scholarly journals Application of structural equation modeling in assessing the self-management activities of patients with type 2 diabetes

2020 ◽  
Vol 11 ◽  
pp. 215013272097420
Author(s):  
Rashid M. Ansari ◽  
Mark Harris ◽  
Hassan Hosseinzadeh ◽  
Nicholas Zwar
Keyword(s):  
Type 2 Diabetes ◽  
Structural Equation Modeling ◽  
Glycemic Control ◽  
Structural Equation ◽  
Self Care ◽  
The Self ◽  
Self Management ◽  
Equation Modeling ◽  
Chi Squared

Objective This study aimed at assessing the self-management activities of type 2 diabetes patients using Structural Equation Modeling (SEM) which measures and analyzes the correlations between observed and latent variables. This statistical modeling technique explored the linear causal relationships among the variables and accounted for the measurement errors. Methods A sample of 200 patients was recruited from the middle-aged population of rural areas of Pakistan to explore the self-management activities of type 2 diabetes patients using the validated version of the Urdu Summary of Diabetes Self-care Activities (U-SDSCA) instrument. The structural modeling equations of self-management of diabetes were developed and used to analyze the variation in glycemic control (HbA1c). Results The validated version of U-SDSCA instrument showed acceptable psychometric properties throughout a consecutive reliability and validity evaluation including: split-half reliability coefficient 0.90, test-retest reliability (r = 0.918, P  ≤ .001), intra-class coefficient (0.912) and Cronbach’s alpha (0.79). The results of the analysis were statistically significant (α = 0.05, P-value < .001), and showed that the model was very well fitted with the data, satisfying all the parameters of the model related to confirmatory factor analysis with chi-squared = 48.9, CFI = 0.94, TLI = 0.95, RMSEA = 0.065, SPMR = 0.068. The model was further improved once the items related to special diet were removed from the analysis, chi-squared value (30.895), model fit indices (CFI = 0.98, TLI = 0.989, RMSEA = 0.045, SPMR = 0.048). A negative correlation was observed between diabetes self-management and the variable HbA1c (r = –0.47; P < .001). Conclusions The Urdu Summary of Diabetes Self-Care Activities (U-SDSCA) instrument was used for the patients of type 2 diabetes to assess their diabetes self-management activities. The structural equation models of self-management showed a very good fit to the data and provided excellent results which may be used in future for clinical assessments of patients with suboptimal diabetes outcomes or research on factors affecting the associations between self-management activities and glycemic control

scholarly journals Effectiveness of Patient-centered Care for Diabetes Self-management to Improve Glycemic Control and Self-care Behaviors in Adults With Type 2 Diabetes: a Systematic Review

2021 ◽  
Author(s):  
Kainat Asmat ◽  
Khairunnisa Dhamani ◽  
Raisa Gul ◽  
Erika Sivarajan Froelicher
Keyword(s):  
Type 2 Diabetes ◽  
Glycemic Control ◽  
Self Care ◽  
Self Management ◽  
Foot Care ◽  
Patient Centered ◽  
Management Interventions ◽  
Centered Care ◽  
Care Outcomes

Abstract Background: Patient-centered care in diabetes self-management might be a significant factor in improving self-care outcomes yet the supporting evidence is inadequate. This review is aimed to assess the effectiveness of patient-centered self-management care interventions on self-care outcomes such as glycemic control (HbA1c) and self-care behaviors in adults with type-2 diabetes compared with usual care. Methods: CINAHL, PubMed, Cochrane Library, Google Scholar and the HEC Pakistan digital library were searched for English language studies that assessed patient-centered self-management educational and/or behavioral interventions in adults aged 18 years or above with type 2 diabetes from 1991 to 2020. Interventional studies comprising randomized controlled trials (RCT) and quasi experimental studies (QES) with at least three months follow up and reporting on self-care outcomes with glycemic control (HbA1c) as primary outcome and self-care behaviors including diet control, physical activity, medication adherence and foot care as secondary outcomes were included. Results: Of the 168 identified records, 25 were found eligible comprising 21 RCTs and 4 QESs with total 4,443 participants. The meta-analysis involved 23 studies that provided enough information for a pooled estimate of HbA1c. Compared with the control group, patient-centered self-management interventions significantly lowered HbA1c −0.53 (95% CI −0.73, −0.32). Stratified analysis for HbA1c with respect to various aspects of intervention showed larger effects in interventions employing both educational and behavioral components −0.59 (95% CI −0.86, −0.32), spanned over shorter (<03 months) duration −0.56 (95% CI −0.86, −0.27), administered by nurses −0.80 (95% CI −1.44, −0.16) and delivered in community setting −0.65 (95% CI −1.00, −0.29). Moreover, patient-centered self-management interventions were found effective in improving diet control, physical activity and foot care. Conclusion: This systematic review provided the evidence supporting the effectiveness of patient-centered self-management care interventions in improving glycemic control and self-care behaviors in adults with type 2 diabetes and identified key features of intervention contributing towards success.

