Practice Profile: Targeted Truancy Interventions

Evidence Rating for Outcomes

Education | Attendance/truancy

Date: This profile was posted on September 10, 2013

These interventions are designed to increase attendance for elementary and secondary school students with chronic attendance problems. The practice is rated Effective for improving attendance.

Practice Goals/Target Population

Truancy is a problem for school systems across the nation and other countries. All truancy programs have a short-term goal of improving attendance; many also have longer-term goals of raising grades and graduation rates. Different interventions are designed to meet the needs of different populations. For instance, universal programs target all students in an elementary school, while indicated programs target youth with chronic attendance problems.

Practice Theory

Most interventions to reduce truancy draw on a risk/protective factors framework A variety of characteristics have been identified that can contribute to the problem of truancy at the school, family, community, and individual levels (Baker, Sigmon, and Nugent 2001; Heilbrunn 2007; Hammond, Smink, and Drew 2007; OJJDP and USED N.d.). School factors include, among others, inconsistent and ineffective school attendance policies, poor record keeping, not notifying parents/guardians of absences, and an unsafe school environment. Family and community factors include, among others, negative peer influences, such as other truant youth; financial, social, medical, or other needs that pressure students to stay home to help with family; teen pregnancy or parenthood; and lack of family support for educational and other goals. Individual factors include, among others, a lack of personal and educational ambition, poor academic performance, low school attachment, unmet mental health needs, and poor relationships with other students.

Practice Components

Interventions designed to address truancy can include a variety of components. Klima, Miller, and Nunlist (2009) identified the following program components included in their review of truancy interventions:

Academic remediation/tutoring
Career/technical education
Case management
Contingency management
Counseling
Mentoring/advocacy
Monitoring attendance
Parent outreach
Youth development

Practice Settings

There are many different types of interventions, settings, and approaches/strategies for truancy reduction. Broad categories include systems change, court-based programs, school-based programs, and community-based programs. Many programs include elements from different program types to successfully meet the needs of local communities.

Systems change approaches generally involve the modification of existing policies and procedures that hinder localities from addressing absenteeism and truancy. For instance, many school districts specify suspension as a punishment for truancy, which ends up “pushing out” students. A change in such policies can support truancy-reduction programs to achieve positive outcomes. For instance, in-school suspension policies, detention, and use of alternative school programs each allow students to continue their academic progress in the school setting, rather than having unsupervised time outside of it (Seeley and MacGillivary 2006).

Court-based programs leverage the power of the court to coordinate and oversee the delivery of services that are identified for the truant youth, and often for the family as well. Programs can differ in how long they run, the number of times the youth/family appears before the judge, the role of a social worker or case manager, the representatives included, and the types of services overseen by the court. Many systems have established diversion programs that offer services after a petition has been received, but before a youth is adjudicated. These programs have various levels of connection to the court, some even being labeled “truancy courts.”

Other programs are school-based. These programs aim to identify truancy and absence problems before they reach a chronic level and patterns become entrenched and harder to reverse.

Finally, some communities address truancy through community-level programs. These programs recognize that chronic truancy is not an individual or family problem alone, but is a community problem that can best be addressed by collaboration among various systems in the community.

For information on components that may influence the effectiveness of truancy programs, please see “Other Information.”

Meta-Analysis Snapshot
	Literature Coverage Dates	Number of Studies	Number of Study Participants
Meta Analysis 1	1990-2009	16	1725
Meta Analysis 2	1973-2007	35	3745

Meta Analysis 1

Maynard and colleagues (2012) conducted a meta analysis to assess the impact of indicated truancy interventions on increasing attendance (or decreasing absenteeism). A comprehensive search was conducted to locate relevant published and unpublished studies produced between 1990 and 2009 in the U.S., the United Kingdom, Australia, and Canada. Studies included programs in school-, court-, and community-based settings (studies in residential facilities and psychiatric day programs were excluded). To be included, studies needed to focus on students in primary or secondary educational institutions who were chronically truant. Interventions targeted either the student and/or the parent and included a variety of components (e.g., counseling or other therapeutic intervention, behavioral intervention, mentoring, and pharmacotherapy).

Maynard and colleagues identified 16 studies. Five studies utilized a randomized design (RCT), and 11 used a quasi-experimental design (QED). (The authors also identified and meta-analyzed the results of 12 single group pre-posttest (SGPP) design studies; because the SGPP design does not meet the minimum inclusion criteria for CrimeSolutions, the results are not reported here.) All included studies were conducted in the U.S. Of the 16 studies, four were published in a peer-reviewed journal; the remaining studies were unpublished and disseminated as dissertations or theses (10 studies) or reports (two studies). In addition to increasing attendance, a number of outcomes were included across studies, such as grades/Grade Point Average, behavior, achievement, and attitude toward school. These outcomes, however, were not assessed in the meta-analysis.

A total of 1,725 students participated in the treatment and comparison groups; of these, 902 students received the treatment and 823 were in the comparison condition. The majority of these participants were in middle school (31 percent) or high school (31 percent); elementary students were the target of intervention in only two of the studies. The mean age for students across samples was 13.73 years. Race/ethnicity was reported in 11 studies. For those reporting, Caucasian was the predominant group in five of the studies, African American in three, and Hispanic in three.

Authors reported the overall mean effect size for attendance outcomes. Mean effect sizes and their confidence intervals (CI) for each study were also reported. The authors assumed a random effects model across the studies. The researchers determined that the mean effect size for randomized control trials (RCTs) (g = .57) did not differ significantly from the mean effect size for quasi-experimental designs (QEDs) (g=.43). However, there was significant variance in effect sizes between studies, ranging from g = .00 to g = 1.175. A moderator analysis was conducted, but no moderators demonstrated a significant relationship with treatment effect.

Meta Analysis 2

Klima and colleagues (2009) conducted a meta analysis to assess the impact of truancy interventions on increasing attendance or enrollment. The evaluation studies were published between 1973 and 2007. To be included in the meta-analysis, evaluations needed to include a comparison group equivalent on key variables (such as attendance patterns and academic achievement). Studies with high attrition or a single group pre/post-test design were excluded from the analysis.

The search for program studies identified 877 possible candidates; only 22 studies met the criteria for methodology and relevant outcomes. These 22 studies included data on 35 independent samples for the attendance outcome. These studies included a number of program types—alternative educational, mentoring, behavioral, youth development, and academic radiation programs—as well as alternative schools. The 35 samples included 3,745 participants in the treatment groups; the number of participants in the control groups is not reported. No information on the race/ethnicity or other demographic information is reported for the studies included in the meta-analysis.

Authors reported an overall weighted mean effect size for all studies using a random effects model, but no individual effect sizes or CIs were reported for individual samples or studies. The authors also reported an overall weighted mean effect size by program class (e.g., academic remediation programs, alternative educational programs, and so forth).