Characteristics and Dynamics of Homeless Families with Children. Resource Allocation Typology


Definition and Guidance from Past Research. A second typology, focused on families who have already become homeless, would classify families by the factors that block their ability to exit homelessness (e.g., poor credit; past justice involvement), as well as challenges they may have to maintain stability and self-sufficiency. Some families exit shelters and emergency housing quickly (within a month or less), while others stay for relatively longer periods of time, depending on the system. Some families experience repeated episodes of homelessness.

Although past research has indicated that housing subsidies are a major predictor of successful, stable exits, it is clear that there are not enough subsidies to meet the needs of all families that are homeless. In addition, some families may need less than a subsidy to exit homelessness and others may need additional supports. For example, domestic violence victims may be able to afford housing but other barriers preclude their ability to access safe housing. In addition, research has indicated that some families do still return to homelessness, despite having had a subsidy in the past. Therefore, it is important to understand the factors that help families exit homelessness quickly, as well as the contextual and personal barriers that block families from exiting homelessness. This understanding could help classify families who need minimal resources to exit and those that need additional assistance. In particular, as Dr. Jill Khadduri emphasized in her paper (see Appendix C), it is important that a typology differentiate between families who need permanent mainstream housing and those who need permanent supportive housing.

A resource allocation typology could also further classify families by the other needs they have that may block their ability to achieve other favorable outcomes. For example, homeless families, even after obtaining housing, have a greater probability of experiencing child separations than nonhomeless families. A resource allocation typology may identify families having needs for family preservation and/or reunification, as well as families that have other needs for their children. In addition, research currently in press indicates that a group of homeless families with psychiatric and/or substance use conditions show less improvement over time in other outcome areas because of ongoing conflict and trauma. Identifying those needs and strategies for dealing with them may be important in typology development. Finally, social capital outcomes, such as education and employment, may be critical targets for a typology. Research in progress with the SAMHSA Homeless Families Program suggests that employment correlates with improvements in other outcome areas, so strategies for helping homeless women secure and maintain employment could be a priority area for resources. Developing a typology, therefore, that identifies the family support needs, broad health needs (including mental health and substance use), and social capital needs of a family, as well as specific housing needs, may be important to helping families obtain and maintain stable housing. Adding the needs of children into this mix, rather than creating a separate typology for children, also was the consensus of the Expert Panel. This approach is further supported by the synthesis of findings on homeless children provided by Dr. John Buckner (see Chapter 3 and Appendix A for a complete copy of his paper).

As noted earlier, having a typology that incorporates environmental variables is important, especially given the role that context plays in homelessness. Drs. Reingold and Fertig's contribution in this volume (Appendix D) suggests that, of the contextual variables they were able to examine in the Fragile Families data base, high unemployment rates and high fair market rents were associated with higher risks of becoming homeless. Shelter availability and the existence of anti-loitering laws also were associated with homelessness, but admittedly were likely to be acting as community indicators of high levels of homelessness and not necessarily elements that contribute toward an increase or decrease in the probability of homelessness.

Short-Term Study Options. As with the development of the prevention typology, a staged approach to informing the resource allocation typology can be envisioned. One of the most expedient strategies for providing data on families living in shelters and their exit patterns would involve an analysis of the HMIS data sets. As noted earlier, in 2001, Congress directed HUD to provide more detailed information on the extent and nature of homelessness and on the effectiveness of programs funded by the McKinney-Vento Act. As a result of this mandate, HUD is requiring each local CoC to develop its own HMIS, a computerized data collection system on homeless individuals and families. By requiring programs and communities to collect demographic, service, and outcome data using standardized data elements, the HMIS system provides a unique opportunity to examine homeless families across programs, providers, and communities.

With data on the types of services homeless families use and how these services relate to outcomes, such as the length of time families are homeless, whether they stay out of the homeless system once they leave, and how many exit to more stable housing arrangements, the HMIS data can help allocate appropriate resources to appropriate services. Knowing which families benefit from the various types of services also can inform the development of better treatment matching efforts (e.g., matching families to the appropriate level and intensity of services required).

