***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: OBJECTIVE To test whether adding mobile application coaching and patient/provider web portals to community primary care compared with st and ard diabetes management would reduce glycated hemoglobin levels in patients with type 2 diabetes . RESEARCH DESIGN AND METHODS A cluster-r and omized clinical trial , the Mobile Diabetes Intervention Study , r and omly assigned 26 primary care practice s to one of three stepped treatment groups or a control group ( usual care ) . A total of 163 patients were enrolled and included in analysis . The primary outcome was change in glycated hemoglobin levels over a 1-year treatment period . Secondary outcomes were changes in patient-reported diabetes symptoms , diabetes distress , depression , and other clinical ( blood pressure ) and laboratory ( lipid ) values . Maximal treatment was a mobile- and web-based self-management patient coaching system and provider decision support . Patients received automated , real-time educational and behavioral messaging in response to individually analyzed blood glucose values , diabetes medications , and lifestyle behaviors communicated by mobile phone . Providers received quarterly reports summarizing patient ’s glycemic control , diabetes medication management , lifestyle behaviors , and evidence -based treatment options . RESULTS The mean declines in glycated hemoglobin were 1.9 % in the maximal treatment group and 0.7 % in the usual care group , a difference of 1.2 % ( P = 0.001 ) over 12 months . Appreciable differences were not observed between groups for patient-reported diabetes distress , depression , diabetes symptoms , or blood pressure and lipid levels ( all P > 0.05 ) . CONCLUSIONS The combination of behavioral mobile coaching with blood glucose data , lifestyle behaviors , and patient self-management data individually analyzed and presented with evidence -based guidelines to providers substantially reduced glycated hemoglobin levels over 1 year Introduction The role of mobile technology in patient-reported outcomes ( PRO ) and glycemic control in adults with type 1 diabetes ( T1D ) needs further evaluation . Methods The single-center , prospect i ve , 6-month , open-label , investigator-initiated study r and omized 100 subjects with T1D in a 1:1 fashion to a  control group using self-monitoring of blood glucose ( SMBG ) with Accu-Chek Nano ® and an intervention group using SMBG with iPhone plus glucose meter ( iBGStar ® ) . The primary endpoint was the change in PRO ( hypoglycemia fear score , behavior and worry subscores ) . Secondary outcomes were the improvement in glycemic variability indices and the reduction in A1c values . Results Baseline demographics and glycosylated hemoglobin ( A1c ) values were similar in the two groups . There was a significant decrease in A1c value at 6 months in iBGStar ® group compared to the control group ( −0.16 vs. −0.51 , p = 0.04 ) . The total insulin dose increased significantly in the iBGStar ® group at 3 months but did not change at 6 months . The hypoglycemia fear scale ( PRO ) improved in both groups at 6 months ( −1.4 ± 10.0 vs. −3.9 ± 12.5 , p = 0.32 ) . Conclusion The use of iBGStar ® result ed in better glycemic control and improvement in some PRO ( hypoglycemia fear and behavior scores ) compared to the control group at 6 months with no increased risk of hypoglycemia . Clinical trial registration Clinical Trials.gov : NCT01825382 . Funding Sanofi Background Mobile health apps for diabetes self-management have different functions . However , the efficacy and safety of each function are not well studied , and no classification is available for these functions . Objective The aims of this study were to ( 1 ) develop and vali date a taxonomy of apps for diabetes self-management , ( 2 ) investigate the glycemic efficacy of  mobile app-based interventions among adults with diabetes in a systematic review of r and omized controlled trials ( RCTs ) , and ( 3 ) explore the contribution of different function to the effectiveness of entire app-based interventions using the taxonomy . Methods We developed a 3-axis taxonomy with columns of clinical modules , rows of functional modules and cells of functions with risk assessment s. This taxonomy was vali date d by review ing and classifying commercially available diabetes apps . We search ed MEDLINE , EMBASE , the Cochrane Central Register of Controlled Trials , the Chinese Biomedical Literature