Fields:

  • Data analytics
  • Neuroscience
  • Digital health

Location: UQ Centre for Clinical Research (Herston)

Type of student:

  • Both HDR and Extra-curricular
  • Honours students
  • 4 Unit Masters of Public Health (MPH) Student
  • PGY1: Post-graduate year 1
  • PGY2: Post-graduate year 2

Type of work:

  • Clinical work
  • Literature review
  • Qualitative methods
  • Statistical analysis

Brief synopsis:

This project involves two separate studies:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) study

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is characterised by the cardinal symptom of post-exertional malaise (PEM). PEM is experienced as marked, rapid physical and/or cognitive fatigue, or exacerbation of other symptoms such as musculoskeletal pain, headaches, sleep problems and impaired cognitive function, in response to minimal exertion. Individuals with ME/CFS vary widely in regards to the severity and particular cluster of symptoms they experience. However, research in this area has typically used a ‘group-based’ research design to study ME/CFS, which pays less attention to individual differences in symptomology, severity and experience. N-of-1 methods involve the repeated, quantitative and prospective measurement of an outcome in an individual over time. N-of-1 methods can be used to study PEM at the individual level. This project will involve a series of N-of-1 observational studies to explore patterns and predictors of ME/CFS symptoms over time. Daily data about fatigue and potential predictors will be collected three times per day for 6-12 weeks using an electronic diary with integrated accelerometer. Participants will receive detailed feedback about their data, which may help patients with self-management of their condition.

Multiple Sclerosis study

Fatigue is the most commonly reported, most disabling but least understood symptom experienced by patients with Multiple Sclerosis (MS). Patterns and predictors of fatigue may differ considerably from one individual to another but these differences are concealed in research using group-based designs (e.g. randomised controlled trials) that focus on average results for the group studied. Tools for assessing fatigue symptoms typically involve self-reported retrospective recall which can be subject to a number of memory biases. Furthermore, fatigue assessment is typically conducted on only one occasion, resulting in a limited understanding about fluctuations over time. N-of-1 methods involve the repeated, quantitative and prospective measurement of an outcome in an individual over time. N-of-1 methods can be used to identify patterns and predictors of fatigue that are unique to the individual. This project will involve a series of N-of-1 observational studies to explore fluctuations in fatigue and potential predictors (e.g. activity, sleep, mood) over time in MS. Daily data about fatigue and potential predictors will be collected three times per day for 6-12 weeks using an electronic diary with integrated accelerometer. Participants will receive detailed feedback about their data.

The student(s) will: (1) learn about a novel research method; N-of-1 methods play a key role in the movement towards personalised medicine, patient-centred health care and shared decision-making. (2) gain experience and skills in relation to conducting research involving patients with chronic disease.

For more information, please visit: https://clinical-research.centre.uq.edu.au/nikles-group or email the primary supervisor (suzanne.mcdonald@uq.edu.au).

Supervisor

Dr Suzanne McDonald

Dr Suzanne McDonald

Senior Research Technician
UQ Centre for Clinical Research