Re-thinking research on typologizing homelessness

In homelessness research and policymaking, it seems to be axiomatic that single adults have three temporal kinds of homelessness: chronic, episodic and transitional. Despite this typology's research and policy influence, its theorization and the empirical research supporting that theorizing have important problems. In this paper, we analyze serious flaws with both of these. We then suggest a different way to think about typologizing temporality and report findings using that approach which suggest a radically different typology. We conclude by observing that, contrary to much argument, no one typology is necessarily accurate, in the sense of being "true," and that we should develop typologies based on theory and the uses to which the typology is put

Typologizing temporality : time-aggregated and time-patterned approaches to conceptualizing homelessness

This paper shows how we can use a relatively new method to construct time-based homeless typologies that expand our ability to theorize and to make policy. Our key argument is that commonly created "time-aggregated" typologies lose potentially useful information by summing, averaging or otherwise summarizing events that occur over time. We suggest instead a "time-patterned" approach that captures events as they unfurl over time by measuring their timing, duration and sequencing. Comparing time-aggregated and time-patterned analyses of Kuhn and Culhane's prominent three-category typology, we find the time-patterned approach performs marginally better. We argue, however, that both analyses reveal problematic heterogeneity in the three groups and that the initial theorizing is not robust. These deficiencies suggest the utility of further analysis. Using the time-patterned results, we identify a four-pattern/ten-group typology that technically and substantively contrasts strongly with the prevailing three-category typology. We then imagine how structural factors and individual traits can combine to generate these observed homeless patterns, and conclude that either approach and either typology may be appropriate, depending on theorizing and the uses to which the findings are to be put

Rethinking Research on Forming Typologies of Homelessness

In homelessness research and policymaking, it seems to be axiomatic that single adults experience 3 temporally based types of homelessness: chronic, episodic, and transitional. We discuss problems with the theorization of this typology and with the research design, data analysis, and time-aggregated conceptualization and measurement of temporality in the empirical work supporting the typology. To address the latter, we suggest a time-patterned approach to temporality and report a 10-group typology that differs significantly from the more familiar 3-group typology. We argue that which approach is used—and how typologies are developed more generally—should be based on theory and the uses to which typologies are put rather than on claims to being more true

Does Residential Mobility Affect Child Development at Age Five? A Comparative Study of Children Born in US and UK Cities

Residential mobility is a normal feature of family life but thought to be a source of disruption to a child's development. Mobility may have its own direct consequences or reflect families' capabilities and vulnerabilities. This article examines the association between changes of residence and verbal and behavioral scores of children aged 5, contributing to the literature in three ways. First, it compares two countries, by drawing on the Fragile Families and Child Wellbeing study in the United States (N = up to 1,820) and an urban subsample of the U.K. Millennium Cohort study (N = up to 7,967). Second, beside taking into account an extensive range of demographic characteristics, it applies inverse probability weights to minimize observable selection bias associated with residential mobility and further controls for a wide range of family changes that often co-occur with moves. Third, the article adds to extant research on residential mobility by incorporating the type of locality from and into which families move. Individual-level longitudinal data are linked to objective measures of neighborhood socioeconomic status to gauge the quality of moves families make. Results show that residential moves are not inevitably deleterious to children. In both countries the poorer outcomes of some moves result not from moving per se but rather from the context in which they occur

Temporality and Intervention Effects: Latent Trajectory Analysis of a Homeless Mental Health Program

Intervention analyses which incorporate temporality over a followup period typically note differences in the patterns of "single-curves" for each the experimental and control groups or differences in temporally-based taxonomies between experimentals and controls. But the former fails to allow for the possibility of subgroups of multiple trajectories and the latter collapses time (e.g., average spell durations) and arbitrarily creates cut-points to form its taxonomies. This paper investigates the utility for intervention research of using latent class growth analysis (LCGA). This method incorporates the more complete temporal information used by single-curve approaches to statistically identify the multiple subgroups at the heart of the taxonomic approach. The authors do this by reanalyzing a critical time intervention study (CTI) of homeless mentally ill men that used both single-curve and taxonomic approaches. By finding, among other things, differences between experimentals and controls in the number, sizes and patterns of latent subgroups than were found in the prior analysis, this paper suggests the utility of LCGA for assessing service interventions

Capturing Intervention Effects Over Time: Reanalysis of a Critical Time Intervention for Homeless Mentally Ill Men

Objectives. We analyzed whether a method for identifying latent trajectories—latent class growth analysis (LCGA)—was useful for understanding outcomes for individuals subject to an intervention. Methods. We used LCGA to reanalyze data from a published study of mentally ill homeless men in a critical time intervention (CTI) program. In that study, 96 men leaving a shelter's onsite psychiatric program were randomly assigned to experimental and control groups. The former received CTI services and the latter usual services. Each individual's housing circumstances were observed for 18 months after program initiation. Our outcome measure was monthly homelessness: a person was considered homeless in a month if he was homeless for even 1 night that month. Results. Four latent classes were found among the control group, but just 3 among the experimental group. Control, but not experimental, group individuals showed a small class of chronically homeless men. The size of the never-homeless class was 19 percentage points larger for the experimental than for the control group. J- and inverted-U-shaped patterns were also found among both groups, but with important differences in timing of patterns. Conclusions. Our results reveal effects not apparent in the original analysis, suggesting that latent class growth models improve intervention evaluation

