Self-compassion is an important psychological resource that improves health-related quality of life and diabetes self-management;however,the psychological processes underlying these associations remain unclear.This st...Self-compassion is an important psychological resource that improves health-related quality of life and diabetes self-management;however,the psychological processes underlying these associations remain unclear.This study examined the roles of meaning in life and resilience in the relationship between self-compassion and both health-related quality of life and diabetes self-management.Participants were 301 individuals living with type 2 diabetes(176(58.5%)females,M age=49.69,SD=12.36)conveniently selected from two tertiary healthcare institutions in Nigeria.They completed self-report measures of self-compassion,meaning in life,resilience,health-related quality of life and diabetes selfmanagement.Multiple regression analyses indicated that self-compassion positively predicted health-related quality of life and diabetes self-management.Meaning in life and resilience independently and positively predicted health-related quality of life and diabetes self-management.Mediation analysis showed that meaning in life mediated the association between self-compassion and health-related quality of life,as well as diabetes self-management.Likewise,resilience mediated the connection between self-compassion and health-related quality of life,and diabetes self-management behaviour.Intervention for diabetes self-management should focus on promoting self-compassion,meaning in life and resilience abilities of patients,as they can potentially improve health and self-care behaviours needed for recovery.展开更多
BACKGROUND Telemedicine is defined as the delivery of health services via remote communication and technology.It is a convenient and cost-effective method of intervention,which has shown to be successful in improving ...BACKGROUND Telemedicine is defined as the delivery of health services via remote communication and technology.It is a convenient and cost-effective method of intervention,which has shown to be successful in improving glyceamic control for type 2 diabetes patients.The utility of a successful diabetes intervention is vital to reduce disease complications,hospital admissions and associated economic costs.AIM To evaluate the effects of telemedicine interventions on hemoglobin A1c(HbA1c),systolic blood pressure(SBP),diastolic blood pressure(DBP),body mass index(BMI),post-prandial glucose(PPG),fasting plasma glucose(FPG),weight,cholesterol,mental and physical quality of life(QoL)in patients with type 2 diabetes.The secondary aim of this study is to determine the effect of the following subgroups on HbA1c post-telemedicine intervention;telemedicine characteristics,patient characteristics and self-care outcomes.METHODS PubMed Central,Cochrane Library,Embase and Scopus databases were searched from inception until 18th of June 2020.The quality of the 43 included studies were assessed using the PEDro scale,and the random effects model was used to estimate outcomes and I2 for heterogeneity testing.The mean difference and standard deviation data were extracted for analysis.RESULTS We found a significant reduction in HbA1c[-0.486%;95%confidence interval(CI)-0.561 to-0.410,P<0.001],DBP(-0.875 mmHg;95%CI-1.429 to-0.321,P<0.01),PPG(-1.458 mmol/L;95%CI-2.648 to-0.268,P<0.01),FPG(-0.577 mmol/L;95%CI-0.710 to-0.443,P<0.001),weight(-0.243 kg;95%CI-0.442 to-0.045,P<0.05),BMI(-0.304;95%CI-0.563 to-0.045,P<0.05),mental QoL(2.210;95%CI 0.053 to 4.367,P<0.05)and physical QoL(-1.312;95%CI 0.545 to 2.080,P<0.001)for patients following telemedicine interventions in comparison to control groups.The results of the meta-analysis did not show any significant reductions in SBP and cholesterol in the telemedicine interventions compared to the control groups.The telemedicine characteristic subgroup analysis revealed that clinical treatment models of intervention,as well as those involving telemonitoring,and those provided via modes of videoconference or interactive telephone had the greatest effect on HbA1c reduction.In addition,interventions delivered at a less than weekly frequency,as well as those given for a duration of 6 mo,and those