School Attendance and Child Welfare: The Prevention Potential of Addressing Educational Neglect

1. School Attendance and Child Welfare: The Prevention Potential of Addressing Educational Neglect Anita M. Larson, M.A. Timothy B. Zuel, MSW, LICSW University of Minnesota Center for Advanced Studies in Child Welfare, School of Social Work

2. History of School Attendance • End of 19th Century in America • Massive immigration • Industrialization • Child labor • Battles ensued between business and child advocates (Katz, 1976)

3. School Attendance Reforms Achieved Multiple Goals • Ready remedy for those wishing to ameliorate child labor • Supported the Americanization of the children of immigrants • Supported an educated work force • Supported an educated polity (Chambers, 1963; Katz, 1976)

4. By 1930 • “Institutionalization of compulsory education laws” (Katz, 1976) • All states had attendance laws by 1919. • Enforcement of laws involved truancy officers, courts, and state attorneys’ offices • School funding was now tied to attendance. • Paved the way for the involvement of criminal systems

5. By the 1980s • The justice systems became overburdened with truants by the 1970s. • Research began to recognize that there were family functioning factors involved in attendance problems. • 25 States incorporated early truancy into their Child Welfare statutes. • There was realization that the justice system might not be appropriate for addressing this problem. (Nielsen & Gerber, 1979; Farrington, 1980; Barth, 1984; Levine, 1984; Bell, Rosen & Dynlacht, 1994; Epstein, 1995, 2001)

6. By the 1980s • 1974 Juvenile Justice and Delinquency Act • Eased monitoring of school attendance problems for young children away from justice system. • Placed responsibility within child welfare by • Redefining truancy as a family problem, • Providing access to intervention services for families, and • Creating a new label: became known as “educational neglect”.

7. Minnesota • 1993 Maltreatment of Minors Act • Created an official delineation of school attendance problem categories based on child age: • 11 and under (Educational Neglect) (7 or more days absent, unexcused) • 12 and over (Truant)

8. Why We Care About School Attendance Social Engagement Inability to succeed Free time and lack of supervision Non-conformity, excess free time • Poor attendance is predictive of maladjustment (Reid, 1984) • Poor academic performance and school dropout (Kandel, et al., 1984; Wehlage, et al., 1986) • Substance abuse (Hallfors, et al., 2002) • Delinquency (Dryfoos, 1990; Rohrman, 1993; Kaplan, et al., 1994: Bell, et al., 1994; Garry, 1996; Baker, 2000)

9. Effects Persist into Adulthood • Predicting poor adult outcomes: • Criminality • Increased violence • Poor job prospects & poverty • Marital instability • Job instability • Incarceration (Robins & Ratcliff, 1978; Dryfoos, 1990; Snyder & Sickmund, 1995; Catalano, et al., 1998)

10. Young Children and Absenteeism • Retrospective study has shown patterns of school drop outs having higher absentee rates as early as 1st grade compared to graduates (Barrington & Hendricks, 1998). • Lehr, et al. (2004) suggest a spiral effect where drop outs had twice the absences in 5th grade and three times the absences in 9th grade compared to graduates. • 70% predictive accuracy of drop outs when using attendance data, teacher comments, and achievement scores (Barrington & Hendricks, 1989)

11. CASCW Studies • Today we will provide an overview of two related studies: • An initial analysis of the status of school attendance of children one year after they received a Child Welfare (CW) intervention for educational neglect (Original Study), and • The status of the school attendance of these same children four years later (longitudinal analysis) (Follow-Up).

12. Original Study: Design • 2005 CASCW paper: Does CP intervention affect attendance? • All educational neglect maltreatment reports in Minnesota during the 2000-2001 school year (47 counties reporting), • Linked these students with their public school attendance records in same year (N=623), and • Compared the attendance records of same cohort the following school year 2001-2002

13. Original Study: Educational Neglect and CP

14. Original Study: Educational Neglect and CP

15. Original Study: Educational Neglect and CP

16. Original Study: Attendance & Age

17. Original Study: Attendance & Race

18. Original Study: Conclusions • Evidence suggested that CP Intervention did positively affect attendance (70% improvement overall). • Disparity in race with maltreatment findings disappeared in improvement outcomes (for both African American and American Indian children) • Either race is a factor in reporting or a factor in maltreatment determination (or both). • Age improvement declined as cohort reached 11 years of age (conforms with practice knowledge)

19. Follow-Up on Original Group • Over four subsequent years of education data, records were located on 502 of the original educational neglect group (varied over years). • There was roughly 9% loss in original students year-to-year (~24 students) • Non-matching was completely at random

20. Follow-up: Education Match Rates

21. Follow-up: Match Rates

22. Follow-up: Groups • The original groups were comprised of three types of student attendance change over time: • Maintained (no significant change in attendance, within +.03) • Worsened • Improved • For the follow-up, we combined Maintained and Improved into one.

