This paper systematically reviews published randomised controlled trials, to determine the educational focus and effectiveness of type 2 diabetes multi-component self-management interventions. PubMed, PsycINFO, Web of Science and reference lists of included studies were searched for English-language articles published 2000–2010. Descriptive information was summarised; when possible, effect sizes were calculated. Fourteen studies, described in 19 articles, were reviewed: six one-on-one interventions; six group interventions; two interventions comprising both intervention types. Four studies used learning as an intervention method; seven used learning and planning; three used learning, planning and practising. Self-management interventions seemed effective for diet, self-monitoring of blood glucose, knowledge and diabetes specific quality of life (QoL) there were mixed results for exercise and clinical outcomes. Findings showed that dietary behaviour seemed relatively easy to change with self-management interventions. Group interventions with a practise component had the greatest potential to improve metabolic control. Self-management interventions had positive effects on diabetes-specific QoL, and interventions using a collaborative learning approach improved knowledge. Multi-component self-management interventions potentially lead to clinically relevant improvements in behaviour and some clinical parameters. Further research is needed to explain the mixed effects on exercise and to identify processes underlying behaviour change. Copyright © 2010 FEND

OBJECTIVES: To review the evidence and determine the effectiveness of smartphone-based self-management interventions on self-efficacy, self-care activities, health-related quality of life, glycated hemoglobin, body mass index (BMI), and blood pressure (BP) levels of adults with type 2 diabetes mellitus . METHODS: A systematic search of five databases (PubMed, Embase, Cochrane, CINAHL and Scopus) was conducted. Studies published in English from January 2007 to January 2018 were considered. Only randomized controlled trials (RCTs) of smartphone-based self-management interventions for patients with type 2 diabetes mellitus that reported any of the study outcomes were included. Two reviewers independently screened the studies, extracted data and assessed the quality of the studies. Meta-analyses were conducted for the different study outcomes. RESULTS: A total of 26 articles, consisting of 22 studies with 2645 participants, were included in the review. The results from meta-analysis on the studies revealed that as compared to control group, participants received smartphone-based self-management intervention had better self-efficacy with large effect size of 0.98 (P < 0.001), self-care activities with effect size of 0.90 (P < 0.001), health related quality of life with effect size of 0.26 (p=0.01), and lower glycated hemoglobin (pooled MD=-0.55; p<0.001). Subgroup analyses were also conducted for self-efficacy as significant heterogeneity was present among the studies. The effects on BMI and BP were not statistically significant. CONCLUSIONS: Smartphone-based self-management interventions appear to have beneficial effects on self-efficacy, self-care activities and health-relevant outcomes for patients with type 2 diabetes mellitus. However, more research with good study design is needed to evaluate the effectiveness of smartphone-based self-care interventions for T2DM.

To evaluate the association between shift work and risk of type 2 diabetes mellitus, we searched PubMed, EMBASE and Web of Science from their inception to June 8, 2019. Observational studies examining the relationship between shift work and type 2 diabetes were included. Subgroup analyses were conducted to explore whether specific characteristics would affect the relationship. A dose-response relationship was estimated by using generalized least squares trend regression. Finally, twelve cohort studies and nine cross-sectional studies were included (inter-rater agreement, k = 0.96). The result of meta-analysis indicated that shift work was associated with an increased risk of type 2 diabetes (relative risk = 1.10, 95% confidence interval = 1.05-1.14). Subgroup analyses demonstrated that female shift workers have increased risk of type 2 diabetes while male not observed, health care workers showed the highest risk compared with civil servants and manual workers, and night shift and rotating shift were associated with an increased risk of type 2 diabetes. Dose-response meta-analysis based on three cohorts among female workers indicated that there might be a positive association between duration of shift work and the risk of type 2 diabetes. In conclusion, shift work is positively associated with an increased risk of type 2 diabetes. Among female workers, with the years of exposure to shift work prolonged, the risk of type 2 diabetes might increase accordingly. In the future, more studies are needed to confirm the results of dose-response analysis.

