19992024

Research activity per year

Personal profile

Area of academic expertise - outline

I am an experienced Exercise Physiologist, although my expertise spans several related disciplines.  Much of my early work focussed on interventions aimed at reducing cardiovascular risk in those at risk of excess sedentariness.  More recently, my work has expanded to include the role of physical activity and exercise as both a treatment and preventative measure in long-term conditions, including Multiple Sclerosis, Long COVID, and ageing.  My research has focussed on using ultrasound to assess the structure and function of both the heart and vasculature.  Allied to this, I also use aspects of data science to support rapid and more nuanced processing of cardiac and vascular strain data.

 

More recently, I have developed research interests in the role of mobile technology in health interventions (mHealth). I am an experienced mobile app developer for iOS and Android and have developed and released multiple mobile apps for different interventions.  These include the ability to request and collect quantitative and qualitative data remotely. I also implement almost real-time activity-triggered messaging, using commercial activity trackers integrated as part of our mHealth physical activity interventions.

 

My past work includes exercise prescription and testing in athletes and clinical patients. I also have an extensive background in sports doping and androgenic anabolic steroid abuse.  This background has meant that I have also worked on media productions in both print and television in addition to research outputs.  I also have expertise in data synthesis, having published several meta-analyses, meta regressions, and ROC analyses.

Current research activities

I manage a large research group with several funded studies using mHealth interventions in individuals with or at risk of Long COVID.  These include using mHealth and activity tracking to implement a just-in-time adaptive intervention to help older individuals stay active during lockdowns. The CSO funds our group to use mobile techniques to perform symptom tracking of individuals who have recently tested positive for COVID to provide the first prospective data on the long COVID risk in Scotland.  The NIHR also funds us to develop a just-in-time adaptive intervention to help people with long COVID to better use pacing as a symptom management strategy. I also supervise a group of PhD students also funded by the CSO. They are investigating how we can better use mHealth approaches to track and understand symptoms in people with Multiple Sclerosis.

 

I also contribute to other research groups.  In my cardiac work, I contribute expertise in data processing to investigate cardiac and vascular health in various clinical and athletic conditions.   We are also contributing to the development and standardisation of these analysis techniques.  I also work with collaborators across the UK in a Healthy  Ageing Collaborative.  This work has focussed on using exercise or physical activity interventions to understand how ageing per se affects cardiovascular health.

Desired research direction

My future work is based on expanding and strengthening these research themes.  In the immediate future, we are working on funding for a project examining the role of mHealth to monitor activity in adults and children with debilitating fatiguing conditions.  Similarly, our group is also interested in better characterising the symptoms and needs of these groups. We are also interested in expanding mHealth technology to collect targeted qualitative and quantitative data using activity triggered reminders.  Our MS group will shortly be rolling out a research toolkit to support this cohort’s longitudinal tracking of symptoms.

 

In my cardiac/ageing research, we plan to assess the efficacy of a daily challenge in older adults. The aim is to determine if it results in improved functional capacity and cardiac and vascular health.  We are also looking at ways to expand the role of data science to further enhance the quality and speed of ultrasound analysis.

Target collaborative organisations

1. CSO

2. NIHR

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