Longer-term Study Options. As with the prevention typology, adding questions on homelessness to the American Community Survey would provide the opportunity to look at homelessness in specific geographic areas and examine how the community and contextual variables relate to changes in the incidence and prevalence of homelessness over time. This procedure would use the community itself as the unit of analysis, rather than the individual family and, given the vastness of the data set, should provide key guidance on whether communities that implement different types of interventions and service efforts affect homelessness for families with different constellations of needs. These efforts could also be examined in tandem with variables such as changes in the housing market and other contextual factors.

As noted above, adding questions to the NLSY97 sample would not only help identify factors that lead to people becoming homeless but, over time, could also help to identify the factors that help predict exits out of homelessness. These data collected over time should provide the ability to look at different exit trajectories for families and determine the service variables and other factors that help to predict an exit for different classifications of families.

A related data set, The National Longitudinal Survey of Youth 1979 (NLSY79), described in Chapter 4, is a series of surveys with a nationally representative sample of 12,686 young men and women who were between the ages of 14 and 22 in 1979. Annual interviews were conducted from 1979 until 1994; since then, respondents have been interviewed every other year (1996, 1998, etc.). A major challenge with the NLSY79 cohort is that the primary respondents are now 40 years of age or older and may be too old to provide a good opportunity to examine homelessness among families. The sample does include a subsample of children born to initial study participants whose ages would make them more likely to be currently experiencing homelessness. Adding questions to the NLSY79 sample about their history of homelessness, as well as to the NLSY79 Children and Young Adult surveys about both their history and current incidence of homelessness, would, therefore, provide a rare opportunity to examine the intergenerational effects and impact of homelessness. However, the smaller sample size of the children's sample (only children born to women in the NLSY79 sample are surveyed) makes this a less promising approach than examining the NLYS79.

Finally, a national longitudinal study of exit patterns and shelter requests of homeless families could answer questions about the exit patterns that families have, the individual and contextual factors that facilitate and inhibit exiting homelessness, the characteristics of families least likely to exit quickly and those most likely to return, as well as the relationship between type and level of service use to length of stay in shelter or homelessness. This type of study would require the collection of primary data, as a longitudinal prospective study focused on how families exit homelessness and their subsequent residential patterns has not been conducted.

Few studies have had a longitudinal perspective that could provide insight into the trajectories families take out of homelessness, and little is known about the types of assistance that families receive or whether they take full advantage of services or benefits that they may be eligible for in order to exit. There is also a lack of rigorous knowledge on the extent to which having bad credit, a criminal record, multiple children, and other factors hinder a family's ability to exit a homeless situation, nor are there data on the factors that influence repeat homelessness among families. Thus, this information would help classify families into level of need at entry into homelessness and during their homeless experience and help inform how these needs relate to length of stay in homelessness, as well as reentries into homelessness. If the sample is large enough to look at subgroups in regions, it would be possible to examine the relationship among contextual factors, individual factors, and family homelessness.

Of all the study options, a national longitudinal study of exit patterns and shelter requests of homeless families would likely provide some of the more intensive information on patterns and pathways out of homelessness and the role that services and resources have in that process. However, it would also be the costliest of the different study strategies proposed to inform the development of the typologies.

Typology Framework. With respect to the initial framework of a resource allocation typology, Dr. Babor proposed that it be based on three types of variables: exogenous (housing environment, housing, and health and human service access); endogenous (family and individual characteristics); and situational (the fit between the families' needs and accessible resources). The key will be to develop a typology that is useful and has practical importance. Selecting criterion variables based on ease of use was stressed by Expert Panel members as important to ensure its usefulness and replication. Environmental factors such as culture and geographic residence are considered important, but careful consideration of which variables to include is recommended since the sheer number of such variables could overwhelm a typology and dilute its usefulness.

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