Objectives: To evaluate the health economics evidence based on randomized controlled trials of pharmacist-led medication review in pharmacotherapy managed cardiovascular disease risk factors, specifically, hypertension, type-2 diabetes mellitus and dyslipidaemia in ambulatory settings and to provide recommendations for future evaluations. Methods: A systematic review was carried out according to the Cochrane Handbook for Systematic Reviews. PubMed (Medline), Scopus, Web of Science, National Health System Economic Evaluation Database (NHS EED), Cochrane Library, and Econlit were searched and screened by two independent authors. Incremental cost-effectiveness ratio was the main outcome. Risk of bias was assessed with the Effective Practice and Organisation of Care tool by the Cochrane Collaboration. Economic evaluation quality was assessed with the he Consensus Health Economic Criteria list (CHEC list). Results: 5636 records were found, and 174 were retrieved for full-text review yielding 11 articles. Eight articles deemed the intervention as cost effective and two as dominant. Two cost-utility analyses were performed yielding ICERs of $612.7 and $59.8 per QALY. Four articles were considered to perform a high-quality economic evaluation and four had a low risk of bias. Future economic evaluations should consider cost-utility analysis, to describe usual care thoroughly, and use time horizons that capture the effect of cardiovascular disease prevention, a societal perspective and uncertainty analysis. Conclusion: Pharmacist-led medication review has proven to be cost effective in various studies in different settings. Policy decision makers are advised to undertake local economic evaluations reflecting the gaps observed in this systematic review and published literature. If this is not possible, a transferability assessment should be conducted.

Background: Diabetes is one of the world's most prevalent and serious non-communicable diseases (NCDs). It is a leading cause of death, disability and financial loss; moreover, it is identified as a major threat to global development. The chronic nature of diabetes and its related complications make it a costly disease. Estimating the total cost of an illness is a useful aid to national and international health policy decision making. The aim of this systematic review is to summarise the impact of the cost-of-illness of type 2 diabetes mellitus in low and lower-middle income countries, and to identify methodological gaps in measuring the cost-of-illness of type 2 diabetes mellitus. Methods: This systematic review considers studies that reported the cost-of-illness of type 2 diabetes in subjects aged 18 years and above in low and lower-middle income countries. The search engines MEDLINE, EMBASE, CINAHL, PSYCINFO and COCHRANE were used form date of their inception to September 2018. Two authors independently identified the eligible studies. Costs reported in the included studies were converted to US dollars in relation to the dates mentioned in the studies. Results: The systematic search identified eight eligible studies conducted in low and lower-middle income countries. There was a considerable variation in the costs and method used in these studies. The annual average cost (both direct and indirect) per person for treating type 2 diabetes mellitus ranged from USD29.91 to USD237.38, direct costs ranged from USD106.53 to USD293.79, and indirect costs ranged from USD1.92 to USD73.4 per person per year. Hospitalization cost was the major contributor of direct costs followed by drug costs. Conclusion: Type 2 diabetes mellitus imposes a considerable economic burden which most directly affects the patients in low and lower-middle income countries. There is enormous scope for adding research-based evidence that is methodologically sound to gain a more accurate estimation of cost and to facilitate comparison between studies.

