1.1. Homelessness in the United States
1.2. Methodological Approaches to Studying Homelessness in the United States
1.3. Recent Advances in Data Science Approaches to Studying Social Issues
1.4. Moving beyond Descriptive Studies of Homelessness
2. Materials and Methods
2.1. Study Sample
2.2. Cluster Analysis
2.3. K-Means Cluster Analysis
2.4. Factors Introduced to the K-Means Model
2.5. Decision Tree Analysis
3.1. K-Means Cluster Analysis
3.2. Decision Tree Analysis
- If a client had a hardship indicator in the area of utilities AND demonstrated a mean hardship indicator score of two, meaning they had two other hardships while also facing an inability to pay their utility bills, the probability of becoming homeless in the future increased to a statistically significant level.
- If a client had a hardship indicator in the area of utilities AND demonstrated a mean hardship indicator score of more than two, meaning they had more than two other hardships while also facing an inability to pay their utility bills, the probability of becoming homeless in the future was highly statistically significant.
- The final pathway to homelessness occurred if a housed client was over 50 years old, male, disabled, and/or not in the workforce AND had ANY medical financial hardship and more than two other hardships at the same time. Respondents with these characteristics were highly statistically significantly more at risk of becoming homeless.
5.1. Collective Impact Regional Data Hubs, like 2-1-1 San Diego’s CIE, Offer New Sources for High-Quality Quantitative Data on the Homeless Population, That Could Be Used to Replicate Study Findings and Expand Research of the Homeless Population in Other Geographies
5.2. Current Calculations of the Federal Poverty Level Do Not Include Regional Cost of Living and Inflation Adjustments, Potentially Leading to Higher Rates of Homeless Recidivism in Certain Geographies. Replicating Study Findings in Other Geographies Could Help Validate This Hypothesis
5.3. Measuring Social Determinants of Health Hardship Indicators When One Accesses Social Services Provides Additional Information to Further Assess Overall Risk across Complex Social Experiences, like the Experience of Homelessness
5.4. Having a Utility Hardship Indicator at Any Level and Two or More Other Social Determinants of Health Hardships That Co-Occur at the Same Time Create a Statistically Significant Probability of an Impending Homeless Event
5.5. A Health Medical Hardship Indicator at Any Level and More Than Two Other Hardships That Co-Occur Create a Highly Statistically Significant Probability of an Impending Homeless Event for Men Who Are Not Working and 50 or Older
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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|Housing||Gender Identity||Race and Ethnicity|
|Homeless||Male||Female||White||African American||Asian||Hispanic||Native American||Other||Pac.Islander||Multi|
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