Among likely risk factors for youth psychopathology, chronic school absenteeism is a widespread problem that is potentially preventable, yet its role in the development of mental illness remains poorly understood. With the high prevalence rates of psychiatric disorders among youth in the U.S., increasing attention has been paid to the 8-11% of American children and adolescents who exhibit chronic absenteeism. Theory suggests that chronic absenteeism can trigger or exacerbate psychiatric disorders, and is not merely an effect or marker of pre-existing psychopathology. However, previous research has been unable to clarify the nature of the psychopathology-absenteeism relationship due to a lack of methodologically-sound longitudinal studies and causal modeling. The proposed study seeks to (a) test a causal model of absenteeism as a determinant of future psychopathology and (b) identify possible causes of absenteeism to inform selective prevention models. Four nationally or regionally representative school-based longitudinal datasets that feature repeated measures of youth psychopathology, school attendance, and relevant covariates spanning 1st through 12th grade will be employed to test hypotheses (Ns = 20,745; 2,311; 678; and 671). Measures of psychopathology administered repeatedly in these studies vary and include validated diagnostic interviews and self-report forms such as the Diagnostic Interview Schedule for Children-IV (DISC-IV, Shaffer et al., 2000), the Children's Depression Inventory (CDI; Kovacs, 1983), and the Teacher Report Form (TRF; Achenbach, 1991). By employing multiple datasets, the invariance of the conceptual model across samples with differing demographic characteristics may be tested. Structural Equation Modeling (SEM) and Latent Mixed Markov Chain Analysis (LMM) will be used to generate a transition-focused analysis of youth psychiatric functioning over time. These causal modeling techniques can test whether being categorized as chronically absent at one time point increases the probability of transitioning to a higher-psychopathology class (i.e., exacerbation) or remaining at a high- psychopathology class (i.e., persistence) in subsequent years, relative to other children and controlling for prior psychiatric functioning and relevant covariates. Potential determinants of absenteeism (e.g., medical problems, social problems, academic difficulties, exposure to risky environments) will then be tested in parallel causal models to assess their influence on emerging school attendance problems over time. These person-centered analyses will permit conclusions about clinically significant transitions over time and will thereby clarify the role of absenteeism as a true risk factor versus a marker or effect of psychopathology. This research may promote public health efforts to reduce the incidence of psychopathology by (a) providing an empirical basis for identifying youth at high risk of developing new or worsening psychiatric problems, and (b) informing the development of preventive interventions to help such youth avoid negative mental health sequelae. The proposed research will advance public health efforts to identify US youth who are at risk for developing mental illness. If poor school attendance is found to be a precursor of psychiatric disorders as hypothesized, at-risk youth may then be offered intervention programs that could prevent the onset of mental illness. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Small Research Grants (R03)
Project #
5R03MH081087-02
Application #
7540851
Study Section
Child Psychopathology and Developmental Disabilities Study Section (CPDD)
Program Officer
Zehr, Julia L
Project Start
2007-06-01
Project End
2010-05-31
Budget Start
2008-06-01
Budget End
2010-05-31
Support Year
2
Fiscal Year
2008
Total Cost
$72,649
Indirect Cost
Name
University of California Los Angeles
Department
Type
Schools of Education
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Wood, Jeffrey J; Lynne-Landsman, Sarah D; Langer, David A et al. (2012) School attendance problems and youth psychopathology: structural cross-lagged regression models in three longitudinal data sets. Child Dev 83:351-66
Langer, David A; Wood, Jeffrey J; Bergman, R Lindsey et al. (2010) A multitrait-multimethod analysis of the construct validity of child anxiety disorders in a clinical sample. Child Psychiatry Hum Dev 41:549-61