***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: OBJECTIVES Many individuals are advised to adhere to specific diet plans for their personal health ; hence , it is important that tools are available to support these behaviors . Smartphone applications ( apps ) may assist health care professionals in educating their clients on specific dietary modifications . This pilot study focused on a single dietary modification , reducing sodium intake , to determine whether a commercial health app is useful for promoting dietary change . METHODS Thirty healthy adults ( age 34.4 ± 15.7 y ; body mass index 25.6 ± 4.3 kg/m2 ) were recruited from a university community and completed this 4-wk r and omized parallel trial . Participants were instructed to reduce their sodium intake to ≤2300 mg/d by using the MyFitnessPal app to receive feedback on sodium content of foods or by paper tallying of estimated sodium intake .  The predicted 24-h sodium excretion , estimated using the ratio of sodium to creatinine from the first morning urine void , and participant satisfaction were the main outcomes measured . RESULTS The change in the predicted 24-h sodium excretion differed between groups : -838 ± 1093 and + 236 ± 1333 mg/24 h predicted for the app and journal groups , respectively ( P = 0.010 ) . Moreover , participants in the app group reported significantly greater satisfaction with their method of diet tracking than the journal group ( P = 0.001 ) . CONCLUSIONS These data suggest that smartphone apps have the potential to facilitate the implementation of dietary advice . This was a small pilot study with limited scope , and more research is necessary to determine the value of smartphone apps for facilitating dietary change Background Mobile apps present a potentially cost-effective tool for delivering behavior change interventions at scale , but no known studies have tested the efficacy of apps as a tool to specifically increase vegetable consumption  among overweight adults . Objective The purpose of this pilot study was to assess the initial efficacy and user acceptability of a theory-driven mobile app to increase vegetable consumption . Methods A total of 17 overweight adults aged 42.0 ( SD 7.3 ) years with a body mass index ( BMI ) of 32.0 ( SD 3.5 ) kg/m2 were r and omized to the use of Vegethon ( a fully automated theory-driven mobile app enabling self-monitoring of vegetable consumption , goal setting , feedback , and social comparison ) or a wait-listed control condition .  All participants were recruited from an ongoing 12-month weight loss trial ( parent trial ) . Research ers who performed data analysis were blinded to condition assignment . The primary outcome measure was daily vegetable consumption , assessed using an adapted version of the vali date d Harvard Food Frequency Question naire administered at baseline and 12 weeks after r and omization . An analysis of covariance was used to assess differences in 12-week vegetable consumption between intervention and control conditions , controlling for baseline . App usability and satisfaction were measured via a 21-item post-intervention question naire . Results Using intention-to-treat analyses , all enrolled participants ( intervention : 8 ; control : 9 ) were analyzed . Of the 8 participants r and omized to the intervention , 5 downloaded the app and logged their vegetable consumption a mean of 0.7 ( SD 0.9 ) times per day , 2 downloaded the app but did not use it , and 1 never downloaded it . Consumption of vegetables was significantly greater among the intervention versus control condition at the end of the 12-week pilot study ( adjusted mean difference : 7.4 servings ; 95 % CI 1.4 - 13.5 ; P=.02 ) . Among secondary outcomes defined a priori , there was significantly greater consumption of green leafy vegetables , cruciferous vegetables , and dark yellow vegetables ( adjusted mean difference : 2.6 , 1.6 , and 0.8 servings ; 95 % CI 0.1 - 5.0 , 0.1 - 3.2 , and 0.3 - 1.4 ; P=.04 , P=.04 , and P=.004 , respectively ) . Participants reported positive experiences with the app , including strong agreement with the statements “ I have found Vegethon easy to use ” and “ I would recommend Vegethon to a friend ” ( mean 4.6 ( SD 0.6 ) and 4.2 ( SD 0.8 ) , respectively , ( on a 5-point scale ) . Conclusions Vegethon demonstrated initial efficacy and user acceptability . A mobile app intervention may be useful for increasing vegetable consumption  among overweight adults . The small sample size prevented precise estimates of effect sizes . Given the improved health outcomes associated with increases in vegetable consumption , these findings indicate the need for larger , longer-term evaluations of Vegethon and similar