As compared to those who graduated, urban high school dropouts, regardless of whether they had childhood ADHD, had significantly lower scores on estimated measures of general cognitive functioning and reading ability, came from more disadvantaged socioeconomic backgrounds, used marijuana on a regular basis over the past year, and had more limited contact with their biological fathers. Strikingly, and in contrast to our hypothesis, none of these factors differentially influenced the risk of dropout in adolescents with childhood ADHD as compared to controls who never have had ADHD. Logistic regression further indicated that among risk factors, both cognitive and psychosocial factors made unique contributions to the likelihood of dropping out. Thus, not only do cognitive ability, marijuana use and paternal involvement appear to independently increase risk for high school dropout, but their effects seem to be additive. In this study, FSIQ was moderately related to drug use and father contact, whereas drug use and father contact were unrelated. Socioeconomic status and reading ability did not contribute to dropout once the other variables were entered.
Notably, this study was not designed to compare dropout rates between ADHD adolescents and controls per se due to the fact that many of the potential participants in the study were still in school. Assessment of such rates would be prone to considerable error. While there was a trend towards increased dropouts among those with ADHD (nearly 1.9 dropouts to every one graduate with childhood ADHD; in controls, nearly 1.2 dropouts to every one graduate), we cannot definitively say that, within our study, childhood ADHD increased the risk for dropping out of high school.
The results of this follow-up study are unique to the existing literature on the heterogeneity of ADHD outcomes in adolescence in that we examined the potential influence of important additive cognitive and psychosocial factors associated with the disorder that also contribute to the likelihood of dropping out of high school. By utilizing a demographically similar control group that was well-matched to the clinical group with regard to SES and general cognitive ability, we were able to determine the relative impact that these risk factors have on school completion in an urban population of adolescents/young adults with and without documented childhood psychopathology. This is important since it has been shown that regardless of disability, many urban minority males who are from the lower end of the socioeconomic spectrum tend to encompass the majority of dropout populations (Scanlon & Mellard, 2002
). Consistent with this, the adolescents with childhood ADHD were not more sensitive to the negative impact of the additive risk factors. This suggests that previous findings (Weiss & Hechtman, 1986
) of elevated rates of dropout among those with childhood ADHD may not have been due to ADHD per se. Rather, group differences may have been due to the fact that, as compared to controls, the group with ADHD had higher rates of these comorbid risk factors as well. It is not uncommon for studies to report lower FSIQ (Doyle, Biederman, Seidman, Weber, & Faraone, 2000
; Faraone et al., 1993
) and reading scores (Faraone et al., 1993
), more limited paternal contact (Barkley et al., 1990
), lower SES (Mannuzza et al., 1993
), and increased substance use (Mannuzza et al., 1993
) among individuals with ADHD as compared to controls.
More importantly, perhaps, is that these other studies differed from the current study on key race/ethnicity and SES variables known to contribute to dropping out (Scanlon & Mellard, 2002
). Our sample is highly ethnically diverse (only 26% Caucasian) with numerous families near the bottom of the SES spectrum, whereas the majority of participants in the other studies (e.g., Mannuzza et al., 1988
; Weiss et al., 1985
) were predominately Caucasian and generally from higher SES backgrounds. The fact that we had such a high background rate of dropout in our sample (31% overall) was not so different from what the general dropout rate has been for schools in the areas from which the participants were drawn (25%), or from similar urban areas (e.g., 55% dropout rate in Los Angeles; Swanson, 2005
). It is important to note, however, that while the findings here may not be true of other SES groups, at least one other study with a different SES pool has reported similar findings regarding the predictability of academic outcomes in ADHD such that childhood IQ predicted later academic achievement (Fischer, Barkley, Fletcher, & Smallish, 1993
). Thus, the discontinuity within SES on dropout rates in ADHD needs to be further explored.
This study was somewhat limited by a small sample size which was in part due to the fact that a substantial proportion of the youths were still in school. This decreased the available statistical power, which forced us to use MANOVA as our primary statistical approach as opposed to structural equation modeling. Nevertheless, using this approach, the effect sizes suggest that even if a greater number of participants were included in the analyses, most non-significant findings would not appreciably change. While it would have been advantageous perhaps to wait and re-evaluate the sample at a later date when all would have reached the age at which they would either graduate or dropout, the highly mobile nature of this urban sample makes it worrisome that many would be lost to follow-up. Perhaps more importantly is the fact that the predictor variables were assessed concurrently rather than in childhood. It would have been advantageous to examine the stability of these factors from childhood into adolescence, but unfortunately the control group was not recruited into the study until the age of 16.
It is important to emphasize the point that the aim of this study was to examine the relative influence that specific risk factors have on dropping out and not whether dropping out is more common in adolescents with childhood ADHD than in controls. In order to answer this latter question, we would have to wait for all participants to either complete or drop-out of high school. More importantly, an epidemiologically-sound, community-based sample would be required to truly determine whether youth with ADHD are more prone to drop-out, not a clinically-referred sample such as ours.
This study indicates the need for examination of risk factors other than ADHD in attempting to identify youth at risk for poor academic outcome in adolescence in an at-risk urban population. When tailoring preventative strategies for educational failure in youth from lower-status urban areas, it may be necessary to focus on these additional risk factors, as they seem to contribute substantially to the probability of dropping out. This is likely due to the added negative influence that less stable family environments and increased drug use adds to youth living in inner-city areas. Despite this risk, it has been shown that participation in early childhood educational and family support interventions for low-income, inner-city preschool students is significantly associated with reduced school dropout rates during adolescence and early adulthood (Reynolds, Temple, Robertson, & Mann, 2001
). Future longitudinal protocols examining ADHD and other developmental disorders should incorporate similar procedures (i.e., examining additive risk factors) in order to determine the degree to which pathology alone contributes to adolescent outcome.