Advertisement

Journal of Youth and Adolescence

, Volume 48, Issue 1, pp 30–42 | Cite as

Young Adult Unemployment and Later Depression and Anxiety: Does Childhood Neighborhood Matter?

  • Jungeun Olivia LeeEmail author
  • Tiffany M. Jones
  • Yoewon Yoon
  • Daniel A. Hackman
  • Joan P. Yoo
  • Rick Kosterman
Empirical Research

Abstract

Young adulthood represents a developmental period with disproportionately heightened risk of losing a job. Young adult unemployment has been linked to increased mental health problems, at least in the short term. However, their possible long-term impacts, often referred as “scarring effects,” have been understudied, possibly underestimating the magnitude of mental health burden that young adult unemployment generates. This longitudinal study examined whether duration of unemployment during young adulthood is associated with later mental health disorders, after accounting for mental and behavioral health problems in childhood. Furthermore, the current study investigated whether childhood neighborhood characteristics affect this association and if so, in what specific functional ways. Data were drawn from a longitudinal study of developmental outcomes in a community sample in Seattle. Data collection began in 1985 when study participants were elementary students and involved yearly assessments in childhood and adolescence (ages 10–16) and then biennial or triennial assessments (ages 18–39; N = 677 at age 39; 47% European American, 26% African American, 22% Asian American, and 5% Native American; 49% female). The current study findings suggest that duration of unemployment across young adulthood increased mental health problems at age 39, regardless of gender. Childhood neighborhood characteristics, particularly their positive aspect, exerted independent impacts on adult mental health problems beyond unemployment experiences across young adulthood. The current findings indicate a needed shift in service profiles for unemployed young adults—a comprehensive approach that not only facilitates reemployment but also addresses mental health needs to help them to cope with job loss. Further, the present study findings suggest that childhood neighborhoods, particularly positive features such as positive neighborhood involvement, may represent concrete and malleable prevention targets that can curb mental health problems early in life.

Keywords

Mental health Unemployment Scarring effects Life course Young adulthood Perceived neighborhood characteristics in childhood 

Notes

Acknowledgements

We would like to extend our gratitude to SSDP study participants for their continued contribution to the study.

Authors’ contributions

J.O.L. originated the study, performed the statistical analyses, guided additional data analyses, led the writing of the article, and coordinated drafting of the manuscript among co-authors; T.M.J. contributed to data preparation for analyses, drafted the method and result sections, and created tables; Y.Y. contributed to literature search; D.A.H. provided expertise in the conceptualization of neighborhood impacts; J.P.Y. contextualized findings in different cultural contexts; R.K. contributed to the conceptualization of the study, the data collection, and the interpretation of findings. In addition, all authors have been involved in drafting the manuscript and revising it critically for important intellectual content. All authors read and approved the final manuscript.

Funding

This study was supported by grants R01DA033956, 1R01DA024411, and 1R01DA009679 from National Institute on Drug Abuse. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the funding agency. The funding agency played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit this article for publication.

Data sharing and declaration

This manuscript’s data will not be deposited.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All study procedures were approved by the Human Subjects Review Committee of the University of Washington.

Informed consent

Informed consent was obtained from all participants included in the study.