lead by allied health resulted in better HbA1c outcomes.Furthermore,interventions with a focus on biomedical parameters,as well as those with an engagement level>70%and those with a drop-out rate of 10%-19.9%showed greatest HbA1c reduction.The patient characteristics investigation reported that Hispanic patients with T2DM had a greater HbA1c reduction post telemedicine intervention.For self-care outcomes,telemedicine interventions that resulted in higher postintervention glucose monitoring and self-efficacy were shown to have better HbA1c reduction.CONCLUSION The findings indicate that telemedicine is effective for improving HbA1c and thus,glycemic control in patients with type 2 diabetes.In addition,telemedicine interventions were also found to significantly improved other health outcomes as well as QoL scores.The results of the subgroup analysis emphasized that interventions in the form of telemonitoring,via a clinical treatment model and with a focus on biomedical parameters,delivered at a less than weekly frequency and 6 mo duration would have the largest effect on HbA1c reduction.This is in addition to being led by allied health,through modes such as video conference and interactive telephone,with an intervention engagement level>70%and a drop-out rate between 10%-19.9%.Due to the high heterogeneity of included studies and limitations,further studies with a larger sample size is needed to confirm our findings.展开更多
Diabetes is one of the fastest-growing non-communicable diseases,becoming an important public health concern worldwide as well as in China.Currently,China has the largest population living with diabetes.Artificial inte...Diabetes is one of the fastest-growing non-communicable diseases,becoming an important public health concern worldwide as well as in China.Currently,China has the largest population living with diabetes.Artificial intelligence(AI)is a fast-growingfield and its applications to diabetes could enable the delivery of better management services for people with diabetes.This perspective summarized the latestfindings of digital tech-nologies and AI use in the following areas of diabetes care,mainly including screening and risk predictions of diabetes and diabetic complications,precise monitoring and inter-vention combined with new technologies,and mobile health application in self-management support for people with diabetes.Challenges to promote further use of AI in diabetes care included data standardization and integra-tion,performance of AI-based medical devices,motivation of patients,and sensitivity to privacy.In summary,although the AI applications in clinical practice is still at an early stage,we are moving toward a new paradigm for diabetes care with the rapid development and emerging application of AI.展开更多
文摘Self-compassion is an important psychological resource that improves health-related quality of life and diabetes self-management;however,the psychological processes underlying these associations remain unclear.This study examined the roles of meaning in life and resilience in the relationship between self-compassion and both health-related quality of life and diabetes self-management.Participants were 301 individuals living with type 2 diabetes(176(58.5%)females,M age=49.69,SD=12.36)conveniently selected from two tertiary healthcare institutions in Nigeria.They completed self-report measures of self-compassion,meaning in life,resilience,health-related quality of life and diabetes selfmanagement.Multiple regression analyses indicated that self-compassion positively predicted health-related quality of life and diabetes self-management.Meaning in life and resilience independently and positively predicted health-related quality of life and diabetes self-management.Mediation analysis showed that meaning in life mediated the association between self-compassion and health-related quality of life,as well as diabetes self-management.Likewise,resilience mediated the connection between self-compassion and health-related quality of life,and diabetes self-management behaviour.Intervention for diabetes self-management should focus on promoting self-compassion,meaning in life and resilience abilities of patients,as they can potentially improve health and self-care behaviours needed for recovery.
