***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: 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 Health education and behavior change programs targeting specific risk factors have demonstrated their effectiveness in reducing the development of future diseases . Alzheimer disease ( AD ) shares many of the same risk factors , most of which can be addressed via behavior change . It is therefore theorized that a behavior change intervention targeting these risk factors would likely result in favorable rates of AD prevention . Objective The objective of this study was to reduce the future risk of developing AD , while in the short term promoting vascular health , through behavior change . Methods The study was an interventional r and omized controlled trial consisting of subjects who were r and omly assigned into either treatment ( n=102 ) or control group ( n=42 ) . Outcome measures included various blood-based biomarkers , anthropometric measures , and behaviors related to AD risk . The treatment group was provided with a bespoke “ Gray Matters ” mobile phone app design ed to encourage and facilitate behavior change . The app presented evidence -based educational material relating to AD risk and prevention strategies , facilitated self-reporting of behaviors across 6 behavioral domains , and presented feedback on the user ’s performance , calculated from reported behaviors against recommended guidelines . Results This paper explores the rationale for a mobile phone – led intervention and details the app ’s effect on behavior change and subsequent clinical outcomes . Via the app , the average participant su bmi tted 7.3 ( SD 3.2 ) behavioral logs/day ( n=122,719 ) . Analysis of these logs against primary outcome measures revealed that participants who improved their high-density lipoprotein cholesterol levels during the study duration answered a statistically significant higher number of questions per day ( mean 8.30 , SD 2.29 ) than those with no improvement ( mean 6.52 , SD 3.612 ) , t97.74=−3.051 , P=.003 . Participants who decreased their body mass index ( BMI ) performed significantly better in attaining their recommended daily goals ( mean 56.21 SD 30.4 % ) than those who increased their BMI ( mean 40.12 SD 29.1 % ) , t80 = −2.449 , P=.017 . In total , 69.2 % ( n=18 ) of those who achieved a mean performance percentage of 60 % or higher , across all domains , reduced their BMI during the study , whereas 60.7 % ( n=34 ) who did not , increased their BMI . One-way analysis of variance of systolic blood pressure category changes showed a significant correlation between reported efforts to reduce stress and category change as a whole , P=.035 . An exit survey highlighted that respondents ( n=83 ) reported that the app motivated them to perform physical activity ( 85.4 % ) and make healthier food choices ( 87.5 % ) . Conclusions In this study , the ubiquitous nature of the mobile phone excelled as a delivery platform for the intervention , enabling the dissemination of educational intervention material while simultaneously monitoring and encouraging positive behavior change , result ing in desirable clinical effects . Sustained effort to maintain the achieved behaviors is expected to mitigate future AD risk . Trial Registration Clinical Trails.gov NCT02290912 ; https:// clinical trials.gov/ct2/show/NCT02290912 ( Archived by WebCite at http://www.webcitation.org/6ictUEwnm Background Home-based exercise programs can improve physical functioning and health status of elderly people . Successful implementation of exercise interventions for older people presents major challenges and supporting elderly people properly while doing their home-based exercises is essential for training success . We developed a tablet-based system — ActiveLifestyle — that offers older adults a home-based strength-balance training program with incorporated motivation strategies and support features . Objective The goal was to compare 3 different home-based training programs with respect to their effect on measures of gait quality and physical performance through planned comparisons between ( 1 ) tablet-based and brochure-based interventions , ( 2 ) individual and social motivation strategies , and ( 3 ) active and inactive participants . Methods A total of 44 autonomous-living elderly people ( mean 75 , SD 6 years ) were assigned to 3 training groups : social ( tablet guided , n=14 ) , individual ( tablet guided , n=13 ) , and brochure ( brochure guided , n=17 ) . All groups joined a 12-week progressive home-based strength-balance training program . Outcome measures were gait performance under single and dual task conditions , dual task costs of walking , falls efficacy , and physical performance as measured by the Short Physical Performance Battery ( SPPB ) . Furthermore , active ( ≥75 % program compliance ) and inactive ( < 75 % program compliance ) individuals were compared based on their characteristics and outcome measures . Results The tablet groups showed significant improvements in single and dual task walking , whereas there were no significant changes observable in the brochure group . Between-groups comparisons revealed significant differences for gait velocity ( U=138.5 ; P=.03 , r=.33 ) and cadence ( U=138.5 , P=.03 r=.34 ) during dual task walking at preferred speed in favor of the tablet groups . The brochure group had more inactive participants , but this did not reach statistical significance ( U=167 , P=.06 , r=.29 ) . The active participants outperformed the inactive participants in single and dual task