References

  1. Achenbach, T. M. (1991). CBCL 4-18: YSR and TRF Profiles. Burlington, VT: University of Vermont Press.Google Scholar
  2. Achenbach, T. M., & Edelbrock, C. (1983). Manual for the Child Behavior Checklist and Revised Child Behavior Profile. Burlington, VT: University of Vermont Press.Google Scholar
  3. Ahern, J., & Galea, S. (2011). Collective efficacy and major depression in urban neighborhoods. American Journal of Epidemiology, 173, 1453–1462.  https://doi.org/10.1093/aje/kwr030.CrossRefGoogle Scholar
  4. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th edn.). Washington, DC: Author.Google Scholar
  5. Axinn, W. G., Pearce, L. D., & Ghimire, D. (1999). Innovations in life history calendar applications. Social Science Research, 28, 243–264.  https://doi.org/10.1006/ssre.1998.0641.CrossRefGoogle Scholar
  6. Bradshaw, C, Rebok, G, Zablotsky, B, Laflair, L, Mendelson, T., & Eaton, W. (2012). Models of stress and adapting to risk: a life course, developmental perspective. In: In W. Eaton (Ed.) Public mental health. (pp. 269–302). New York, NY: Oxford University Press.CrossRefGoogle Scholar
  7. Braveman, P. A., & Barclay, C. (2009). Health disparities beginning in childhood: a life-course perspective. Pediatrics, 124, S163–S175.  https://doi.org/10.1542/peds.2009-1100D.CrossRefGoogle Scholar
  8. Brody, G. H., Lei, M. K., Chen, E., & Miller, G. E. (2014). Neighborhood poverty and allostatic load in African American youth. Pediatrics, 134, E1362–E1368.  https://doi.org/10.1542/peds.2014-1395.CrossRefGoogle Scholar
  9. Broidy, L., & Agnew, R. (1997). Gender and crime: a general strain theory perspective. Journal of Research in Crimean and Delinquency, 34, 275–306.  https://doi.org/10.1177/0022427897034003001.CrossRefGoogle Scholar
  10. Bronfenbrenner, U. (2005). Making human beings human: Bioecological perspectives on human development. Thousand Oaks, CA: Sage.Google Scholar
  11. Bronfenbrenner, U., & Morris, P. A. (1998). The ecology of developmental processes. In R. Lerner (Ed.), Handbook of child psychology: 1. Theoretical models of human development. 5th ed. (pp. 992–1028). New York, NY: Wiley.Google Scholar
  12. Brydsten, A., Hammarström, A., Strandh, M., & Johansson, K. (2015). Youth unemployment and functional somatic symptoms in adulthood: results from the Northern Swedish cohort. European Journal of Public Health, 25, 796–800.  https://doi.org/10.1093/eurpub/ckv038.CrossRefGoogle Scholar
  13. Burt, K. B., & Paysnick, A. A. (2012). Resilience in the transition to adulthood. Development and Psychopathology, 24, 493–505.  https://doi.org/10.1017/S0954579412000119.CrossRefGoogle Scholar
  14. Caspi, A., Moffitt, T. E., Newman, D. L., & Silva, P. A. (1996a). Behavioral observations at age 3 years predict adult psychiatric disorders: longitudinal evidence from a birth cohort. Archives of General Psychiatry, 53, 1033–1039.  https://doi.org/10.1001/archpsyc.1996.01830110071009.CrossRefGoogle Scholar
  15. Caspi, A., Moffitt, T. E., Thornton, A., Freedman, D., Amell, J. W., Harrington, H., & Silva, P. A. (1996b). The life history calendar: a research and clinical assessment method for collecting retrospective event-history data. International Journal of Methods in Psychiatric Research, 6, 101–114.  https://doi.org/10.1002/(sici)1234-988x(199607)6:2<101::aid-mpr156>3.3.co;2-e.CrossRefGoogle Scholar
  16. Cassidy, T., & Wright, L. (2008). Graduate employment status and health: a longitudinal analysis of the transition from student. Social Psychology of Education, 11, 181–191.  https://doi.org/10.1007/s11218-007-9043-x.CrossRefGoogle Scholar
