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Sleep and Preteen Delinquency: Is the Association Robust to ADHD Symptomatology and ADHD Diagnosis?

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Abstract

Both qualitative and quantitative aspects of sleep have been linked to multiple dimensions of well-being. An emerging body of research has also revealed that poor sleep during adolescence can increase the likelihood of delinquent involvement. The contribution of early sleep difficulties to later delinquency, however, is often overlooked. Furthermore, the role that ADHD symptomatology and/or diagnosis might play in this association has not been adequately addressed, despite findings suggesting that both sleep disturbances and delinquent involvement are more common among children with ADHD symptomatology or an ADHD diagnosis. The current study examines the associations between sleep behaviors and preteen delinquency, and the extent to which ADHD symptomatology and/or diagnosis might inform these associations. Data from the Fragile Families and Child Wellbeing Study (FFCWS) were employed to explore these associations and logistic regression techniques were utilized to analyze the data. The findings reveal that both sleep problems and sleep duration are associated with the odds of ADHD symptomatology, an ADHD diagnosis, and preteen delinquency. Even so, the results also suggest that persistent sleep problems are not significantly associated with the odds of preteen delinquency once ADHD symptomatology and diagnosis are taken into account. The influence of sleep duration on preteen delinquency, however, is robust to the association between ADHD measures and preteen delinquency. Poor sleep, therefore, appears to be an important modifiable risk factor for preteen delinquency. Even so, future investigations into the link between sleep and delinquency should account for developmental risks and/or disorders that commonly co-occur with sleep problems.

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Notes

  1. In cases where the survey was labeled “primary caregiver”, such as the in-home survey, mothers were the primary caregivers overwhelmingly (at wave 3, for example, 98.8% of caregivers were mothers – 0.47% were fathers, 0.41% were grandmothers, and even fewer were other relatives/friends).

  2. Home visits were attempted with all eligible individuals in the sample by wave 3.

  3. Importantly, alternative models using multiple imputation (instead of listwise deletion based on missing data on covariates) yielded substantively similar results. For other studies using FFCWS and listwise deletion, and with final samples similar in size to our study, see Boutwell and Beaver 2010 and Wildeman 2010.

  4. Alternative coding of the outcome variable yield substantively similar results. Dichotomization was chosen due to the scale (alpha = .74) being positively skewed and zero-inflated.

  5. Mean = .00, standard deviation = .57, range = −.93–3.29. If teacher data was missing, children would be assessed on parent data only, although the majority of children did have both reports (about 70%). Supplementary materials display results using the continuous ADHD symptomatology scale. The results were substantively identical.

  6. Youths may have a high degree of symptomatology, yet remain undiagnosed. Conversely, diagnosed individuals may not score incredibly high on the symptomatology index, yet still be considered as having ADHD by a medical professional. Thus, including both in the analysis minimizes the possibility of overlooking youths with a behavioral repertoire that characterizes the disorder.

  7. Although a continuous measure of income was available, it did not emerge as a significant predictor of any of the outcomes, as small variations in income had little bearing on the results. Consequently, the quintile measure was included to demonstrate the robustness of the results to categories that more accurately reflect the degree of economic disadvantage in the household.

  8. See supplementary materials for additional descriptive details regarding individual delinquency items.

  9. Although not explicitly displayed, all covariates that were included in the models displayed in Table 2 were also included in the models displayed in Table 3.

  10. We checked the robustness of the results after performing multiple imputation in STATA using mi commands. After increasing the sample sizes in cases to the full sample of in-home surveys, similar results emerged across all models [e.g., delinquency regressed on sleep problems, OR = 1.68; CI = 1.35–2.09. delinquency regressed on sleep duration, OR = .83; CI = (.74–.93]. See Supplementary Materials for a summary of the multiple imputation results.

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Authors and Affiliations

  1. The University of Texas at San Antonio, San Antonio, TX, USA

    Dylan B. Jackson

  2. Saint Louis University, St. Louis, MO, USA

    Michael G. Vaughn

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  1. Dylan B. Jackson
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Correspondence to Dylan B. Jackson.

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Dylan B. Jackson and Michael G. Vaughn declare that they have no conflict of interest.

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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.

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Jackson, D.B., Vaughn, M.G. Sleep and Preteen Delinquency: Is the Association Robust to ADHD Symptomatology and ADHD Diagnosis?. J Psychopathol Behav Assess 39, 585–595 (2017). https://doi.org/10.1007/s10862-017-9610-1

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