technologies among overweight adults and other suitable target groups . Trial Registration Clinical Trials.gov NCT01826591 ; https:// clinical trials.gov/ct2/show/NCT01826591 ( Archived by WebCite at http://www.webcitation.org/6hYDw2AOB Background Conventional face-to-face weight loss and weight control programs are very labor intensive for both the patient and the provider . It is unclear to what extent conventional programs can be ( partially ) completed by mobile health ( mHealth ) apps . Objective The aim of this study was to compare the effectiveness of different weight loss programs using a combination of conventional and mobile programs among adults who are overweight ( body mass index [ BMI ] > 29 kg/m² ) . Methods A single-blinded r and omized controlled trial among obese adults was performed from September 2015 to March 2016 . The study took place in Leuven , Belgium . Of the 102 eligible ( BMI > 29 kg/m² ) adults , 81 ( 79 % ) completed the study . The three intervention groups consisted of a conventional face-to-face weight loss program , a weight loss app program ( app group ) , and a partial face-to-face and partial app program ( combi group ) . All intervention groups received the same advice from a dietician and a physical activity coach during a 12-week period . The control group did not receive any information during the same period . Primary outcomes were weight reduction ( 5 % decrease of baseline weight in kg ) , BMI , metabolic risk factors , dietary pattern , and physical activity . Results Significant more participants in all three intervention groups lost at least 5 % or more of their weight at baseline compared with the control group . No significant difference was found between the combi group and the conventional group . A trend was found that more participants in the combi group lost 5 % or more compared with the app group ( 19 % ) , P=.06 . A significant time x group effect was found for BMI and metabolic risk factors , with the control group having the worst results and the combi group being significantly better with regard to BMI compared with the app group . No significant group x time effects were found for the intake of different food and drinks and moderate to vigorous physical activity ( MVPA ) . Conclusions The results of this study show that a conventional weight loss program could partially be completed with an mHealth program without affecting the effectiveness . Trial Registration Clinical trials.gov NCT02595671 ; https:// clinical trials.gov/ct2/show/NCT02595671 ( Archived by WebCite at http://www.webcitation.org/6w1H0x1Q6 Background Obesity is a growing global issue that is linked to cognitive and psychological deficits . Objective This preliminary study investigated the efficacy of training to improve  inhibitory control ( IC ) , a process linked to overeating , on consumption and cognitive control factors . Methods This study utilized a multisession mobile phone – based intervention to train IC in an overweight and obese population using a r and omized waitlist-control design . A combination of self- assessment question naires and psychophysiological measures was used to assess the efficacy of the intervention in terms of improved general IC and modified food consumption after training . Attitudes toward food were also assessed to determine their mediating role in food choices . A total of 58 participants ( 47 female ) completed 2 assessment sessions 3 weeks apart , with 2 weeks of intervention training for the training group during this time . The groups did not differ in baseline demographics including age , body mass index , and inhibitory control . Results Inhibitory control ability improved across the training sessions , with increases in P3 amplitude implying increased cognitive control over responses . Inhibitory control training was associated with increased healthy and reduced unhealthy food consumption in a taste test and in the week following training , as measured by the Healthy Eating Quiz and the food consumption test . Cognitive restraint was enhanced after training for the training but not the waitlist condition in the Three-Factor Eating Question naire , implying that attempts to avoid unhealthy foods in the future will be easier for the training group participants . Conclusions Inhibitory control training delivered via a purpose - design ed mobile phone app is easy to complete , is convenient , and can increase cognitive restraint and reduce unhealthy food consumption . Trial Registration Australian New Zeal and Clinical Trials Registry ACTRN12616000263493 ; http://www.ANZCTR.org.au/ACTRN12616000263493.aspx ( Archived by WebCite at http://www.webcitation.org/6ioHjGING Background Growing evidence