The rate of poverty for children in the United States is far higher than for other advantaged nations (Payne & Biddle, 1999) with an estimated 13.3 million children, 18% of all children, living below the poverty threshold (U. S. Bureau of the Census, 2008). An estimated 5.8 million children live in extreme poverty where their families earn less than $10,600 per year (U. S. Bureau of the Census, 2008). Impoverished children are at a greater risk than their advantaged counterparts and face additional challenges including parental distress, lack of health insurance, chronic health problems, a cumulative risk stress, and a higher exposure to adversity (Masten, Miliotis, Graham-Bermann, Ramirez, & Neemann, 1993; Payne & Biddle, 1999). The situation for homeless or highly mobile children (HHM) is far bleaker. Children that are HHM are at an extreme risk for health problems, physical disabilities, poor self-control, malnutrition, developmental delays, anxiety, and depression (Miller & Lin, 1988; Rafferty & Shinn, 1991). They experience additional behavioral problems including nightmares, phobias, food hoarding, psychogenic water drinking, and extreme mood liability (Whitman, Accardo, Boyert, & Kendagor, 1990). The current study had two primary aims. The first aim was to examine HHM status as a risk factor for mathematic achievement over time, beyond the risk associated with poverty, indexed by qualifying for Federal free or reduced-price meal programs. The second aim was to examine whether the nature of this risk includes aspects that are chronic, acute, or both. Longitudinal achievement data spanning five years of assessment, beginning in the Fall of 2005, which was the ending point for the data analyzed by Obradovic and colleagues (2009) in the same school district. The current analyses employed an accelerated longitudinal design (Helms, 1992) to examine growth from 3rd to 8th grade, pooling 5 waves of longitudinal test data that were available. All analyses used multilevel models (Fitzmaurice, Laird, & Ware, 2004) to examine differences in initial achievement levels and in growth over 3rd through 8th grades. The setting for this study was a large, urban school district (LUSD). Homelessness and high residential mobility represent a substantial risk for lower academic achievement among students in 3rd through 8th grades in this large, urban school district. This was a salient issue with nearly 14% of all students in this district identified as HHM at some point over the course of 6 years. The risk associated with HHM-status has a clear chronic component where students who are ever HHM show markedly lower levels of achievement across 3rd through 8th grades, with no differences in growth compared to any other group of students. HHM students, as a group, underperform compared to more stably housed peers in reading and math achievement over time. Gaps appear and persist for the HHM group even when compared to peers who qualified for free meals based on low income. This suggests that HHM-status is a marker for high chronic risk. (Contains 3 tables and 1 figure.)
Authors
Desjardins, Christopher David, Cutuli, J.J., Herbers, Janette E., Chan, Chi-Keung, Hinz, Elizabeth, Heistad, David, Long, Jeffrey D., Masten, Ann S.
- Authorizing Institution
- Society for Research on Educational Effectiveness (SREE)
- Education Level
- ['Grade 3', 'Grade 4', 'Grade 5', 'Grade 6', 'Grade 7', 'Grade 8']
- Peer Reviewed
- F
- Publication Type
- Reports - Research
- Published in
- United States of America
Table of Contents
- Abstract Title Page 1
- Title Authors 1
- Abstract Body 2
- Background Context 2
- Purpose Objective Research Question Focus of Study 2
- Setting Population Participants Subjects Intervention Program Practice 3
- Research Design Data Collection and Analysis Data Collection Data Analysis 4
- Chronic-risk analyses. Acute-risk analyses 4
- Findings Results Chronic-Risk Analyses. Acute-Risk Analyses. Conclusions 5
- Appendices 6
- Appendix A. References 6
- Second international symposium on information theory 6
- IEEE Transactions on 6
- Automatic Control AC-19 6
- Model based inference in the life sciences A primer on evidence 6
- Sociological Methods Research 23 6
- Pediatrics 6
- The Review of Economics and Statistics 91 6
- American Journal of Physical Anthropology 6
- Journal of the American Academy of Child and Adolescent Psychiatry 6
- Austrailian Journal of Education 52 6
- Current 6
- Directions in Psychological Science 6
- Development and Psychopathology 6
- Journal of Consulting and Clinical Psychology 6
- Education 6
- Pediatrics 6
- Student mobility Exploring the 7
- RIT scale norms 7
- Development and Psychopathology 21 7
- The Journal of Educational Research 7
- American 7
- Psychologist 7
- Review of Educational Research 75 7
- Social Work 7
- American Journal of Public Health 7
- Appendix B. Tables and Figuress Table 1. 8
- Static Risk Models 8
- 446121 8
- 0.99 8
- Dynamic Risk Models 8
- 52558 8
- 0.82 8
- Table 2. 9
- Table 3. 10
- Figure 1 11
