Chronic pain is a widespread problem, especially in the older population, and can affect various aspects of daily living. At a time when it has been acknowledged that the population is increasingly ageing, research regarding the effects of chronic pain on the daily living of older adults is essential. Furthermore, the development of innovative technology is changing the way that much research is being conducted, and can lead to the retrieval of novel information, using a fresh approach. The adoption of this technology in the field of chronic pain research has the potential to examine various aspects of the daily living of older adults living with chronic pain using a different approach to previous research.This study is underpinned by a Critical Realist ontology and Hermeneutic epistemology and follows a Generic Qualitative Research methodology (Caelli, et al., 2003). The aim of the study was not to generalise the findings but to gather a deep theoretical description of the outcomes and offer an explanation of these findings based on an analysis of the multiple research methods used within the study.This study had two main aims and was split into two sections according to the aims. Firstly, Part A of this study aimed to explore a range of day-to-day patterns and experiences of functioning in older adults suffering from chronic pain. Part B aimed to explore the usability, acceptance and experience of the technology used to measure functioning as part of the first aim of this study. Part B also aimed to look at the practicalities the participants were faced with when using the technology.A mixed methods design was used for Part A in which 15 older adults (65+) living with chronic pain (pain >3 months) took part in an in-depth study lasting seven days. As well as the 15 core participants that took part in the study, two older adults (65+) without chronic pain and two younger adults (<65) with chronic pain took part in the study in order to provide some insight into the effects of either pain, or age, on functioning. Part A used four data collection techniques to gather data upon the daily functioning of older adults with chronic pain; the Daily Reconstruction Method diary (Kahneman, Krueger, Schkade, Schwarz, Stone, 2004), the Sensecam (also known as the Vicon Revue, Vicon©), the LifeShirt (Vivometrics Inc) and a semi-structured interview. However, although the LifeShirt was validated, as part of this PhD, and used throughout the study, the gathered data was not analysed due to multiple problems with the data.The Daily Reconstruction Method, Sensecam and the semi-structured interview were each analysed separately before the results of the Daily Reconstruction Method and Sensecam were integrated into the themes derived from the semi-structured interviews. The integrated results led to the development of two themes, each with sub-themes; ‘effect on daily living’ and ‘managing pain and functioning’.The themes from Part A highlighted the way in which pain affected functioning and the modifications to daily functioning as a result of chronic pain. The way in which individuals perceived the management of their own pain and functioning, as well as strategies and assistive devices to manage pain and functioning were also discussed. This study has furthered current knowledge due to the idiographic nature of the study, as well as multiple, novel, data collection tools used, adding additional details to how tasks have been modified, reduced, or terminated.Part B of this study used the Unified Theory of Acceptance and Use of Technology (UTAUT, Venkatesh, et al., 2003), the Flow-State Scale (Jackson & Marsh, 1996) and semi-structured interviews to explore participants’ use of both the Sensecam and LifeShirt. The questionnaires and interviews were carried out with all of the individuals that carried out Part A of this research. From the semi-structured interviews two main themes were reported, each with sub-themes; ‘expectations an
| Date of Award | 17 Sept 2014 |
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| Original language | English |
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| Awarding Institution | |
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| Supervisor | Denis Martin (Supervisor), Derek Jones (Supervisor) & Patricia Schofield (Supervisor) |
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