shows that fixed , nonpersonalized daily step goals can discourage individuals , result ing in unchanged or even reduced physical activity . Objective The aim of this r and omized controlled trial ( RCT ) was to evaluate the efficacy of an automated mobile phone – based personalized and adaptive goal - setting intervention using machine learning as compared with an active control with steady daily step goals of 10,000 . Methods In this 10-week RCT , 64 participants were recruited via email announcements and were required to attend an initial in-person session . The participants were r and omized into either the intervention or active control group with a one-to-one ratio after a run-in period for data collection . A study -developed mobile phone app ( which delivers daily step goals using push notifications and allows real-time physical activity monitoring ) was installed on each participant ’s mobile phone , and participants were asked to keep their phone in a pocket throughout the entire day . Through the app , the intervention group received fully automated adaptively personalized daily step goals , and the control group received constant step goals of 10,000 steps per day . Daily step count was objective ly measured by the study -developed mobile phone app . Results The mean ( SD ) age of participants was 41.1 ( 11.3 ) years , and 83 % ( 53/64 ) of participants were female . The baseline demographics between the 2 groups were similar ( P>.05 ) . Participants in the intervention group ( n=34 ) had a decrease in mean ( SD ) daily step count of 390 ( 490 ) steps between run-in and 10 weeks , compared with a decrease of 1350 ( 420 ) steps among control participants ( n=30 ; P=.03 ) . The net difference in daily steps between the groups was 960 steps ( 95 % CI 90 - 1830 steps ) . Both groups had a decrease in daily step count between run-in and 10 weeks because interventions were also provided during run-in and no natural baseline was collected . Conclusions The results showed the short-term efficacy of this intervention , which should be formally evaluated in a full-scale RCT with a longer follow-up period . Trial Registration Clinical Trials.gov : NCT02886871 ; https:// clinical trials.gov/ct2/show/NCT02886871 ( Archived by WebCite at http://www.webcitation.org/6wM1Be1Ng ) Background : Evidence on the efficacy of smartphone applications ( apps ) for reducing body weight and other measurements of adiposity sustainably is not conclusive . Objective : To evaluate the effect of adding an app for 3 months to traditional counselling on physical activity ( PA ) and a heart-healthy diet for the modification of measurements of adiposity at 3 and 12 months after intervention . Methods : This r and omised clinical trial included 833 subjects . The  counselling and app group ( IG ) had 415 subjects , while 418 were included in the counselling only group ( CG ) . The primary outcome was adiposity measurements at 3 and 12 months after intervention . The secondary outcome was the effect of the intervention by sex . Intervention : Counselling on a heart-healthy diet and PA was given to both groups . The IG also received training in the use of a smartphone app design ed to promote a heart-healthy diet and PA , and this group was given access to this application for 3 months . Outcome measurements included waist circumference ( WC ) , body mass index ( BMI ) and Clínica Universidad de Navarra – body adiposity estimator ( CUN-BAE ) . Results : In the IG at 12 months , the following decreased : WC −0.72 cm ( 95 % confidence interval [ CI ] : −2.35 to −0.02 ) and CUN-BAE −0.35 ( 95 % CI : −0.63 to −0.06 ) . These decreases were only observed in women . After baseline adjustment , the beneficial effect was maintained in the IG compared to the CG at 12 months in terms of WC ( −0.67 ; 95 % CI : −0.29 to −0.02 ) and CUN-BAE ( −0.57 ; 95 % CI : −1.10 to −0.04 ) , but only in women . Conclusions : An intervention of nutritional counselling and PA plus the smartphone app with personalised recommendations compared to CG showed beneficial results in terms of reduction of abdominal obesity and the percentage of body fat in women , but not in men Background Mobile applications ( apps ) have been heralded as transformative tools to deliver behavioral health interventions at scale , but few have been tested in rigorous r and omized controlled trials . We tested 
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However , there was little evidence of changed behavior or health outcomes .
There was no strong evidence in support of the effectiveness of mobile apps in improving health behaviors or outcomes because few studies found significant differences between the app and control groups .