Do homelessness prevention programs prevent homelessness? Evidence from a randomized controlled trial

Last registered on September 20, 2021

Pre-Trial

Trial Information

General Information

Title
Do homelessness prevention programs prevent homelessness? Evidence from a randomized controlled trial
RCT ID
AEARCTR-0008261
Initial registration date
September 20, 2021
Last updated
September 20, 2021, 6:23 PM EDT

Locations

Region

Primary Investigator

Affiliation
University of Notre Dame

Other Primary Investigator(s)

PI Affiliation
University of Notre Dame

Additional Trial Information

Status
Completed
Start date
2019-07-01
End date
2021-06-01
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
This project studies how providing one-time financial assistance affects housing stability. Among people who are housed, at imminent risk of homelessness, and ineligible for other similar programs in Santa Clara County, California, we randomly assign some marginal clients to receive assistance. As an outcome, we track use of homelessness services as observed in the county's Homelessness Management Information System.
External Link(s)

Registration Citation

Citation
Phillips, David and James Sullivan. 2021. "Do homelessness prevention programs prevent homelessness? Evidence from a randomized controlled trial." AEA RCT Registry. September 20. https://doi.org/10.1257/rct.8261-1.0
Experimental Details

Interventions

Intervention(s)
The treatment group receives one-time emergency financial assistance, mostly as back rent paid to landlords. Typical amounts range 1-2 months of rent.
Intervention Start Date
2019-07-01
Intervention End Date
2020-12-31

Primary Outcomes

Primary Outcomes (end points)
Homeless program use
Primary Outcomes (explanation)
We will rely on administrative records for outcome measures. The research team will only receive de-identified data from an existing administrative data source. The Homeless Management Information System collects client-level data from all publicly contracted homeless service providers in Santa Clara County. From this information system, we can observe date-specific service records to track outcomes for both treatment and control group participants. Among other variables, HMIS data will allow us to observe vulnerability assessment scores and entry into emergency shelters or transitional housing. We have a signed service agreement with Santa Clara County specifying the outcomes we will track for study participants.

Secondary Outcomes

Secondary Outcomes (end points)
Address changed
Secondary Outcomes (explanation)
We measure address changes using address histories from consumer reference data.

Experimental Design

Experimental Design
In the status quo without the study, clients visit participating non-profit service providers seeking help to prevent imminent homelessness. Clients meet with a case manager and participate in an eligibility screening which the county is already implementing. Clients scoring above 13 would be automatically eligible for financial assistance. Clients scoring below 8 will not be considered eligible for financial assistance. For clients scoring 8-13 there is a monthly quota of funds available. Clients scoring in that range would get funds on a first-come first-served basis until funds are exhausted for the month.

Participants for the study will be recruited from this process. With the study, the only change in services is that clients with an eligibility score 8-13 will be entered into a lottery rather treated first-come-first-served. The case manager will briefly explain the purpose of the study and the way the lottery works to randomly determine whether or not someone can get access to emergency financial assistance. Participants will be entered into a lottery through a web-based form design on SurveyCTO. The form will be programmed to consider pre-specified funding quotas for each participating agency that match the quotas that would have been implemented for first-come, first-served. When the agency puts in the information for the last person in the quota, the form will tell them not only the result for that person but also the fact that this is the last person for the month. After that point, people scoring 8-13 are turned away for the rest of the month at that agency, which is identical to the status quo.

All clients already sign a release of information; the study would slightly modify that form to acknowledge the introduction of the lottery. Following the lottery, study participants will not be contacted again in the context of the research study. We will rely on administrative records for outcome measures. The research team will only receive de-identified data from an existing administrative data source. The Homeless Management Information System collects client-level data from all publicly contracted homeless service providers in Santa Clara County. From this information system, we can observe date-specific service records to track outcomes for both treatment and control group participants. Among other variables, HMIS data will allow us to observe vulnerability assessment scores and entry into emergency shelters or transitional housing. We have a signed service agreement with Santa Clara County specifying the outcomes we will track for study participants.

The only new elements introduced by the study are (a.) analysis of existing de-identified data and (b.) replacing existing firstcome- first-served rationing with a lottery. All other elements of service provision, including use of a risk scoring tool and rationing of homelessness prevention funds, will exist regardless of the evaluation.

Those clients assigned to the control group and any who do not wish to participate in the study but are otherwise eligible for other social services outside of homelessness prevention funding, will be provided usual care. Study participants not offered homelessness prevention services, are given information about other ways to find housing in Santa Clara County. They have about the same chances of securing housing as other people who are at risk of homelessness in Santa Clara County and who are not in the study. If a client decides not to join the study, this decision will not affect the client’s chances of getting housing in other ways, but the client will not have the chance to be offered homelessness prevention services through Destination:Home.
Experimental Design Details
Randomization Method
Random number via SurveyCTO
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Ex-ante unknown, dependent on demand. Ex-post 1,263 individuals.
Sample size: planned number of observations
Ex-ante unknown, dependent on demand. Ex-post 1,263 individuals.
Sample size (or number of clusters) by treatment arms
Ex-ante unknown, dependent on demand. Ex-post, 749 control, 514 treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
An MDE of 0.03 from a baseline HMIS program use rate of 0.04 in the control group.
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Notre Dame IRB
IRB Approval Date
2019-06-20
IRB Approval Number
18-08-4776
Analysis Plan

Analysis Plan Documents

scc_hp_analysis_plan.pdf

MD5: 39df0bfed550e4a13e9c62f3765eb7c1

SHA1: 01de8b4421472be6847b114f5b88857567b59992

Uploaded At: September 20, 2021

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials