<b>PhD Thesis: Insights under the skin - DATA SETS (QUANT / QUAL / INTEGRATION)</b>
<p dir="ltr"><b>PhD Thesis: Insights under the skin - sensing the journey. Using mixed methods research to explore the biopsychosocial impact and experiences of people living with type 1 diabetes using continuous glucose monitoring technology - DATA SET (QUANT / QUAL / INTEGRATION)</b></p><p dir="ltr"><b><u>Files Included: </u></b></p><ul><li>Anonymised data 11/01/2024 (quantitative data set - PROMs and sensor data)</li><li>Scans per day (quantitative data set)</li><li>PhD study data Reorganised - March 24 (PROMs and sensor data - SPSS data file)</li><li>PhD Main output (PROMs and Sensor Data - SPSS analysis output) </li><li>QUAL demographics (SPSS data file)</li><li>QUAL demographics output (SPSS analysis output) </li><li>QUAL data and analysis (NVivo R14.23.2)</li><li>Integration 1 (Excel file - full convergence of data sets) </li><li>Traffic light grid integration (Word - Convergence coding matrix)</li></ul><p dir="ltr"><b><u>Abstract </u></b>Type 1 diabetes (T1D) is associated with an increased risk of morbidity and mortality. Treatment involves life-long exogenous insulin to prevent complications in the short and long term. Continuous glucose monitoring (CGM) technologies such as Freestyle Libre 2 (FSL2) are now offered to help people with self-management.</p><p dir="ltr">A systematic review was conducted to establish whether person reported outcome measures (PROMs) were associated with clinical outcomes in randomised control trials (RCTs) of CGM for adults with T1D. A mixed methods explanatory sequential design was conducted. Quantitatively assessed changes in PROMs and sensor data after six months of using FSL2 were collected. The subsequent qualitative phase explored the experiences of people living with T1D using FSL2. Systematic review data, PROMs, sensor data and qualitative data were integrated using a triangulation protocol.</p><p dir="ltr">Key findings indicated a high level of satisfaction compared with finger-prick testing alongside modest improvements in diabetes distress and quality of life (QoL). However, changes in glucometrics derived from sensor data did not demonstrate improvement. Participants highlighted the complexity of diabetes management, and the duality of many concepts related to their perception of their own diabetes and the impact of this on their lives and sense of self. Five meta-themes were identified from triangulation of data:</p><ol><li>Access and onboarding shape outcomes</li><li>Embodied empowerment versus burden dialectic</li><li>The embodied trust plateau</li><li>Bridging the diabetes tech translational gap</li><li>The social ecosystem matters</li></ol><p dir="ltr">Findings indicated several areas for improvement to enhance user experience: improved onboarding and education, greater device reliability, and support with managing the burden of data.<b> </b>The sensor has differential benefits and limitations according to the experiences and preferences of users. Person-centred approaches are recommended for the introduction and use of technology to support individuals in better self-managing their T1D and improving their QoL.</p>