scholarly journals Structural equation modeling for hypertension and type 2 diabetes based on multiple SNPs and multiple phenotypes

PLoS ONE ◽  
2019 ◽  
Vol 14 (9) ◽  
pp. e0217189
Author(s):  
Saebom Jeon ◽  
Ji-yeon Shin ◽  
Jaeyong Yee ◽  
Taesung Park ◽  
Mira Park
Keyword(s):  
Type 2 Diabetes ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Multiple Snps ◽  
Multiple Phenotypes

Development and utility of m-health enabled nutrition informatics intervention for self-care management of type 2 diabetes in home settings (Preprint)

2021 ◽  
Author(s):  
Abhijeet Prasad Sinha ◽  
Manmohan Singhal ◽  
Mansi Gupta ◽  
Ashish Joshi
Keyword(s):  
Public Health ◽  
Type 2 Diabetes ◽  
Care Management ◽  
Self Care ◽  
The Self ◽  
Self Management ◽  
Integrative Approach ◽  
Health Application ◽  
The Impact

BACKGROUND Diabetes represents an important public health challenge in India and Globally. It affects quality of life and is one of the leading causes of death and disability. The burden on global health is huge and about 463 million adults are currently living with diabetes. 77 million people in India in the age group of 20-79 years are affected by this pandemic and total cost to health expenditure is 8 billion US dollars, therefore huge burden, and great economic cost on Public health. The self-management of diabetes, the research priorities include exploring the concept of diabetes self-management and major research questions would comprise of asking what affects self-management in persons with diabetes and how do m-health application and interventions can impact on the self-management behaviors in development, utility of the m-health app in self-management of person with diabetes. Therefore, this project research is of great significance and would bring an integrative approach on self-care management OBJECTIVE To design, develop and evaluate the impact of m-health enabled nutrition informatics intervention for home based self-management of type 2 diabetes in an Indian setting. METHODS A mixed research study will be conducted between January 2022 and January 2023. A sample of approximately 250 individuals will be recruited and enrolled using a nonprobability complete enumeration sampling method from selected urban settings of Delhi inclusion and exclusion criteria with age20-79 years male and female with Type 2 diabetes and have access to Smart phone Data will be collected using which questionnaires. The collected data will be used to assess use and utility of mobile health application developed. The knowledge, attitudes, practices, and beliefs regarding Diabetes self-care management. Lastly, the study questionnaire system usability survey(SUS) will be used to assess the usability of mobile applications on selfcare management of Diabetes RESULTS A pilot of 250 individuals has been conducted to pretest the DBMS questionnaire. The data collection will be initiated from January 2022, and the initial results are planned for publication by October 2022.Descriptive analysis of the gathered data will be performed using SPSS V11, and reporting of the results will be done at 95% CIs and P=.0.05. CONCLUSIONS The findings of the study would inform the elements essential for the development of m-health intervention to improve self-care management of diabetes at home settings. The usefulness and acceptance of the proposed intervention will be conducted. CLINICALTRIAL DITU/UREC/2021/07/10

scholarly journals Effect of a Ten-Week Short Message Service-Based Intervention on Self-Management of Type-2 Diabetes Patients in Bali, Indonesia

2021 ◽  
Vol 11 (2) ◽  
pp. 177-186
Author(s):  
Made Rini Damayanti ◽  
Gusti Ayu Ary Antari ◽  
Ni Luh Putu Nopriani
Keyword(s):  
Type 2 Diabetes ◽  
Intervention Group ◽  
Self Care ◽  
The Self ◽  
Self Management ◽  
Care Practice ◽  
Control Group ◽  
Short Message ◽  
Diabetes Patients

