Background: Sleep has been found to have an important restorative function. Any disturbance to sleep can be detrimental to both physical and mental health. Between 9-50% of adults with intellectual disabilities (ID) are reported to experience sleep disturbance. Support workers have a key role in identifying and responding to difficulties in the people they work with. Support workers' attributions towards the cause of these difficulties are crucial in mediating their decision to seek treatment. Their attributions may also mediate their adherence to a recommended treatment. Hence, their awareness and beliefs regarding sleep difficulties may influence their ability to recognise and seek help for sleep problems in adults they support. Method: This study utilised an exploratory vignette and questionnaire design. Questionnaires were given to 120 support workers, based in community settings, to measure their attributions to negative behaviour change and sleep problems. Support workers' attributional style was compared to their views on the acceptability of a variety of treatments for sleep disturbance. Support workers' own sleep quality was measured and compared to their attributions. Results: Support workers attributed negative behaviour change to sleep and mental health problems most strongly. Sleep problems were believed to be internal, uncontrollable and unintentional. Support workers were optimistic about treatment, particularly non-pharmacological treatments. Support workers' own sleep quality did not correlate with their attributions towards sleep problems or views on the different types of treatment. Conclusions: Support workers are optimistic that sleep problems in adults with ID can be treated, however further work is necessary to understand barriers to seeking out assessment and treatment for clients with ID.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:524057 |
| Date | January 2010 |
| Creators | Gervais, Mhairi |
| Publisher | University of Glasgow |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://theses.gla.ac.uk/2129/ |
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