Abstract:Aims
This study investigated self‐care activities and identified their related factors in Chinese patients with type 2 diabetes mellitus.
Methods
A cross‐sectional study was conducted in Guangzhou, China, between September 2016 and February 2017, involving 202 Chinese patients with type 2 diabetes mellitus. Measures included the Summary of Diabetes Self‐Care Activities Questionnaire and Revised Illness Perception Questionnaire.
Results
Self‐care activities in Chinese patients with type 2 diabetes mellitus were… Show more
“…As the income level of households increased, it was noted that selfcare behaviors were significantly reduced and HbA1c levels were increased. Most of the previous studies reported significant differences among self-care behaviors, HbA1c status, and sociodemographic factors among patients with type 2 diabetes (29)(30)(31)(32)(33)(34)(35)(36)(37). A study in Northern Jordan demonstrated that HbA1c level is significantly related to household income, education levels, employment status, and disease duration (16).…”
Section: Discussionmentioning
confidence: 99%
“…In studies, the observed diabetes-related knowledge and self-care knowledge were associated with self-care behaviors ( 38 , 42 ). Patients who have better knowledge about the symptoms of diabetes are more successful in testing their blood sugar and exercising ( 34 , 44 ). Knowledge, attitudes, and behaviors to promote health-related behaviors and prevent diseases are related ( 41 ).…”
AimsThis study used the Extended Theory of Reasoned Action (ETRA) to predict self-care behaviors and HbA1c among patients with type 2 diabetes in Iran.Materials and methodsA cross-sectional study was performed using a multistage random sample. A total of 240 patients with type 2 diabetes, who were referred to the diabetes healthcare centers in Chaldoran, participated in the research. Instruments consisting of standardized questionnaires were used based on the Extended Theory of Reasoned Action (ETRA) constructs and the summary scale of diabetes self-care behaviors measure.FindingsThe results of this study demonstrated that demographic variables explained ~ 7% (p-value = 0.23) and ETRA constructs 18% of the variance (p-value = 0.02) in behavioral intention, respectively. According to the hierarchical multiple linear regressions on self-care behaviors, demographic factors (p-value 0.001) dictated 45.7% of the variation of the self-care behavior, while knowledge, attitude, self-efficacy, and behavioral intention (p-value 0.001) accounted for 63.4% of the variance. The ETRA constructs, self-care practices, and demographic factors together account for almost 57% of the variation in the HbA1c. Self-care practices were the best indicator of HbA1c (β = −0.593).ConclusionETRA constructs and self-care behavior can be the best determinants of HbA1c level in type 2 diabetes. This model is suggested to be applied in designing intervention programs to improve HbA1c in these groups of patients.
“…As the income level of households increased, it was noted that selfcare behaviors were significantly reduced and HbA1c levels were increased. Most of the previous studies reported significant differences among self-care behaviors, HbA1c status, and sociodemographic factors among patients with type 2 diabetes (29)(30)(31)(32)(33)(34)(35)(36)(37). A study in Northern Jordan demonstrated that HbA1c level is significantly related to household income, education levels, employment status, and disease duration (16).…”
Section: Discussionmentioning
confidence: 99%
“…In studies, the observed diabetes-related knowledge and self-care knowledge were associated with self-care behaviors ( 38 , 42 ). Patients who have better knowledge about the symptoms of diabetes are more successful in testing their blood sugar and exercising ( 34 , 44 ). Knowledge, attitudes, and behaviors to promote health-related behaviors and prevent diseases are related ( 41 ).…”
AimsThis study used the Extended Theory of Reasoned Action (ETRA) to predict self-care behaviors and HbA1c among patients with type 2 diabetes in Iran.Materials and methodsA cross-sectional study was performed using a multistage random sample. A total of 240 patients with type 2 diabetes, who were referred to the diabetes healthcare centers in Chaldoran, participated in the research. Instruments consisting of standardized questionnaires were used based on the Extended Theory of Reasoned Action (ETRA) constructs and the summary scale of diabetes self-care behaviors measure.FindingsThe results of this study demonstrated that demographic variables explained ~ 7% (p-value = 0.23) and ETRA constructs 18% of the variance (p-value = 0.02) in behavioral intention, respectively. According to the hierarchical multiple linear regressions on self-care behaviors, demographic factors (p-value 0.001) dictated 45.7% of the variation of the self-care behavior, while knowledge, attitude, self-efficacy, and behavioral intention (p-value 0.001) accounted for 63.4% of the variance. The ETRA constructs, self-care practices, and demographic factors together account for almost 57% of the variation in the HbA1c. Self-care practices were the best indicator of HbA1c (β = −0.593).ConclusionETRA constructs and self-care behavior can be the best determinants of HbA1c level in type 2 diabetes. This model is suggested to be applied in designing intervention programs to improve HbA1c in these groups of patients.