23. Follow-up: Median Attendance Trajectories

24. Follow-up: Attendance Medians and Means

25. Follow-up: Variation

26. 90%AttendanceThreshold • For analyses of attendance patterns, a threshold was established. • We chose 90%: • School districts across the country use 90% as a minimum threshold(Tulsa Public Schools, 2004; Nevada Public Schools, 2008; New Mexico Public Schools, 2008) • Minnesota’s schools and Legislature have recognized 90% as a threshold(Minnesota House of Representatives House Research, 2003; Heistad, 2008) • This threshold helps us determine whether there is practical significance to our findings.

27. Follow-up: Differences Observed in Means through 2004 F=9.264, 1, 486, p=.002

28. Follow-up: Differences Observed in Means by Age of Child at Maltreatment F=3.018, 1, p=.075 F=3.345, 1, p=.071

29. Follow-up: Differences Observed in Means by Age of Child at Maltreatment F=7.137, 1, p=.010

30. Attendance Trajectories • Attendance patterns were grouped depending upon their overall direction: • NAT: Negative Attendance Trajectory • PAT: Positive Attendance Trajectory • MIX: Mixed attendance trajectory • A majority of attendance ratios needed to be in the same direction to assign a trajectory • E.g. 2 years increasing, one year decreasing = PAT; 3 years decreasing, one year missing = NAT

31. Attendance Trajectories by Original Groups Trajectory groups were used in combination with whether or not students had attendance that rose above 90%. (MIXed attendance students were removed.)

32. Predicting Trajectories • There were no significant relationships between trajectory and substantiated maltreatment, gender or geography (Metro versus non-Metro counties) • Black/African American students were twice as likely as Whites to have PAT (risk ratio: 2.22, p<.01, 95% CI) although other non-white groups fared the worst of all three groups.

33. Predicting Trajectories • Students with school disruptions were nearly twice as likely to have a NAT than those without any disruptions (risk ratio: 1.91 p<.001, 95% CI) • Students with subsequent (additional) reports to child welfare were half again more likely than one who did not to have PAT (risk ratio: .52, p<.01, 95% CI). This was not true for substantiated maltreatment.

34. Limitations • Students with mixed trajectories (40%) were removed to simplify our analyses • We are unable to discern a pattern • Many data quality issues • Variability in school attendance recording practices • Variability in school attendance policies • Intervention unknowns • We cannot know what interventions schools might have employed. • There is county variation in how educational neglect is addressed.

35. What We Learned: What the study was not • Not a formal evaluation of child welfare as an intervention strategy for school non-attendance • Lacked controls / randomization • Cannot “prove” that child welfare successfully changed the course of student attendance • Does not control for the myriad of other factors that influence school engagement

36. What We Learned: What we believe the study showed • It is likely that Child Welfare involvement had someimpact on student attendance • Supported by what we know about what causes poor attendance (family factors) and • How child welfare services are structured (child & family ecology) • Ongoing contacts may have been protective (reports) • Gains are not sustained beyond two years. • Gains are more likely retained by African American children.

37. Implications: Practice • Better leverage of community sources inclusive of school personal as partners in CP work. • Focus on K-3 population in school attendance intervention strategies. • Emphasize attendance in all CP case planning irrespective of placement or allegation.

38. Implications: Policy • Direct prevention funding to systems that attend to absenteeism. • Require data collection on child welfare and attendance beyond CFSR’s. • Employ consistent attendance process across districts and schools. • Consider whether CW the best place to attend to absenteeism and accompanying developmental issues?

39. Implications: Research • Child welfare as an intervention for early attendance problems deserves more rigorous study • Other, similarly structured interventions for young children should be rigorously examined • Interventions that take into account the ecology of the child; the family context • Studies should incorporate dollar figures for costs and benefits

40. Research Hypothesis

41. Thank you! Timothy B. Zuel, LICSW tzuel@umn.edu Anita Larson, M.A. Research Fellow amlarson@umn.edu http://cehd.umn.edu/SSW/cascw/research/minnlink/default.asp