Treatment for Sleep Problems in Children with Autism and Caregiver Spillover Effects
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Sleep problems in children with autism spectrum disorders (ASD) are under-recognized and under-treated. Identifying treatment value accounting for health effects on family members (spillovers) could improve the perceived cost-effectiveness of interventions to improve child sleep habits. A prospective cohort study (N = 224) was conducted with registry and postal survey data completed by the primary caregiver. We calculated quality of life outcomes for the child and the primary caregiver associated with treatments to improve sleep in the child based on prior clinical trials. Predicted treatment effects for melatonin and behavioral interventions were similar in magnitude for the child and for the caregiver. Accounting for caregiver spillover effects associated with treatments for the child with ASD increases treatment benefits and improves cost-effectiveness profiles.
KeywordsAutism spectrum disorder Child health Caregiver health Child sleep habits Quality adjusted life year Cost-effectiveness analysis
The project was supported by a Grant (R01MH089466) with JMT and KAK serving as principal investigators and a Grant (R03MH102495) with NP as the principal investigator both from the National Institute of Mental Health. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health. The authors acknowledge the members of the Autism Treatment Network for use of the data. The data for the study were collected as part of the Autism Treatment Network, a program of Autism Speaks. Further support came from a cooperative agreement (UA3MC11054) from the US Department of Health and Human Services, Health Resources and Services Administration, Maternal and Child Health Research Program, to the Massachusetts General Hospital. The work described in this article represents the independent efforts of the authors with no restrictions from the funding source or the Autism Treatment Network. None of the authors of this study reported a conflict of interest associated with the preparation of the manuscript. Maria Melguizo, Nupur Chowdhury, Rebecca Rieger and Latunja Sockwell provided excellent research assistance.
Compliance of ethical standards
Conflict of interest
The authors declare they have no conflict of interest associated with the manuscript.
Human and animal rights
All procedures performed in studies involving human participants were in accordance with the ethical standard of the institutional research committees of the participating institutions and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev). Washington, DC: American Psychiatric Association.Google Scholar
- Arnold, L. E., Vitiello, B., McDougle, C., Scahill, L., Shah, B., Gonzalez, N. M., et al. (2003). Parent-defined target symptoms respond to risperidone in RUPP autism study: customer approach to clinical trials. Journal of the American Academy of Child and Adolescent Psychiatry, 42, 1443–1450.CrossRefPubMedGoogle Scholar
- Bayley, N. (2006). Bayley scales of infant and toddler development–third edition. San Antonio, TX: Harcourt Assessment.Google Scholar
- Bureau of Labor Statistics, U. S. D. o. L. (2014). American time use survey—2013 results (Rep. No. USDL-14-1137). http://www.bls.gov/news.release/pdf/atus.pdf
- Cortesi, F., Giannotti, F., Sebastiani, T., Panunzi, S., & Valente, D. (2012). Controlled-release melatonin, singly and combined with cognitive behavioural therapy, for persistent insomnia in children with autism spectrum disorders: A randomized placebo-controlled trial. Journal of Sleep Research, 21, 700–709.CrossRefPubMedGoogle Scholar
- Glasgow, R. E., & Steiner, J. F. (2012). Comparative effectiveness research to accelerate translation: Recommendations for an emerging field of science. In R. C. Brownson, G. A. Colditz, & E. K. Proctor (Eds.), Dissemination and implementation research in health (pp. 72–92). New York, NY: Oxford University Press.Google Scholar
- Gold, M., Siegel, J., Russell, L., & Weinstein, M. (1996). Cost effectiveness in health and medicine. New York, NY: Oxford University Press.Google Scholar
- Kaplan, R., & Anderson, J. (1996). The general health policy model: An integrated approach. In B. Spiker (Ed.), Quality of life and pharmacoeconomics in clinical trials (2nd ed., pp. 309–322). Philadelphia, PA: Lippincott-Raven Publishers.Google Scholar
- Kelly, A., Haddix, A., Scanlon, K., Helmick, C., & Mulinare, J. (1996). Cost-effectiveness of strategies to prevent neural tube defects. In J. E. Siegel, L. B. Russell, M. C. Weinstein, & M. R. Gold (Eds.), Cost-effectiveness in health and medicine (pp. 312–349). New York, Oxford: Oxford University Press.Google Scholar
- Levy, S. E., Giarelli, E., Lee, L. C., Schieve, L. A., Kirby, R. S., Cunniff, C., et al. (2010). Autism spectrum disorder and co-occurring developmental, psychiatric, and medical conditions among children in multiple populations of the United States. Journal of Developmental and Behavioral Pediatrics, 31, 267–275.CrossRefPubMedGoogle Scholar
- Meltzer, D., & Smith, P. (2012). Theoretical issues relevant to the economic evaluation of health technologies. In M. V. Pauly, T. G. McGuire, & P. P. Barros (Eds.), Handbook of health economics (Vol. 2, pp. 433–470). Oxford, UK: North Holland.Google Scholar
- Mullen, E. (1997). Mullen Scales of early learning. Los Angeles, CA: Western Psychological Services.Google Scholar
- Prosser, L. A., Lamarand, K., Gebremariam, A., & Wittenberg, E. (2015). Measuring family HRQoL spillover effects using direct health utility assessment. Medical Decision Making, 35, 81–93.Google Scholar
- Ramsey, J. (1969). Tests for specification error in classical linear least squares regression analysis. Journal of the Royal Statisical Society Series B, 31, 350–371.Google Scholar
- Simonoff, E., Pickles, A., Charman, T., Chandler, S., Loucas, T., & Baird, G. (2008). Psychiatric disorders in children with autism spectrum disorders: Prevalence, comorbidity, and associated factors in a population-derived sample. Journal of American Academy of Child Adolescent Psychiatry, 47, 921–929.CrossRefGoogle Scholar
- The National Institute for Health and Care Excellence. (2013). Guide to the methods of technology appraisal 2013 London. England: The National Institute for Health and Care Excellence.Google Scholar
- Tilford, J. M. & Payakachat, N. (2014). Progress in measuring family spillover effects for economic evaluations. Expert Review of Pharmacoeconomics & Outcomes Research, 16, 1–4.Google Scholar
- Tilford, J. M., Payakachat, N., Kovacs, E., Pyne, J. M., Brouwer, W., Nick, T. G., et al. (2012). Preference-based health-related quality-of-life outcomes in children with autism spectrum disorders: A comparison of generic instruments. Pharmacoeconomics, 30, 661–679.PubMedCentralCrossRefPubMedGoogle Scholar
- Ungar, W., & Gerber, A. (2010). The uniqueness of child health and challenges to measuring costs and consequences. In W. Ungar (Ed.), Economic evaluation in child health. New York: Oxford University Press.Google Scholar