disasters relate to levels of psychological distress over time. The research employs Exploratory Data Analysis (EDA) and Time Series Analysis to identify patterns and trends between the frequency and intensity of natural disasters and the rise of psychological distress across various periods in U.S. history. Additionally, real-time data from Reddit was collected through a custom-built Reddit web scraper specialized for Hurricane Helene. This dataset was labeled for sentiment and used to train machine learning models for sentiment analysis, providing valuable tools for understanding emotional responses in real-time. Their adaptability makes them applicable for future use in crisis response. The findings of this research offer a dual perspective: understanding the broader historical relationship between natural disasters and psychological distress, and providing insights into emotional reactions to 2024 events. Contents 1 Abstract 1 2 Acronyms 4 3 List of Figures 5 4 Background 6 4.1 Relevant Climate-Mental Health Research .................. 6 4.1.1 Existing Research and Gaps ...................... 6 5 Research Objectives 8 5.1 Focus: The Impact of Natural Disasters on Mental Health ......... 8 5.2 Mental Health, Emotional Responses, and Psychological Disorders ... 8 5.3 Research Questions and Hypotheses ..................... 8 5.3.1 Research Question 1 .......................... 8 5.3.2 Research Question 2 .......................... 8 6 Methodology 9 6.1 Research Design ................................. 9 6.2 Data Collection from Public Sources ..................... 9 6.3 Data Preprocessing ............................... 10 6.3.1 Natural Disaster Dataset ........................ 10 6.3.2 Institute For Health Metrics and Evaluation (IHME) Dataset ... 10 6.3.3 National Survey on Drug Use and Health (NSDUH) Dataset ... 10 6.3.4 Reddit Dataset .............................. 11 6.4 Data Validation ................................. 11 6.5 Data Analysis Techniques ........................... 12 7 Exploratory Data Analysis 13 7.1 Natural Disasters ................................ 13 7.1.1 Frequency and Temporal Trends ................... 13 7.1.2 Geographic Analysis .......................... 17 7.2 NSDUH Population ............................... 19 7.3 Years Lived with Disability (YLD)s (Global Burden of Disease (GBD) Study) ....................................... 20 7.4 Relat

FAQs

How does the thesis connect natural disasters to psychological distress in the U.S.?

It analyzes historical patterns to examine how changes in disaster frequency and intensity relate to levels of psychological distress over time across different periods in U.S. history.

What datasets and methods are used to study these relationships?

The study uses Exploratory Data Analysis and time-series analysis, drawing on long-term public datasets for natural disasters and mental health indicators, supported by data validation and preprocessing steps.

How is Hurricane Helene-related Reddit data used in the research?

The thesis collects real-time Reddit data using a custom web scraper, labels the text for sentiment, and trains machine learning models to perform sentiment analysis and interpret emotional responses.

What are the practical implications of the findings?

The research provides both historical insight into the disaster–distress relationship and actionable tools for understanding emotional reactions to 2024 events, supporting future crisis response analysis.

Aug 6, 2026

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