Welfare Research Perspectives: Past, Present, and Future, 2000 Edition

This is the second in a series of three working papers designed to examine what has been learned since the enactment of the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) of 1996

Developing Better Measures of Neighbourhood Characteristics and Change for Use in Studies of Residential Mobility: A Case Study of Britain in the Early 2000s

This paper addresses the problem of measuring neighbourhood characteristics and change when working with individual level datasets to understand the effects of residential mobility. Currently available measures in Britain are in various respects unsuitable for this purpose. The paper explores a new indicator of small area poverty: the Unadjusted Means-tested Benefits Rate (UMBR), which divides claimants of means-tested benefits in a small area by the number of households. We describe changes in area poverty between 2001 and 2006, using UMBR. As often assumed, these are generally negligible, but small areas in “disadvantaged urban“ and “multicultural city life“ communities did change considerably in this period. We also link UMBR to the first three waves of the UK Millennium Cohort Study, a survey of families with children born at the beginning of the 2000s. We examine opinions about neighbourhood and find that parents living in areas of higher poverty did tend to express more negative views than those living elsewhere. Living in high poverty areas was also associated with moving home, and those families who retrospectively gave neighbourhood considerations as reasons for moving did move into areas with markedly lower poverty rates. Finally, we compare families' moving trajectories to trends in poverty within areas. We are able to show that a large proportion of families who moved to poorer neighbourhoods were at double disadvantage, as they often moved to areas with increasing poverty rates. We conclude that UMBR can be used to enhance understanding of changing neighbourhood contexts in cohort studies, at least for this period, although it still suffers from the same conceptual and technical difficulties as other available alternatives in terms of its ability to capture aspects of neighbourhood quality

Developing Better Measures of Neighbourhood Characteristics and Change for Use in Studies of Residential Mobility: A Case Study of Britain in the Early 2000s

This paper addresses the problem of measuring neighbourhood characteristics and change when working with individual level datasets to understand the effects of residential mobility. Currently available measures in Britain are in various respects unsuitable for this purpose. The paper explores a new indicator of small area poverty: the Unadjusted Means-tested Benefits Rate (UMBR), which divides claimants of means-tested benefits in a small area by the number of households. We describe changes in area poverty between 2001 and 2006, using UMBR. As often assumed, these are generally negligible, but small areas in “disadvantaged urban“ and “multicultural city life“ communities did change considerably in this period. We also link UMBR to the first three waves of the UK Millennium Cohort Study, a survey of families with children born at the beginning of the 2000s. We examine opinions about neighbourhood and find that parents living in areas of higher poverty did tend to express more negative views than those living elsewhere. Living in high poverty areas was also associated with moving home, and those families who retrospectively gave neighbourhood considerations as reasons for moving did move into areas with markedly lower poverty rates. Finally, we compare families' moving trajectories to trends in poverty within areas. We are able to show that a large proportion of families who moved to poorer neighbourhoods were at double disadvantage, as they often moved to areas with increasing poverty rates. We conclude that UMBR can be used to enhance understanding of changing neighbourhood contexts in cohort studies, at least for this period, although it still suffers from the same conceptual and technical difficulties as other available alternatives in terms of its ability to capture aspects of neighbourhood quality

Measuring Economic Disadvantage During Childhood: A Group-Based Modeling Approach

Recent research suggest that child well-being and subsequent status attainment are influenced not only by the overall magnitude of exposure to family economic disadvantage during childhood, but also by the age of exposure and significant changes in family economic circumstances. Unfortunately, traditional measures of children's economic deprivation, such as permanent and transitory income, persistent or cumulative poverty, and the number and length of poverty spells, fail to differentiate between exposure to disadvantage at different stages in childhood and largely ignore how family economic circumstances are changing over time. In this paper, the authors propose a new method for assessing economic disadvantage during childhood that captures both children's overall levels of exposure to economic disadvantage and their patterns of exposure. This new method, which takes advantage of recent advances in finite mixture modeling, uses a longitudinal latent class model to classify children into a limited number of groups with similar histories of exposure to family economic disadvantage. Using this new methodology, group membership can be related to both family background characteristics and achievement in childhood and early adulthood, making it possible both to assess how family characteristics affect patterns of exposure to disadvantage during childhood and directly test alternative theories about the effect of different patterns of exposure on achievement. In this paper, the relationship between background factors, such as race, parental education, and family structure, and group membership is investigated, as is the association between group membership and achievement in early adulthood. The use of this technique is demonstrated using data from the Panel Study of Income Dynamics (PSID)