BACKGROUND: The popularity of internet as an area of research has grown manifold over the years. Given its rapid development and increasing coverage worldwide, internet-based interventions seem to offer a promising option to ameliorate huge burdens brought by type 2 diabetes mellitus. However, studies conducted by different researchers have provided contradictory results on the effect of internet-based interventions in glycemic control. OBJECTIVE: This meta-analysis aims to summarize currently available evidence and evaluate the overall impact of internet-based interventions on glycemic management of type 2 diabetic patients. METHODS: A systematic literature search was performed in PubMed, ScienceDirect, and Web of Science. Randomized controlled trials that used glycosylated hemoglobin values as the outcome measure of glycemic control were considered. Risk of bias and publication bias were evaluated. RESULTS: Of the 492 studies, 35 were included in meta-analysis, and results indicated that the weighted mean difference (WMD) between usual care and internet-based interventions at endpoint was -0.426% (95% CI -0.540 to -0.312; P<.001). Subgroup analyses revealed that intervention duration ≤3 months yielded optimal performance (WMD -0.51%; 95% CI -0.71 to -0.31; P<.001). Combined mobile and website interventions were substantially superior to solely Web-based and mobile-based interventions in glycemic control (combined WMD -0.77%, 95% CI -1.07 to -0.47; P<.001; Web only: WMD -0.48%; 95% CI -0.71 to -0.24, P<.001; mobile only WMD -0.31%, 95% CI -0.49 to -0.14; P<.001). Furthermore, the effect of interventions with automated feedbacks was similar to those with manual feedbacks, and studies with internet-based educational contents were more effective in glycemic control. The assessment revealed a low risk of bias. CONCLUSIONS: In conclusion, utilization of internet-based intervention is beneficial for patients with type 2 diabetes mellitus, and taking full advantage of this type of intervention may substantially reduce the incidence of complications and improve quality of life.

Technology can be used to supplement healthcare provider diabetes care by providing both educational and motivational support. Education can be provided using technology allowing patients to learn new practices and routines related to diabetes management. Technology can support daily diabetes self-management activities including blood glucose monitoring, exercising, healthy eating, taking medication, monitoring for complications, and problem-solving. This article describes an integrative review conducted to evaluate the types of technology being used to facilitate diabetes self-management and the effect of that technology on self-management and diabetes outcomes for adults living with type 2 diabetes mellitus. A literature review was conducted by searching Medline, PubMed, and Psych INFO databases using the search terms: diabetes self-management, technology, type 2 diabetes, smartphones, cell phones, and diabetes mellitus covering the years from 2008-2013. Articles relying on secondary data (editorials, systematic reviews) and articles describing study protocol only were excluded. Fourteen studies including qualitative, quasi-experimental, and randomized controlled trial designs were identified and included in the review. The review found that technological interventions had positive impacts on diabetes outcomes including improvements in hemoglobin A1C levels, diabetes self-management behaviors, and diabetes self-efficacy. Results indicate that technological interventions can benefit people living with diabetes when used in conjunction with diabetes care delivered by healthcare providers

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a highly prevalent chronic metabolic disease characterized by hyperglycemia and cardiovascular risks. Without proper treatment, T2DM can lead to long-term complications. Diabetes self-management is recognized as the cornerstone of overall diabetes management. Web-based self-management programs for T2DM patients can help to successfully improve patient health behaviors and health-related outcomes. Theories can help to specify key determinants of the target behaviors and behavior change strategies required to arrive at the desired health outcomes, which can then be translated into specific behavioral techniques or strategies that patients can learn to apply in their daily life. From previous reviews of a wide range of online diabetes self-management tools and programs, it appears that it is still unclear which behavioral change techniques (BCTs) are primarily used and are most effective when it comes to improving diabetes self-management behaviors and related health outcomes.OBJECTIVE: We set out to identify which BCTs are being applied in online self-management programs for T2DM and whether there is indication of their effectiveness in relation to predefined health outcomes.METHODS: Articles were systematically searched and screened on the mentioned use of 40 BCTs, which were then linked to reported statistically significant improvements in study outcomes.RESULTS: We found 13 randomized controlled trials reporting on 8 online self-management interventions for T2DM. The BCTs used were feedback on performance, providing information on consequences of behavior, barrier identification/problem solving, and self-monitoring of behavior. These BCTs were also linked to positive outcomes for health behavior change, psychological well-being, or clinical parameters.CONCLUSIONS: A relatively small number of theory-based online self-management support programs for T2DM have been reported using only a select number of BCTs. The development of future online self-management interventions should be based on the use of theories and BCTs and should be reported accurately.