  17. Catalano, R., Goldman-Mellor, S., Saxton, K., Margerison-Zilko, C., Subbaraman, M., LeWinn, K., & Anderson, E. (2011). The health effects of economic decline. Annual Review of Public Health, 32, 431–450.  https://doi.org/10.1146/annurev-publhealth-031210-101146.CrossRefGoogle Scholar
  18. Center for Behavioral Health Statistics and Quality (2015). Behavioral health trends in the United States: Results from the 2014 National Survey on Drug Use and Health (HHS Publication No. SMA 15-4927, NSDUH Series H-50). https://www.samhsa.gov/data/sites/default/files/NSDUH-FRR1-2014/NSDUH-FRR1-2014.pdf
  19. Chodorow, N. (1978). Mothering, object-relations, and the female Oedipal configuration. Feminist Studies, 4, 137–158.  https://doi.org/10.2307/3177630.CrossRefGoogle Scholar
  20. Cicchetti, D., & Toth, S. L. (2009). The past achievements and future promises of developmental psychopathology: the coming of age of a discipline. Journal of Child Psychology and Psychiatry, 50, 16–25.  https://doi.org/10.1111/j.1469-7610.2008.01979.x.CrossRefGoogle Scholar
  21. Clark, A. E., Georgellis, Y., & Sanfey, P. (2001). Scarring: the psychological impact of past unemployment. Economica, 68, 221–241.  https://doi.org/10.1111/1468-0335.00243.CrossRefGoogle Scholar
  22. Currie, J. (2009). Healthy, wealthy, and wise: socioeconomic status, poor health in childhood, and human capital development. Journal of Economic Literature, 47, 87–122.CrossRefGoogle Scholar
  23. Daly, M., & Delaney, L. (2013). The scarring effect of unemployment throughout adulthood on psychological distress at age 50: estimates controlling for early adulthood distress and childhood psychological factors. Social Science & Medicine, 80, 19–23.  https://doi.org/10.1016/j.socscimed.2012.12.008.CrossRefGoogle Scholar
  24. Del Giudice, M., Ellis, B. J., & Shirtcliff, E. A. (2011). The adaptive calibration model of stress responsivity. Neuroscience and Biobehavioral Reviews, 35, 1562–1592.  https://doi.org/10.1016/j.neubiorev.2010.11.007.CrossRefGoogle Scholar
  25. Dooley, D., & Prause, J. (2004). The social costs of underemployment.. New York, NY: Cambridge University Press.Google Scholar
  26. Echeverria, S., Diez-Roux, A. V., Shea, S., Borrell, L. N., & Jackson, S. (2008). Associations of neighborhood problems and neighborhood social cohesion with mental health and health behaviors: the multi-ethnic study of atherosclerosis. Health and Place, 14, 853–865.  https://doi.org/10.1016/j.healthplace.2008.01.004.CrossRefGoogle Scholar
  27. Edwards, K. A., & Hertel-Fernandez, A. (2010). The kids aren’t alright: a labor market analysis of young workers. Washington, DC: Economic Policy Institute.Google Scholar
  28. Elder, Jr., G. H. (1994). Time, human agency, and social change: perspectives on the life course. Social Psychology Quarterly, 57, 4–15.CrossRefGoogle Scholar
  29. Ellis, B. J., & Boyce, W. T. (2008). Biological sensitivity to context. Current Directions in Psychological Science, 17, 183–187.  https://doi.org/10.1111/j.1467-8721.2008.00571.x.CrossRefGoogle Scholar
  30. Erdem, Ö., Van Lenthe, F. J., Prins, R. G., Voorham, T. A., & Burdorf, A. (2016). Socioeconomic inequalities in psychological distress among urban adults: The moderating role of neighborhood social cohesion. PLOS One, 11, e0157119  https://doi.org/10.1371/journal.pone.0157119.CrossRefGoogle Scholar