Data base , and Clinical Trials.gov from January 2007 to May 2016 . We included RCTs of adult out patients with diabetes that compared using  mobile app-based interventions with usual care alone . The mean differences ( MDs ) in hemoglobin A1c ( HbA1c ) concentrations and risk ratios of adverse events were pooled using a r and om-effects meta- analysis . After taxonomic classification , we performed exploratory subgroup analyses of the presence or absence of each module across the included app-based interventions . Results Across 12 included trials involving 974 participants , using app-based interventions was associated with a clinical ly significant reduction of HbA1c ( MD 0.48 % , 95 % CI 0.19%-0.78 % ) without excess adverse events . Larger HbA1c reductions were noted among patients with type 2 diabetes than those with type 1 diabetes ( MD 0.67 % , 95 % CI 0.30%-1.03 % vs MD 0.37 % , 95 % CI –0.12%-0.86 % ) . Having a complication prevention module in app-based interventions was associated with a greater HbA1c reduction ( with complication prevention : MD 1.31 % , 95 % CI 0.66%-1.96 % vs without : MD 0.38 % , 95 % CI 0.09%-0.67 % ; intersubgroup P=.01 ) , as was having a structured display ( with structured display : MD 0.69 % , 95 % CI 0.32%-1.06 % vs without : MD 0.69 % , 95 % CI –0.18%-0.53 % ; intersubgroup P=.03 ) . However , having a clinical decision-making function was not associated with a larger HbA1c reduction ( with clinical decision making : MD 0.19 % , 95 % CI –0.24%-0.63 % vs without : MD 0.61 % , 95 % CI 0.27%-0.95 % ; intersubgroup P=.14 ) . Conclusions The use of mobile app-based interventions yields a clinical ly significant HbA1c reduction among adult out patients with diabetes , especially among those with type 2 diabetes . Our study suggests that the clinical decision-making function needs further improvement and evaluation before being added to apps OBJECTIVE Widespread use of carbohydrate counting is limited by its complex education . In this study we compared a Diabetes Interactive Diary ( DID ) with st and ard carbohydrate counting in terms of metabolic and weight control , time required for education , quality of life , and treatment satisfaction . RESEARCH DESIGN AND METHODS Adults with type 1 diabetes were r and omly assigned to DID ( group A , n = 67 ) or st and ard education ( group B , n = 63 ) and followed for 6 months . A subgroup also completed the  SF-36 Health Survey ( SF-36 ) and World Health Organization-Diabetes Treatment Satisfaction Question naire ( WHO-DTSQ ) at each visit . RESULTS Of 130 patients ( aged 35.7 ± 9.4 years ; diabetes duration 16.5 ± 10.5 years ) , 11 dropped out .  Time for education was 6 h ( range 2–15 h ) in group A and 12 h ( 2.5–25 h ) in group B ( P = 0.07 ) . A1C reduction was similar in both groups ( group A from 8.2 ± 0.8 to 7.8 ± 0.8 % and group B from 8.4 ± 0.7 to 7.9 ± 1.1 % ; P = 0.68 ) . Nonsignificant differences in favor of group A were documented for fasting blood glucose and body weight . No severe hypoglycemic episode occurred . WHO-DTSQ scores increased significantly more in group A ( from 26.7 ± 4.4 to 30.3 ± 4.5 ) than in group B ( from 27.5 ± 4.8 to 28.6 ± 5.1 ) ( P = 0.04 ) . Role Physical , General Health , Vitality , and Role Emotional SF-36 scores improved significantly more in group A than in group B. CONCLUSIONS DID is at least as effective as traditional carbohydrate counting education , allowing dietary freedom for a larger proportion of type 1 diabetic patients . DID is safe , requires less time for education , and is associated with lower weight gain . DID significantly improved treatment satisfaction and several quality -of-life dimensions The dem and for new healthcare services is growing rapidly . Improving accessibility of the African population to diabetes care seems to be a big challenge in most countries where the number of care centers and medical staff is reduced . Information and communication technologies ( ICT ) have great potential to address some of these challenges faced by several countries in providing accessible , cost-effective , and high- quality health care services . This paper presents the Mobil Diab system which is a telemedical approach proposed for the management of long-term diseases . The system applies modern mobile and web technologies which overcome geographical barriers , and increase access to health care services . The idea of the system is to involve patients in the therapy process and motivate them for an active participation . For validation of the system in African context , a trial was conducted in the Democratic Republic of Congo . 