Despite an increasing focus on health literacy in the clinical setting and in the literature, there is still ongoing debate about its influence on diabetes self-management. The aim of the study was to examine the relationships of sociodemographic, clinical, and psychological factors on health literacy and diabetes self-management. A cross-sectional survey was undertaken on 224 patients with type 2 diabetes at two diabetes centres in Sydney, Australia. Findings showed that people with low health literacy were more likely to (a) have lower educational attainment; (b) be migrants; and (c) have depressed mood. Unexpectedly, those who met HbA1c threshold of good glucose control were more likely to have low health literacy. Predictors of low diabetes self-management included (a) younger age group (AOR: 2.58, 95% CI: 1.24–4.64); (b) having postsecondary education (AOR: 2.30, 95% CI: 1.05–5.01); (c) low knowledge of diabetes management (AOR: 2.29, 95% CI: 1.25–4.20); and (d) having depressed mood (AOR: 2.30, 95% CI: 1.30–4.06). The finding that depressed mood predicted both low health literacy and low diabetes self-management stresses the importance of screening for depression. Increasing people's understanding of diabetes self-management and supporting those with depression are crucial to enhance participation in diabetes self-management.

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The baseline audit revealed gaps between current practice and best practice. Through the implementation of a targeted education program and resource package, outcomes improved in the follow up audit. The findings indicated that engagement from multidisciplinary team members and consumers was effective in developing tailored education that improved knowledge of best practice. This was demonstrated by an increase in the percentage of compliance across the 10 criteria, although leaving room for more improvement. A policy has been developed for implementation and future audits are planned to measure whether improved practices have been sustained.

The objectives of this project were to conduct a retrospective healthcare records audit to determine the current compliance with evidence-based criteria regarding perioperative management of patients with diabetes; to identify barriers and facilitators to achieve compliance and develop strategies to address areas of non-compliance, and to implement evidence-based best practice recommendations for perioperative diabetic management and to assess the effectiveness of these strategies in improving compliance of perioperative diabetic management across five participating clinical areas in a large tertiary referral hospital.Introduction: Type 2 diabetes is a frequent co-morbidity among inpatients. It affects up to 20% of the general surgical population. Patients with diabetes undergoing surgery have a greater complication rate and length of hospital stay. Optimization of diabetes management of hospitalized patients will improve quality of care delivery, prevent postoperative complications and reduce length of stay and costs. However, there is limited knowledge and understanding of whether the current nursing practices concerning perioperative diabetic management meet the best practice recommendations outlined by JBI best practice criteria.Methods: A pre-post intervention healthcare record audit was conducted to examine compliance with nine best practice recommendations for perioperative diabetic management across five clinical areas. Following preintervention data analysis along with two focus group discussions, barriers to compliance with best practice criteria were identified and targeted strategies were used to address the issues. This project used the JBI Practice Application of Clinical Evidence System (PACES) and Getting Research into Practice (GRiP) tools.Results: Face to face education sessions and educational resources relating to perioperative diabetic management were delivered to nursing staff, which resulted in improved compliance for most of the audit criteria, with significant improvement in the areas of regular blood glucose level monitoring and nursing staff receiving education and training in the post-implementation analysis.