The Inside Scoop: New Publications

New publications include:

Child Development

Anagnostou E, Aman MG, Handen BL, Sanders KB, Shui A, Hollway JA, Brian J, Arnold LE, Capano L, Hellings JA, Butter E, Mankad D, Tumuluru R, Kettel J, Newsom CR, Hadjiyannakis S, Peleg N, Odrobina D, McAuliffe-Bellin S, Zakroysky P, Marler S, Wagner A, Wong T, Macklin EA, Veenstra-VanderWeele J. Metformin for Treatment of Overweight Induced by Atypical Antipsychotic Medication in Young People With Autism Spectrum Disorder: A Randomized Clinical Trial. JAMA Psychiatry. 2016 Sep 1;73(9):928-37. doi: 10.1001/jamapsychiatry.2016.1232. Impact Factor 14.441

  • Senior Clinician Scientist and Canada Research Chair, Evdokia Anagnostou evaluated the efficacy of Metformin for weight gain associated with atypical antipsychotic medications in children and adolescents with ASD, aged 6 to 17 years. Dr. Anagnostou’s international team included 4 sites in Canada and across the United States.  209 potential participants were screened, and of those, 61 participants were randomized to receive either Metformin or placebo.  The team uncovered that Metformin may be effective in decreasing weight gain associated with atypical antipsychotic use and is well tolerated by children and adolescents with ASD.

Brian J, Smith I, Zwaigenbaum L, Roberts W, Bryson S. The Social ABCs Caregiver-Mediated Intervention for Toddlers with Autism Spectrum Disorder: Feasibility, Acceptability, and Evidence of Promise from a Multisite Study. Autism Res. 2016 Aug;9(8):899-912. doi: 10.1002/aur.1582. Epub 2015 Dec 21. Impact Factor 4.432

Ozel S, Switzer L, Macintosh A, Fehlings D. Informing evidence-based clinical practice guidelines for children with cerebral palsy at risk of osteoporosis: an update. Dev Med Child Neurol. 2016 Sep;58(9):918-23. doi: 10.1111/dmcn.13196. Epub 2016 Jul 20. Impact Factor 3.668

Brian J, Bryson SE, Smith IM, Roberts W, Roncadin C, Szatmari P, Zwaigenbaum L. Stability and Change in Autism Spectrum Disorder Diagnosis from Age Three to Middle Childhood in a High-Risk Sibling Cohort. Autism. 2016 Oct;20(7):888-92. doi: 10.1177/1362361315614979. Epub 2015 Dec 18. Impact Factor 3.483

  • Clinician Investigator, Jessica Brian and collaborators examined the stability and change of the diagnostic classification of younger siblings of children with autism spectrum disorders from age 3 to middle childhood. The study found that 89.6% of the siblings, whose clinical diagnoses were informed by two clinical gold standards, namely the autism diagnostic observation schedule (ADOS and ADOS-2) and the autism diagnostic interview – revised (ADI-R) maintained their diagnostic classification between 3 and 9 years of age.  Some siblings who did not initially meet criteria on these tools, but showed signs of a broader autism phenotype were later diagnosed with ASD; thus signifying a change in the diagnostic classification. This study was the first report of diagnostic stability and change in siblings with ASD beyond toddlerhood, and showed the importance of continued surveillance of this group.        

Brian J, Doyle-Thomas K, Baribeau D, Anagnostou E. Novel mechanisms and treatment approaches in autism spectrum disorder. Discov Med. 2016 Aug;22(119):47-54. Impact Factor 3.139

McDougall J, DeWit DJ, Nichols M, Miller L, Wright FV. Three-year trajectories of global perceived quality of life for youth with chronic health conditions. Qual Life Res. 2016 Dec;25(12):3157-3171. Epub 2016 Jul 5. Impact Factor 3.081


Ballantyne M, Benzies KM, McDonald S, Magill-Evans J, Tough S. Risk of developmental delay: Comparison of late preterm and full term Canadian infants at age 12 months. Early Hum Dev. 2016 Oct;101:27-32. doi: 10.1016/j.earlhumdev.2016.04.004. Epub 2016 Jul 9. Impact Factor 2.271


Cheung S, Han E, Kushki A, Anagnostou E, Biddiss E. Biomusic: An Auditory Interface for Detecting Physiological Indicators of Anxiety in Children. Front Neurosci. 2016 Aug 30;10:401. doi: 10.3389/fnins.2016.00401. eCollection 2016.

