Abstract
To construct a path model addressing influences of diabetes distress, self-efficacy of injecting insulin, resilience and decisional balance of injecting insulin to quality of life (QoL) in insulin-treated patients with type 2 diabetes (T2DM). Insulin regimens more negatively impact QoL than oral medication treatments in patients with T2DM. Understanding the factors and influencing pathways associated with subsequent QoL will help nurses design timely interventions to improve QoL of insulin-treated T2DM patients. A 9-month prospective design was employed in this study. Self-reported questionnaires were used to collect data from 185 insulin-treated T2DM patients. At baseline, diabetes distress and self-efficacy of injecting insulin were collected, while QoL, resilience and decisional balance of injecting insulin were collected 9months later. Data were collected from February 2017 to February 2018. Structural equation modelling was used for analysis. This study was conducted based on the STROBE. Low baseline diabetes distress and high 9-month decisional balance of injecting insulin directly associated with high 9-month QoL. High baseline self-efficacy of injecting insulin and high 9-month resilience directly associated with high 9-month decisional balance of insulin injection and indirectly associated with high 9-month QoL. High baseline diabetes distress directly and indirectly associated with poor 9-month QoL. Diabetes distress, self-efficacy of injecting insulin, resilience and decisional balance of injecting insulin play different roles in associating with QoL in insulin-treated T2DM patients. Nurses could provide educational programs focusing on enhancing decisional balance of injecting insulin to improve QoL in insulin-treated patients. Improving self-efficacy of injecting insulin and resilience could be promising strategies to improve the decisional balance of injecting insulin. More timely assessment of diabetes distress and intervention might be powerful strategies to improve subsequent QoL in these patients.
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