“…The late diagnosis may partially contribute to the high prevalence of DKD in Asia and Africa. In Asia, healthcare providers and nurses are not sufficiently educated about diabetes patients, about 50% lack understanding of diabetes complications,32 and self-care activities are suboptimal overall 33. Therefore, it is extremely significant to have an accurate prediction model that could assist clinicians in real-time evaluation of patient risk and implement primary and secondary preventive measures to delay progression of disease.…”
ObjectivesThis study aims to independently and externally validate the Risk Prediction Model for Diabetic Kidney Disease (RPM-DKD) in patients with type 2 diabetes mellitus (T2DM).DesignThis is a retrospective cohort study.SettingOutpatient clinics at Lee’s United Clinics, Taiwan, China.ParticipantsA total of 2504 patients (average age 55.44 years, SD, 7.49 years) and 4455 patients (average age 57.88 years, SD, 8.80 years) were included for analysis in the DKD prediction and progression prediction cohorts, respectively.ExposureThe predicted risk for DKD and DKD progression for each patient were all calculated using the RPM-DKD.Primary and secondary outcome measuresThe primary outcome measure was overall incidence of DKD. Secondary outcomes included DKD progression. The discrimination, calibration and precision of the RPM-DKD score were assessed.ResultsThe DKD prediction cohort and progression prediction cohort consisted of patients with 2504 and 4455 T2DM, respectively. The RPM-DKD examined in this study showed moderately discriminative ability with area under the curve ranged from 0.636 to 0.681 for the occurrence of DKD and 0.620 to 0.654 for the progression of DKD. The Hosmer-Lemeshow χ2test indicted the RPM-DKD was not well calibrated for predicting the occurrence of DKD and overestimated the progression of DKD. The precision for predicting the occurrence and progression of DKD were 43.2% and 42.2%, respectively.ConclusionsOn external validation, the RPM-DKD cannot accurately predict the risk of DKD occurrence and progression in patients with T2DM.
“…The Chinese version of SDSCA has an acceptable internal consistency, with Cronbach’s α range from 0.62 to 0.98. 30 …”
Section: Methodsmentioning
confidence: 99%
“…The Chinese version Open access of SDSCA has an acceptable internal consistency, with Cronbach's α range from 0.62 to 0.98. 30 The DES-SF measures the psychosocial empowerment of patients with diabetes. 31 The 8-item DES-SF employs the 5-point Likert scoring system.…”
IntroductionResearch on the needs and preferences of patients with poorly controlled type 2 diabetes mellitus (T2DM) with mobile health (mHealth) service is limited. With the principles of co-production, this study aims to address this research gap by exploring the health needs of Chinese patients with poorly controlled T2DM.Methods and analysisThis study uses a three-phase, exploratory sequential mixed-method design. Phase 1 aims to assess the health needs of patients with poorly controlled T2DM by conducting semi-structured interviews with patients, doctors and nurses. Participants will be recruited by purposive sampling with maximum variation. Content analysis will be employed. Phase 2 will form item generation and develop the mHealth need scale. The scale will be subject to pilot testing and psychometric evaluation, including content validity, construct validity, discriminant validity, internal validity and test–retest reliability. Phase 3 will explore the priority of health needs perceived by patients with poorly controlled T2DM through a cross-sectional study. The measurement tools include an mHealth needs scale, the Summary of Diabetes Self-care Activities Questionnaire, the Diabetes Empowerment Scale-Short Form, the Diabetes Health Literacy Scale and the eHealth Literacy Scale. Multiple regression techniques with a hierarchical block design will be used for the model building to identify the factors contributing to the heterogeneity of the perceived mHealth needs. The findings of phase 1 and phase 3 will be integrated using data correlation, comparison and consolidation.Ethics and disseminationThe Ethics Committee of the School of Nursing, Sun Yat-sen University, has approved this study (No. 2021ZSLYEC). The results of this study will be disseminated through conference presentations and peer-reviewed publications.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.