  • Scientist Elaine Biddiss, in collaboration with Davie Scientist Azadeh Kushki and Senior Clinician Scientist Evdokia Anagnostou investigated the ability of Biomusic, an auditory interface which maps physiological signals to music to detect anxiety in participants. Biomusic samples were generated from physiological recordings of typically developing children and children with autism spectrum disorders during relaxing and anxiety-provoking conditions. Adult participants were then asked to identify “anxious” and “relaxed” states by listening to the samples. Participants were able to form an early and accurate impression of the anxiety state within 12 seconds of hearing the Biomusic, with very little training and no contextual information. The team concluded that Biomusic holds promise for monitoring, communication, and biofeedback systems for anxiety management.     

Zeid EA, Sereshkeh AR, Chau T. A pipeline of spatio-temporal filtering for predicting the laterality of self-initiated fine movements from single trial readiness potentials.  J Neural Eng. 2016 Dec;13(6):066012. Epub 2016 Oct 20. Impact Factor 3.493

Myrden A, Chau T. Towards psychologically adaptive brain-computer interfaces. Journal of Neural Engineering. 2016 Dec 31;13(6):066022 (12 pp) Impact Factor 3.493

Saghir H, Chau T, Kushki A. Clustering of time-evolving scaling dynamics in a complex signal. Physical Review E. 2016 Jul;94(1-1):012220. Impact Factor 2.3.

Participation and Inclusion

McPherson AC, King G, Rudzik A, Kingsnorth S, Gorter JW. Ontario Independence Program Research (OIPR) team. Optimizing life success through residential immersive life skills programs for youth with disabilities: study protocol of a mixed-methods, prospective, comparative cohort study. BMC Pediatr. 2016 Sep 6;16(1):153. doi: 10.1186/s12887-016-0694-7. Impact Factor 2.326

King G, Kingsnorth S, McPherson A, Jones-Galley K, Pinto M, Fellin M, Timbrell N, Savage D. Residential immersive life skills programs for youth with physical disabilities: A pilot study of program opportunities, intervention strategies, and youth experiences. Res Dev Disabil. 2016 Aug;55:242-55. doi: 10.1016/j.ridd.2016.04.014. Epub 2016 May 3. Impact Factor 2.181

  • Senior Scientist and Canada Research Chair, Gillian King and team described the creation and validation of six simulations concerned with effective listening and interpersonal communication in pediatric rehabilitation.  The simulations involved clinicians from various disciplines, were based on clinical scenarios related to client issues, and reflected core aspects of listening/communication. Each simulation had a key learning objective, thus focusing clinicians on specific listening skills. The article contributed an in-depth understanding of procedures that could be used by others to establish authenticity, rate complexity, and design scenarios to illuminate the key elements required by standard patients (actors) in simulations.

King G, Rigby P, Avery L. Revised Measure of Environmental Qualities of Activity Settings (MEQAS) for youth leisure and life skills activity settings. Disability and Rehabilitation 38:15, 1509-1520, DOI: 10.3109/09638288.2015.1103792 Impact Factor 2.135

Lindsay S, Fellin M, Cruickshank H, McPherson A, Maxwell J. Youth and parents' experiences of a new inter-agency transition model for spina bifida compared to youth who did not take part in the model. Disabil Health J. 2016 Oct;9(4):705-12. doi: 10.1016/j.dhjo.2016.05.009. Epub 2016 May 27. Impact Factor: 1.579

King G, Orchard C, Khalili H, Avery L. Refinement of the Interprofessional Socialization and Valuing Scale (ISVS-21) and Development of 9-Item Equivalent Versions. J Contin Educ Health Prof. 2016 Summer;36(3):171-7. doi: 10.1097/CEH.0000000000000082. Impact Factor 1.406