Self-care is essential for patients with diabetes mellitus. Both clinicians and researchers must be able to assess the quality of that self-care. Available tools have various limitations and none are theoretically based. The aims of this study were to develop and to test the psychometric properties of a new instrument based on the middle range-theory of self-care of chronic illness: the Self-Care of Diabetes Inventory (SCODI). Forty SCODI items (5 point Likert type scale) were developed based on clinical recommendations and grouped into 4 dimensions: self-care maintenance, self-care monitoring, self-care management and self-care confidence based on the theory. Content validity was assessed by a multidisciplinary panel of experts. A multi-centre cross-sectional study was conducted in a consecutive sample of 200 type 1 and type 2 diabetes patients. Dimensionality was evaluated by exploratory factor analyses. Multidimensional model based reliability was estimated for each scale. Multiple regression models estimating associations between SCODI scores and glycated haemoglobin (HbA1c), body mass index, and diabetes complications, were used for construct validity. Content validity ratio was 100%. A multidimensional structure emerged for the 4 scales. Multidimensional model-based reliabilities were between 0.81 (maintenance) and 0.89 (confidence). Significant associations were found between self-care maintenance and HbA1c (p = 0.02) and between self-care monitoring and diabetes complications (p = 0.04). Self-care management was associated with BMI (p = 0.004) and diabetes complications (p = 0.03). Self-care confidence was a significant predictor of self-care maintenance, monitoring and management (all p < 0.0001). The SCODI is a valid and reliable theoretically-grounded tool to measure self-care in type 1 and type 2 DM patients.

The escalating prevalence of diabetes mellitus may benefit from add-on therapeutic approaches. Given the recognized need for an updated synthesis of the literature, this systematic review and meta-analysis aimed to synthesize and critically assess the available randomized controlled trials (RCTs) that investigate the efficacy of probiotics and synbiotics on glycemic control in patients with Type 1 (T1DM) and Type 2 (T2DM) diabetes mellitus. Comprehensive searches were conducted on PubMed, Embase, CINAHL, Scopus, and Web of Science, focusing on adults with T1DM or T2DM. All comparators were deemed eligible. Primary outcomes included changes in glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), and insulin levels. Only RCTs were included, and the Cochrane RoB2 tool assessed the risk of bias. Random-effect models facilitated data analysis, supplemented by sensitivity, subgroup analyses, and meta-regressions. A total of 537 records were screened, resulting in 41 RCTs for analysis, which comprises 2991 (54% females) patients with diabetes. The meta-analysis revealed statistically significant improvements in HbA1c (standardized mean difference (SMD) = -0.282, 95% CI: [-0.37, -0.19], p < 0.001), FPG (SMD = -0.175, 95% CI: [-0.26, -0.09], p < 0.001), and insulin levels (SMD = -0.273, 95% CI: [-0.35, -0.20], p < 0.001). A medium degree of heterogeneity between studies was found in HbA1c (I² = 62.5%), FPG (I² = 71.5%), and insulin levels (I² = 66.4%) analyses. Subgroup analyses indicated that the efficacy varied based on the type of strains used and the country. Multispecies strains were particularly effective in improving HbA1c levels. The study findings suggest that probiotics and synbiotics may be effective as complementary therapies for managing diabetes. Additionally, the study underscores the need for further tailored research that considers variables such as strain types and geographical factors to deepen the understanding of the role of these interventions in diabetes care. PROSPERO (CRD42023396348).

The Self-care of Diabetes Inventory (SCODI) is a theory-based tool that measures self-care, a key strategy in the appropriate treatment of diabetes. However, despite the clinical differences between people with Type 1 Diabetes Mellitus (T1DM) and Type 2 Diabetes Mellitus (T2DM), the psychometric properties of the SCODI were only tested in mixed samples. This study aims to test the psychometric performances of the SCODI in two separate groups of adults with T1DM and T2DM. This is a secondary analysis from two previous multicentre cross-sectional observational studies involving patients with T1DM (n = 181) and T2DM (n = 540). We tested dimensionality with confirmatory factor analysis and reliability with a multidimensional model-based coefficient for every scale of the SCODI: self-care maintenance, self-care monitoring, self-care management, and self-care self-efficacy. We found that the SCODI showed the same dimensionality, with minimal variation in factor loadings for each factor and each scale among T1DM and T2DM groups. High reliability for each scale in both groups was also found (self-care maintenance: T1DM = 0.86, T2DM = 0.83; self-care monitoring: T1DM = 0.84, T2DM = 1.00; self-care management: T1DM = 0.87, T2DM = 0.86; self-care self-efficacy: T1DM = 0.88; T2DM = 0.86). The SCODI can be used for measuring self-care in people with T1DM, T2DM, or mixed groups using identical scoring procedures. Considering the well-known differences between Type 1 and Type 2 diabetes diseases and patients’ characteristics, our results support the generalizability of the self-care theory on which the instrument is based.

Background: In Italy, Diagnosis-Related Groups (DRGs) have been adopted for hospital services reimbursement. In some Italian regions, nurse staffing allocation is purely volume-based, with different minutes/patient/day categories determined by the type of hospital ward. The Information System of Nursing Performance (SIPI) is a valid and reliable tool assessing nursing care complexity as an indicator of the actual nursing care demand. Evidence is lacking about the ability of current resource allocation methods to account for the nursing care demand. Objective: To evaluate the association between (1) DRG rates and nursing care complexity and (2) hospital ward categories of nurse staffing and nursing care complexity. Methods: All patients discharged from the medical department of an Italian hospital over a data collection period were eligible. To assess the association between nursing care complexity (SIPI) and DRGs, the distribution of the DRG rate (median and first–third quartile) was compared for cases with high or low complexity. To evaluate the association between nursing care complexity (SIPI) and nurse staffing, the frequency of high complexity within nurse staffing categories (120/180/240 min/patient/day) was compared. Because the sample was very large, methods of statistical inference were not applied, and only descriptive measures were reported. Results: 6872 hospitalizations were included. The median DRG rate for high and low complexity admissions were very similar (EUR 3536 and EUR 3285, respectively). The proportion of admissions with high complexity decreased for wards with higher staffing allocation rates. Conclusion: DRG reimbursement and the nurse staffing allocation systems were ineffective in accounting for nursing care complexity. The SIPI could help identify areas requiring more financial and staffing resources for nursing care.