Background: Diabetes mellitus is a chronic disease that may pose serious complications if poorly managed. The application of mobile technology (m-health) ranging from simple to more complex programs in diabetes management has the potential to foster patients’ active involvement in their care. However, the evidence of m-health effectiveness on the self-management of type-2 diabetes patients in low- and middle-income countries is still mixed.Purpose: To evaluate the effect of a ten-week short message system (SMS)-based intervention (Tweek SMSDM) on self-management of type-2 diabetes patients.Methods: A quasi-experimental study was performed in two groups. The intervention group (n=30) received additional daily automated messages to enhance their diabetic self-care practice, while the control group (n=30) continued to follow the standard program only. Pre- and post-intervention data were measured in both groups using the Indonesian version of the Summary of Diabetes Self-Care Activities (SDSCA) questionnaire. T-test, Mann-Whitney, Wilcoxon Signed-Ranks, McNemar and Fisher exact tests were carried out to analyze the data.Results: After ten weeks, the intervention group showed significant mean changes in the domains of general diet (0.42±1.08; p=0.034), specific diet (1.75±1.42; p=0.0001), exercise (1.02±1.85; p=0.005), blood-glucose testing (0.53±1.67; p=0.009), and foot care (4.75±2.51; p=0.001) before and after the intervention, while the control group did not. This study also found significant differences in the mean scores for each domain of the SDSCA between the intervention and the control groups (p<0.05).Conclusion: The Tweek SMSDM program can improve the self-management of type-2 diabetes patients and positively affect each domain in the SDSCA. The findings of this study recommend that nurses integrate the program into patient treatment regimes in primary healthcare centers; therefore, patients and their significant others can play more proactive roles in their diabetic care.

scholarly journals Structural equation modeling for hypertension and type 2 diabetes based on multiple SNPs and multiple phenotypes

2019 ◽  
Author(s):  
Saebom Jeon ◽  
Ji-yeon Shin ◽  
Jaeyong Yee ◽  
Taesung Park ◽  
Mira Park
Keyword(s):  
Type 2 Diabetes ◽  
Structural Equation Modeling ◽  
Genetic Variants ◽  
Latent Variables ◽  
Structural Equation ◽  
Equation Modeling ◽  
Multiple Snps ◽  
Informative Snps ◽  
Intermediate Phenotypes

AbstractGenome-wide association studies (GWAS) have been successful in identifying genetic variants associated with complex diseases. However, association analyses between genotypes and phenotypes are not straightforward due to the complex relationships between genetic and environmental factors. Moreover, multiple correlated phenotypes further complicate such analyses.To resolve this complexity, we present an analysis using structural equation modeling (SEM). Unlike current methods that focus only on identifying direct associations between diseases and genetic variants such as single-nucleotide polymorphisms (SNPs), our method introduces the effects of intermediate phenotypes, which are related phenotypes distinct from the target, into the systematic genetic study of diseases. Moreover, we consider multiple diseases simultaneously in a single model. The procedure can be summarized in four steps: 1) selection of informative SNPs, 2) extraction of latent variables from the selected SNPs, 3) investigation of the relationships among intermediate phenotypes and diseases, and 4) construction of an SEM. As a result, a quantitative map can be drawn that simultaneously shows the relationship among multiple SNPs, phenotypes, and diseases.In this study, we considered two correlated diseases, hypertension and type 2 diabetes (T2D), which are known to have a substantial overlap in their disease mechanism and have significant public health implications. As intermediate phenotypes for these diseases, we considered three obesity-related phenotypes—subscapular skin fold thickness, body mass index, and waist circumference—as traits representing subcutaneous adiposity, overall adiposity, and abdominal adiposity, respectively. Using GWAS data collected from the Korea Association Resource (KARE) project, we applied the proposed SEM process. Among 327,872 SNPs, 24 informative SNPs were selected in the first step (p<1.0E-05). Ten latent variables were generated in step 2. After an exploratory analysis, we established a path diagram among phenotypes and diseases in step 3. Finally, in step 4, we produced a quantitative map with paths moving from specific SNPs to hypertension through intermediate phenotypes and T2D. The resulting model had high goodness-of fit measures (χ2= 536.52, NFI=0.997, CFI=0.998).

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