Measuring (hyper)activity in ADHD using Runscribe sensors

Background

Attention deficit hyperactivity disorder (ADHD) is a chronic, neuropsychiatric disorder affecting 3-5% of school age children in the UK (Ford et al,2003). It is reported that by 2011 in the USA, 11% (6.4 million) of school-aged children, compared to 7.8% in 2003, had received a diagnosis of ADHD, and 69% of those were taking medication. This suggests that from 2003 to 2011, two million more American children were diagnosed and one million more were taking medication (Visser 2014). Over the last 30 years the numbers treated for ADHD in the UK have also risen, from 0.5 per 1000 to over 3.0 per 1000 (NICE 2013), and more recently in 2003 to 2008, from 4.8 to 9.2 for 6- to 12-year olds and from 3.6 to 7.4 for13-17 year olds (McCarthy 2012).

Children and young people (YP) with ADHD typically present with symptoms of inattention, impulsivity, and hyperactivity, which can have a profound impact on the individual, their family, academic performance, intellectual functioning, social skills, and social relationships from preschool to adult life (Faraone et al, 2006; Harpin 2005; Biederman and Faraone 2005; Klein et al, 2012).

A diagnosis of ADHD (for ICD 10) necessitates individuals to demonstrate, in more than one setting, a minimum number of symptoms in all three dimensions (inattention, hyperactivity, and impulsivity; WHO 1992). The DSM-IV and DSM-5 define only two dimensions (with hyperactivity and impulsivity symptoms included in the same dimension (NICE 2009).

Current service provision for individuals with ADHD involves a complex assessment and treatment process, which necessitates clinicians, parents, and education providers to complete multiple questionnaires and interviews detailing their subjective account of symptoms. However, there are no routinely used objective measures for the key dimension of hyperactivity. 

This research will measure activities carried out by a child or young person with ADHD over 24 hours using Runscribe sensors. These data will provide activity data (accelerometry and orientation) and will be compared to an aged matched control to analyse the difference in activity levels in multiple settings such as at home and at school. This will provide the patient, the parent(s), teachers and clinicians vital data to infer heightened levels of activity over 24+ hours. This has the potential to provide a detailed picture of hyperactivity levels at different points of the day and crucially for

clinicians, detail when their patient’s medication is more or less effective. This will answer two key questions: Is my patient hyperactive compared to aged matched controls? How effective is their medication for controlling hyperactivity symptoms over a 24-hour period? This could be provided by a simple graph of (hyper)activity levels over time.

Aim:

To explore (hyper)activity behaviour amongst children/young people living with ADHD using Runscribe sensors and compare with age matched controls.

The benefits of this research:

By asking children / young people to wear the sensors at the point of assessment or for follow up assessments, clinicians can ask:

·      Is my patient hyperactive compared to age matched controls?

·      How effective is their medication for controlling hyperactivity symptoms over a 24-hour period?

Meet the team

Dr Jack Parker (Project lead, University of Sheffield): Jack.parker@sheffield.ac.uk

Miss Lauren Powell (Research Associate, University of Sheffield): L.a.powell@sheffield.ac.uk

Dr Ben Heller (Biomechanist, Sheffield Hallam University): Ben.heller@shu.ac.uk

Ms Eileen Schweiss (Data analyst, Rubscribe): Eileen@runscribe.com