文摘BACKGROUND Telemedicine is defined as the delivery of health services via remote communication and technology.It is a convenient and cost-effective method of intervention,which has shown to be successful in improving glyceamic control for type 2 diabetes patients.The utility of a successful diabetes intervention is vital to reduce disease complications,hospital admissions and associated economic costs.AIM To evaluate the effects of telemedicine interventions on hemoglobin A1c(HbA1c),systolic blood pressure(SBP),diastolic blood pressure(DBP),body mass index(BMI),post-prandial glucose(PPG),fasting plasma glucose(FPG),weight,cholesterol,mental and physical quality of life(QoL)in patients with type 2 diabetes.The secondary aim of this study is to determine the effect of the following subgroups on HbA1c post-telemedicine intervention;telemedicine characteristics,patient characteristics and self-care outcomes.METHODS PubMed Central,Cochrane Library,Embase and Scopus databases were searched from inception until 18th of June 2020.The quality of the 43 included studies were assessed using the PEDro scale,and the random effects model was used to estimate outcomes and I2 for heterogeneity testing.The mean difference and standard deviation data were extracted for analysis.RESULTS We found a significant reduction in HbA1c[-0.486%;95%confidence interval(CI)-0.561 to-0.410,P<0.001],DBP(-0.875 mmHg;95%CI-1.429 to-0.321,P<0.01),PPG(-1.458 mmol/L;95%CI-2.648 to-0.268,P<0.01),FPG(-0.577 mmol/L;95%CI-0.710 to-0.443,P<0.001),weight(-0.243 kg;95%CI-0.442 to-0.045,P<0.05),BMI(-0.304;95%CI-0.563 to-0.045,P<0.05),mental QoL(2.210;95%CI 0.053 to 4.367,P<0.05)and physical QoL(-1.312;95%CI 0.545 to 2.080,P<0.001)for patients following telemedicine interventions in comparison to control groups.The results of the meta-analysis did not show any significant reductions in SBP and cholesterol in the telemedicine interventions compared to the control groups.The telemedicine characteristic subgroup analysis revealed that clinical treatment models of intervention,as well as those involving telemonitoring,and those provided via modes of videoconference or interactive telephone had the greatest effect on HbA1c reduction.In addition,interventions delivered at a less than weekly frequency,as well as those given for a duration of 6 mo,and those lead by allied health resulted in better HbA1c outcomes.Furthermore,interventions with a focus on biomedical parameters,as well as those with an engagement level>70%and those with a drop-out rate of 10%-19.9%showed greatest HbA1c reduction.The patient characteristics investigation reported that Hispanic patients with T2DM had a greater HbA1c reduction post telemedicine intervention.For self-care outcomes,telemedicine interventions that resulted in higher postintervention glucose monitoring and self-efficacy were shown to have better HbA1c reduction.CONCLUSION The findings indicate that telemedicine is effective for improving HbA1c and thus,glycemic control in patients with type 2 diabetes.In addition,telemedicine interventions were also found to significantly improved other health outcomes as well as QoL scores.The results of the subgroup analysis emphasized that interventions in the form of telemonitoring,via a clinical treatment model and with a focus on biomedical parameters,delivered at a less than weekly frequency and 6 mo duration would have the largest effect on HbA1c reduction.This is in addition to being led by allied health,through modes such as video conference and interactive telephone,with an intervention engagement level>70%and a drop-out rate between 10%-19.9%.Due to the high heterogeneity of included studies and limitations,further studies with a larger sample size is needed to confirm our findings.
基金Chinese Academy of Engineering Grants Award No.2022-XY-08Shanghai Municipal Science and Technology Commission Grants Award No.22692114600+1 种基金Shanghai Municipal Grants Award No.2022ZZ01002UNC-Michigan Peer Support Core of the University of Michigan Center for Diabetes Translational Research,P30 DK092926.
文摘Diabetes is one of the fastest-growing non-communicable diseases,becoming an important public health concern worldwide as well as in China.Currently,China has the largest population living with diabetes.Artificial intelligence(AI)is a fast-growingfield and its applications to diabetes could enable the delivery of better management services for people with diabetes.This perspective summarized the latestfindings of digital tech-nologies and AI use in the following areas of diabetes care,mainly including screening and risk predictions of diabetes and diabetic complications,precise monitoring and inter-vention combined with new technologies,and mobile health application in self-management support for people with diabetes.Challenges to promote further use of AI in diabetes care included data standardization and integra-tion,performance of AI-based medical devices,motivation of patients,and sensitivity to privacy.In summary,although the AI applications in clinical practice is still at an early stage,we are moving toward a new paradigm for diabetes care with the rapid development and emerging application of AI.