  31. Farver, J., Ghosh, C., & Garcia, C. (2000). Children’s perceptions of their neighborhoods. Journal of Applied Developmental Psychology, 21, 139–163.  https://doi.org/10.1016/S0193-3973(99)00032-5.CrossRefGoogle Scholar
  32. Fortin, N. M. (2015). Gender role attitudes and women’s labor market participation: opting-out, AIDS, and the persistent appeal of housewifery. Annals of Economics and Statistics, 117/118, 379–401.  https://doi.org/10.15609/annaeconstat2009.117-118.379.CrossRefGoogle Scholar
  33. Frasquilho, D., de Matos, M. G., Marques, A., Gaspar, T., & Caldas-de-Almeida, J. M. (2016). Distress and unemployment: the related economic and noneconomic factors in a sample of unemployed adults. International Journal of Public Health, 61, 821–828.  https://doi.org/10.1007/s00038-016-0806-z.CrossRefGoogle Scholar
  34. Freedman, D., Thornton, A., Camburn, D., Alwin, D., & Young-DeMarco, L. (1988). The life history calendar: a technique for collecting retrospective data. Sociological Methodology, 18, 37–68.  https://doi.org/10.2307/271044.CrossRefGoogle Scholar
  35. Friedland, D. S., & Price, R. H. (2003). Underemployment: Consequences for the health and well-being of workers. American Journal of Community Psychology, 32, 33–45.  https://doi.org/10.1023/a:1025638705649.CrossRefGoogle Scholar
  36. Galea, S., Ahern, J., Nandi, A., Tracy, M., Beard, J., & Vlahov, D. (2007). Urban neighborhood poverty and the incidence of depression in a population-based cohort study. Annals of Epidemiology, 17, 171–179.  https://doi.org/10.1016/j.annepidem.2006.07.008.CrossRefGoogle Scholar
  37. Galster, G., Santiago, A., Lucero, J., & Cutsinger, J. (2016). Adolescent neighborhood context and young adult economic outcomes for low-income African Americans and Latinos. Journal of Economic Geography, 16, 471–503.  https://doi.org/10.1093/jeg/lbv004.CrossRefGoogle Scholar
  38. Hackman, D. A., Betancourt, L. M., Brodsky, N. L., Hurt, H., & Farah, M. J. (2012). Neighborhood disadvantage and adolescent stress reactivity. Frontiers in Human Neuroscience, 6, 277  https://doi.org/10.3389/fnhum.2012.00277.CrossRefGoogle Scholar
  39. Hammarström, A., Gustafsson, P. E., Strandh, M., Virtanen, P., & Janlert, U. (2011). It’s no surprise! Men are not hit more than women by the health consequences of unemployment in the Northern Swedish Cohort. Scandinavian Journal of Public Health, 39, 187–193.  https://doi.org/10.1177/1403494810394906.CrossRefGoogle Scholar
  40. Hammarström, A., & Janlert, U. (2002). Early unemployment can contribute to adult health problems: Results from a longitudinal study of school leavers. Journal of Epidemiology and Community Health, 56, 624–630.  https://doi.org/10.1136/jech.56.8.624.CrossRefGoogle Scholar
  41. Hawkins, J. D., Oesterle, S., Brown, E. C., Abbott, R. D., & Catalano, R. F. (2014). Youth problem behaviors 8 years after implementing the communities that care prevention system: a community-randomized trial. JAMA Pediatrics, 168, 122–129.  https://doi.org/10.1001/jamapediatrics.2013.4009.CrossRefGoogle Scholar
  42. Hawkins, J. D., Smith, B. H., Hill, K. G., Kosterman, R., Catalano, R. F., & Abbott, R. D. (2003). Understanding and preventing crime and violence: Findings from the Seattle Social Development Project. In T. P. Thornberry & M. D. Krohn (Eds.), Taking stock of delinquency: an overview of findings from contemporary longitudinal studies (pp. 255–312). New York, NY: Kluwer Academic/Plenum.CrossRefGoogle Scholar
