Knowledge Transfer: From Indentify Determinants of Poor Sleep in Nursing Homes to Developing and Implementing Solutions Supported By Technology

Friday, July 18, 2014: 5:45 PM
Room: Booth 40
Oral Presentation
Ingrid EYERS , Department of Sociology, University of Surrey, Guildford, United Kingdom
This paper presents the process of knowledge transfer from within a research project into the development of best practice recommendations. It will show how research findings inform practice development involving the use of technology and how this can improve night time care provision in nursing homes. Building on research conducted in England, best practice recommendations have been developed to improve sleep in nursing homes.

An extensive study of 10 nursing homes in England aiming to identify the determinants of poor sleep incorporated a collection of quantitative and qualitative data from 183 residents aged 65-100 and 40 members of staff. One of the key findings from the study was related to sleep disruption caused by regular, physical checking of the bedclothes to establish if they needed changing. A recommendation from the study was to enhance person-centred care at night by the use of technology, e.g. sensors in the mattress. In this instance the use of sensors in a mattress can for example indicate whether the bed is wet or dry and when the resident is more restless, implying that they are not in a deep sleep phase. Care supported by technology can be provided when it is needed and suits the individual sleep pattern of residents. Consequently restorative sleep can be achieved and dignity maintained.  Thus the evidence based knowledge and understanding related to a determinant of poor sleep is transferred to the development of care giving procedures involving the use of technology. This process can be seen to improve care delivery and result in an outcome which acknowledges the individuality of night time sleep and maintains personal dignity of older people.

The research was supported by the New Dynamics of Ageing initiative, a multidisciplinary research programme funded by AHRC, BBSRC, EPSRC, ESRC and MRC (RES-339-25-0009)