Sleep Treatment Outcome Predictors: A Pilot Study (STOP-pilot)
Sleep Treatment Outcome Predictors: A Pilot Study (STOP-pilot)
Insomnia occurs frequently causing a substantial burden to society (1). Historically, insomnia has been considered as secondary to a handful of other psychiatric disorders, such as depression and anxiety - but it is now clear that this disorder is associated with a wide range of psychiatric conditions and may actually precede and predict their development and severity (e.g. 2). Treating insomnia has been posited to hold the promise of reducing or preventing the development of co-morbid problems - although this possibility needs to be rigorously tested.
Cognitive behavioural therapy (CBT) is an effective treatment for disturbed sleep, specifically insomnia, in adults (3) and is recommended by NICE for the management of long-term sleep problems. This treatment is more accessible than ever before given recent ground-breaking internet initiatives - such as the Sleepio programme (see: https://www.sleepio.com/home/), which was developed by one of the collaborators (Colin Espie) and has yielded encouraging results (4).
Despite the importance of CBT for treating disturbed sleep and the finding that it leads to a good outcome for the majority of sufferers, some people fail to respond to this treatment. For example, research cited on the Sleepio website notes that around 70% of those with even very long term sleep difficulties experience long-term improvements from the treatment, meaning that 30% do not (see 4). Understanding more about who does and does not respond holds the promise of improving or tailoring treatments for insomnia.
The study proposed here builds on recent work by one of the researchers who has been exploring demographic (5), clinical (e.g. 6) and most uniquely genetic (e.g. 7); and epigenetic (e.g. 8) predictors of psychological treatment response (coining the term Therapygenetics, see, 7). While these predictors are individually only likely to explain a small proportion of the variance of treatment outcome, understanding these multiple risks and their interaction is the best way to consider this issue. The study addressed here is a pilot study, necessary to demonstrate feasibility of utilising a sleep intervention application in an unselected sample of young adults, prior to applying for grant funding to undertake a larger but similar behavioural genetics study in the future.
The main aim of this pilot study is to test the feasibility of the study design, by investigating whether unselected participants show an improvement in sleep quality after taking the intervention. Participation and drop out rates as well acceptability of the intervention in a non-clinical population will also be investigated.
Research Questions:
Does the online CBT intervention improve sleep quality in a non-clinical, unselected sample?
How feasible is it to run this study on a non-clinical sample? This will include investigating response rate, participant drop-out, and treatment accessibility.
The investigators will also offer perform preliminary investigations into:
Does improving sleep quality have implications for associated phenotypes? Specifically the investigators will examine symptoms of anxiety, depression, attention-deficit hyperactivity disorder (ADHD), psychosis, and well-being.
Which demographic, clinical, genetic, and epigenetic factors predict treatment outcome for sleep problems?
Research questions 3) and 4) will be primary aims in the main study, but will constitute secondary aims in the pilot study as there won't be the statistical power to fully address these questions.
Inclusion
Exclusion