  43. Heinrichs, N., Rapee, R. M., Alden, L. A., Bögels, S., Hofmann, S. G., Ja Oh, K., & Sakano, Y. (2006). Cultural differences in perceived social norms and social anxiety. Behaviour Research and Therapy, 44, 1187–1197.  https://doi.org/10.1016/j.brat.2005.09.006.CrossRefGoogle Scholar
  44. Hertzman, C., & Power, C. (2003). Health and human development: understandings from life-course research. Developmental Neuropsychology, 24, 719–744.  https://doi.org/10.1207/s15326942dn242&3_10.CrossRefGoogle Scholar
  45. Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations. Thousand Oaks: Sage.Google Scholar
  46. Hultman, B., & Hemlin, S. (2008). Self-rated quality of life among the young unemployed and the young in work in northern Sweden. Work, 30, 461–472.Google Scholar
  47. Janlert, U., Winefield, A. H., & Hammarström, A. (2014). Length of unemployment and health-related outcomes: A life-course analysis. European Journal of Public Health, 25, 662–667.  https://doi.org/10.1093/eurpub/cku186.CrossRefGoogle Scholar
  48. Jukkala, T., Makinen, I. H., Kislitsyna, O., Ferlander, S., & Vagero, D. (2008). Economic strain, social relations, gender, and binge drinking in Moscow. Social Science and Medicine, 66, 663–674.  https://doi.org/10.1016/j.socscimed.2007.10.017.CrossRefGoogle Scholar
  49. Lee, J. O., Jones, T. M., Kosterman, R., Rhew, I. C., Lovasi, G. S., Hill, K. G., & Hawkins, J. D. (2017). The association of unemployment from age 21 to 33 with substance use disorder symptoms at age 39: the role of childhood neighborhood characteristics. Drug and Alcohol Dependence, 174, 1–8.  https://doi.org/10.1016/j.drugalcdep.2017.01.005.CrossRefGoogle Scholar
  50. Ludwig, J., Duncan, G. J., Gennetian, L. A., Katz, L. F., Kessler, R. C., Kling, J. R., & Sanbonmatsu, L. (2012). Neighborhood effects on the long-term well-being of low-income adults. Science, 337, 1505–1510.  https://doi.org/10.1126/science.1224648.CrossRefGoogle Scholar
  51. Ludwig, J., Duncan, G. J., Gennetian, L. A., Katz, L. F., Kessler, R. C., Kling, J. R., & Sanbonmatsu, L. (2013). Long-term neighborhood effects on low-income families: Evidence from moving to opportunity. American Economic Review, 103, 226–231.  https://doi.org/10.1257/aer.103.3.226.CrossRefGoogle Scholar
  52. McGee, R. E., & Thompson, N. J. (2015). Unemployment and depression among emerging adults in 12 states, Behavioral Risk Factor Surveillance System, 2010. Preventing Chronic Disease, 12, 140451  https://doi.org/10.5888/pcd12.140451.CrossRefGoogle Scholar
  53. McKee-Ryan, F. M., & Harvey, J. (2011). “I have a job, but…”: A review of underemployment. Journal of Management, 37, 962–996.  https://doi.org/10.1177/0149206311398134.CrossRefGoogle Scholar
  54. McKee-Ryan, F., Song, Z., Wanberg, C. R., & Kinicki, A. J. (2005). Psychological and physical well-being during unemployment: a meta-analytic study. Journal of Applied Psychology, 90, 53–76.  https://doi.org/10.1037/0021-9010.90.1.53.CrossRefGoogle Scholar
  55. McLeod, J. D., & Almazan, E. P. (2003). Connections between childhood and adulthood. In J. Mortimer & M. J. Shanahan (Eds.), Handbook of the life course (pp. 391–411). New York, NY: Kluwer Academic/Plenum.CrossRefGoogle Scholar
  56. Monteiro, N. M., Balogun, S. K., & Oratile, K. N. (2014). Managing stress: The influence of gender, age and emotion regulation on coping among university students in Botswana. International Journal of Adolescence and Youth, 19, 153–173.  https://doi.org/10.1080/02673843.2014.908784.CrossRefGoogle Scholar