walking , dual task costs of walking , and SPPB scores . Significant between-groups differences were seen between the tablet groups and the brochure group , in favor of the tablet groups . Conclusions A tablet-based strength-balance training program that allows monitoring and assisting autonomous-living older adults while training at home was more effective in improving gait and physical performance when compared to a brochure-based program . Social or individual motivation strategies were equally effective . The most prominent differences were observed between active and inactive participants . These findings suggest that in older adults a tablet-based intervention enhances training compliance ; hence , it is an effective way to improve gait IMPORTANCE Mobile smartphones are rapidly emerging as an effective means of communicating with many Americans  .  Using mobile applications ( apps ) , they can access remote data bases , track time and location , and integrate user input to provide tailored health information . OBJECTIVE A smartphone mobile app providing personalized , real-time sun protection advice was evaluated in a r and omized clinical trial . DESIGN , SETTING , AND PARTICIPANTS The trial was conducted in 2012 and had a r and omized pretest-posttest controlled design with a 10-week follow-up . Data were collected from a nationwide population -based survey panel . A sample of 604 non-Hispanic and Hispanic adults from the Knowledge Panel 18 years or older who owned an And roid smartphone were enrolled . INTERVENTIONS The mobile app provided advice on sun protection ( ie , protection practice s and risk of sunburn ) and alerts ( to apply or reapply sunscreen and get out of the sun ) , hourly UV Index , and vitamin D production based on the forecast UV Index , the phone 's time and location , and user input . MAIN OUTCOMES AND MEASURES Percentage of days using sun protection and time spent outdoors ( days and minutes ) in the midday sun and number of sunburns in the past 3 months were collected . RESULTS Individuals in the treatment group reported more shade use ( mean days staying in the shade , 41.0 % vs 33.7 % ; P = .03 ) but less sunscreen use ( mean days , 28.6 % vs 34.5 % ; P = .048 ) than controls . There was no significant difference in number of sunburns in the past 3 months ( mean , 0.60 in the treatment group vs 0.62 for controls ; P = .87 ) . Those who used the mobile app reported spending less time in the sun ( mean days keeping time in the sun to a minimum , 60.4 % for app users vs 49.3 % for nonusers ; P = .04 ) and using all protection behaviors combined more ( mean days , 39.4 % vs 33.8 % ; P = .04 ) . CONCLUSIONS AND RELEVANCE The mobile app improved some sun protection . Use of the mobile app was lower than expected but associated with increased sun protection . Providing personalized advice when and where people are in the sun may help reduce sun exposure Background Brief interventions via the internet have been shown to reduce university students ’ alcohol intake . This study tested two smartphone applications ( apps ) targeting drinking choices on party occasions , with the goal of reducing problematic alcohol intake among Swedish university students . Methods Students were recruited via e-mails sent to student union members at two universities . Those who gave informed consent , had a smartphone , and showed risky alcohol consumption according to the Alcohol Use Disorders Identification Test ( AUDIT ) were r and omized into three groups . Group 1 had access to the Swedish government alcohol monopoly ’s app , Promillekoll , offering real-time estimated blood alcohol concentration ( eBAC ) calculation ; Group 2 had access to a web-based app , PartyPlanner , developed by the research group , offering real-time eBAC calculation with planning and follow-up functions ; and Group 3 participants were controls . Follow-up was conducted at 7 weeks . Results Among 28574 students offered participation , 4823 agreed to join ; 415 were excluded due to incomplete data , and 1932 fulfilled eligibility criteria for r and omization . Attrition was 22.7–39.3 percent , higher among heavier drinkers and highest in Group 2 .  Self-reported app use was higher in Group 1 ( 74 % ) compared to Group 2 ( 41 % ) . Per- protocol analyses revealed only one significant time-by-group interaction , where Group 1 participants increased the frequency of their drinking occasions compared to controls ( p = 0.001 ) . Secondary analyses by gender showed a significant difference among men in Group 1 for frequency of drinking occasions per week ( p = 0.001 ) , but not among women . Among all participants , 29 percent showed high-risk drinking , over the recommended weekly drinking levels of 9 ( women ) and 14 ( men ) st and ard glasses . Conclusions Smartphone apps can make brief interventions available to large numbers of university students . The apps studied using eBAC calculation did not , however , seem to affect alcohol consumption among university students and one app may have led to a negative effect among men . Future research should : 1 ) explore ways to increase user retention , 2 ) include apps facilitating technical manipulation for evaluation of added components , 3 ) explore the effects of adapting app content to possible gender differences , and 4 ) offer additional interventions to high-risk users . Trial registration clinical trials.gov : NCT01958398 BACKGROUND Few weight loss interventions are evaluated 
    Output:
    
Overall , the evidence so far showed a modest efficacy of apps in health promotion .