40 Subjects with diabetes divided r and omly into control and intervention groups were included in the test . Results show that Mobil Diab is suitable for African countries and presents a number of benefits for the population and public health care system . It improves clinical management and delivery of diabetes care services by enhancing access , quality , motivation , reassurance , efficiency , and cost-effectiveness Background Adoptions of health behaviors are crucial for maintaining good health after type 2 diabetes mellitus ( T2DM ) diagnoses . However , adherence to glucoregulating behaviors like regular exercise and balanced diet can be challenging , especially for people living in lower-socioeconomic status ( SES ) communities . Providing cost-effective interventions that improve self-management is important for improving quality of life and the sustainability of health care systems . Objective To evaluate a health coach intervention with and without the use of mobile phones to support health behavior change in patients with type 2 diabetes . Methods In this noninferiority , pragmatic r and omized controlled trial ( RCT ) , patients from two primary care health centers in Toronto , Canada , with type 2 diabetes and a glycated hemoglobin/hemoglobin A1c ( HbA1c ) level of ≥7.3 % ( 56.3 mmol/mol ) were r and omized to receive 6 months of health coaching with or without mobile phone monitoring support . We hypothesized that both approaches would result in significant HbA1c reductions , although health coaching with mobile phone monitoring would result in significantly larger effects . Participants were evaluated at baseline , 3 months , and 6 months . The primary outcome was the change in HbA1c from baseline to 6 months ( difference between and within groups ) . Other outcomes included weight , waist circumference , body mass index ( BMI ) , satisfaction with life , depression and anxiety ( Hospital Anxiety and Depression Scale [ HADS ] ) , positive and negative affect ( Positive and Negative Affect Schedule [ PANAS ] ) , and quality of life ( Short Form Health Survey-12 [ SF-12 ] ) . Results A total of 138 patients were r and omized and 7 were excluded for a sub study ; of the remaining 131 , 67 were allocated to the intervention group and 64 to the control group  . Primary outcome data were available for 97 participants ( 74.0 % ) . While both groups reduced their HbA1c levels , there were no significant between-group differences in change of HbA1c at 6 months using intention-to-treat ( last observation carried forward [ LOCF ] ) ( P=.48 ) or per- protocol ( P=.83 ) principles . However , the intervention group did achieve an accelerated HbA1c reduction , leading to a significant between-group difference at 3 months ( P=.03 ) . This difference was reduced at the 6-month follow-up as the control group continued to improve , achieving a reduction of 0.81 % ( 8.9 mmol/mol ) ( P=.001 ) compared with a reduction of 0.84 % ( 9.2 mmol/mol)(P=.001 ) in the intervention group . Intervention group participants also had significant decreases in weight ( P=.006 ) and waist circumference ( P=.01 ) while controls did not . Both groups reported improvements in mood , satisfaction with life , and quality of life .  Conclusions Health coaching with and without access to mobile technology appeared to improve glucoregulation and mental health in a lower-SES , T2DM population . The accelerated improvement in the mobile phone group suggests the connectivity provided may more quickly improve adoption and adherence to health behaviors within a clinical diabetes management program . Overall , health coaching in primary care appears to lead to significant benefits for patients from lower-SES communities with poorly controlled type 2 diabetes . Trial Registration Clinical Trials.gov NCT02036892 ; http:// clinical trials.gov/ct2/show/NCT02036892 ( Arch 
    Output:
    
Patients did not experience improvements in quality of life , blood pressure , or weight , regardless of app used or type of diabetes .
Discussion Limited evidence suggests that use of some commercially available apps , when combined with additional support from a healthcare provider or study staff , may improve some short-term diabetes-related outcomes .
The impact of these apps on longer-term outcomes is unclear .