  57. Moore, T. H. M., Kapur, N., Hawton, K., Richards, A., Metcalfe, C., & Gunnell, D. (2017). Interventions to reduce the impact of unemployment and economic hardship on mental health in the general population: A systematic review. Psychological Medicine, 47, 1062–1084.  https://doi.org/10.1017/s0033291716002944.CrossRefGoogle Scholar
  58. Mossakowski, K. N. (2009). The influence of past unemployment duration on symptoms of depression among young women and men in the United States. American Journal of Public Health, 99, 1826–1832.  https://doi.org/10.2105/ajph.2008.152561.CrossRefGoogle Scholar
  59. Muthén, L. K., & Muthén, B. O. (2015). Mplus user’s guide (7th ed.). Los Angeles, CA: Muthén & Muthén.Google Scholar
  60. Newman, D. L., Moffitt, T. E., Caspi, A., Magdol, L., Silva, P. A., & Stanton, W. R. (1996). Psychiatric disorder in a birth cohort of young adults: prevalence, comorbidity, clinical significance, and new case incidence from ages 11 to 21. Journal of Consulting and Clinical Psychology, 64, 552–562.  https://doi.org/10.1037//0022-006x.64.3.552.CrossRefGoogle Scholar
  61. Nieuwenhuis, J., van Ham, M., Yu, R. Q., Branje, S., Meeus, W., & Hooimeijer, P. (2017). Being poorer than the rest of the neighborhood: relative deprivation and problem behavior of youth. Journal of Youth and Adolescence, 46, 1891–1904.  https://doi.org/10.1007/s10964-017-0668-6.CrossRefGoogle Scholar
  62. Nolen-Hoeksema, S. (2004). Gender differences in risk factors and consequences for alcohol use and problems. Clinical Psychology Review, 24, 981–1010.  https://doi.org/10.1016/j.cpr.2004.08.003.CrossRefGoogle Scholar
  63. Oesterle, S. (2013). Pathways to young adulthood and preventive interventions targeting young adults.. Washington, DC: National Academies Press.Google Scholar
  64. Paul, K. I., & Moser, K. (2009). Unemployment impairs mental health: Meta-analyses. Journal of Vocational Behavior, 74, 264–282.  https://doi.org/10.1016/j.jvb.2009.01.001.CrossRefGoogle Scholar
  65. Reinherz, H. Z., Giaconia, R. M., Hauf, A. M. C., Wasserman, M. S., & Paradis, A. D. (2000). General and specific childhood risk factors for depression and drug disorders by early adulthood. Journal of the American Academy of Child and Adolescent Psychiatry, 39, 223–231.  https://doi.org/10.1097/00004583-200002000-00023.CrossRefGoogle Scholar
  66. Reneflot, A., & Evensen, M. (2014). Unemployment and psychological distress among young adults in the Nordic countries: a review of the literature. International Journal of Social Welfare, 23, 3–15.  https://doi.org/10.1111/ijsw.12000.CrossRefGoogle Scholar
  67. Riumallo-Herl, C., Basu, S., Stuckler, D., Courtin, E., & Avendano, M. (2014). Job loss, wealth and depression during the great recession in the USA and Europe. International Journal of Epidemiology, 43, 1508–1517.  https://doi.org/10.1093/ije/dyu048.CrossRefGoogle Scholar
  68. Robins, L., Helzer, J. E., Croghan, J., Williams, J. B. W., & Spitzer, R. L. (1981). NIMH Diagnostic Interview Schedule (Version III). Rockville: National Institute of Mental Health.Google Scholar
  69. Sareen, J., Afifi, T. O., McMillan, K. A., & Asmundson, G. J. G. (2011). Relationship between household income and mental disorders: findings from a population-based longitudinal study. Archives of General Psychiatry, 68, 419–427.  https://doi.org/10.1001/archgenpsychiatry.2011.15.CrossRefGoogle Scholar
  70. Schreier, S. S., Heinrichs, N., Alden, L., Rapee, R. M., Hofmann, S. G., Chen, J. W., & Bogels, S. (2010). Social anxiety and social norms in individualistic and collectivistic countries. Depression and Anxiety, 27, 1128–1134.  https://doi.org/10.1002/da.20746.CrossRefGoogle Scholar
  71. Sroufe, L. A. (2007). The place of development in developmental psychopathology. In M. A. S. (Ed.) Multilevel dynamics in developmental psychopathology: the Minnesota Symposia on Child Psychology (Vol. 34, pp. 285–299). Mahwah: Lawrence Erlbaum. .Google Scholar
  72. Stein, M. B., & Stein, D. J. (2008). Social anxiety disorder. Lancet, 371, 115–1125.  https://doi.org/10.1016/S0140-6736(08)60488-2.Google Scholar
  73. Strandh, M., Winefield, A., Nilsson, K., & Hammarström, A. (2014). Unemployment and mental health scarring during the life course. European Journal of Public Health, 24, 440–445.  https://doi.org/10.1093/eurpub/cku005.CrossRefGoogle Scholar
  74. Sweet, S., Sarkisian, N., Matz-Costa, C., & Pitt-Catsouphes, M. (2016). Are women less career centric than men? Structure, culture, and identity investments. Community, Work and Family, 19, 481–500.  https://doi.org/10.1080/13668803.2015.1078287.CrossRefGoogle Scholar
  75. Taylor, B., Rehm, J., Room, R., Patra, J., & Bondy, S. (2008). Determination of lifetime injury mortality risk in Canada in 2002 by drinking amount per occasion and number of occasions. American Journal of Epidemiology, 168, 1119–1125.  https://doi.org/10.1093/aje/kwn215.CrossRefGoogle Scholar
  76. Taylor, P., Parker, K., Kochhar, R., Fry, R., Funk, C., Patten, E., & Motel, S. (2012). Young, underemployed and optimistic: coming of age, slowly, in a tough economy. Washington, DC: Pew Research Center.Google Scholar
  77. Theall, K. P., Shirtcliff, E. A., Dismukes, A. R., Wallace, M., & Drury, S. S. (2017). Association between neighborhood violence and biological stress in children. JAMA Pediatrics, 171, 53–60.  https://doi.org/10.1001/jamapediatrics.2016.2321.CrossRefGoogle Scholar
  78. Tucker, J. S., Pollard, M. S., De La Haye, K., Kennedy, D. P., & Green, H. D. (2013). Neighborhood characteristics and the initiation of marijuana use and binge drinking. Drug and Alcohol Dependence, 128, 83–89.  https://doi.org/10.1016/j.drugalcdep.2012.08.006.CrossRefGoogle Scholar
  79. Wanberg, C. R. (2012). The individual experience of unemployment. Annual Review of Psychology, 63, 369–396.  https://doi.org/10.1146/annurev-psych-120710-100500.CrossRefGoogle Scholar
  80. Wilkins, R. (2007). The consequences of underemployment for the underemployed. Journal of Industrial Relations, 49, 247–275.  https://doi.org/10.1177/0022185607074921.CrossRefGoogle Scholar
  81. Wodtke, G. T., Harding, D. J., & Elwert, F. (2011). Neighborhood effects in temporal perspective: the impact of long-term exposure to concentrated disadvantage on high school graduation. American Sociological Review, 76, 713–736.  https://doi.org/10.1177/0003122411420816.CrossRefGoogle Scholar
  82. Yoshihama, M., Gillespie, B., Hammock, A. C., Belli, R. F., & Tolman, R. M. (2005). Does the life history calendar method facilitate the recall of intimate partner violence? Comparison of two methods of data collection. Social Work Research, 29, 151–163.  https://doi.org/10.1093/swr/29.3.151.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Suzanne Dworak-Peck School of Social WorkUniversity of Southern CaliforniaLas AngelesUSA
  2. 2.Social Development Research Group, School of Social WorkUniversity of WashingtonSeattleUSA
  3. 3.Department of Social Welfare, College of Social SciencesSeoul National UniversitySeoulSouth Korea

Personalised recommendations