***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 Web-based and mobile health interventions ( also called “ Internet interventions ” or " eHealth/mHealth interventions ") are tools or treatments , typically behaviorally based , that are operationalized and transformed for delivery via the Internet or mobile platforms . These include electronic tools for patients , informal caregivers , healthy consumers , and health care providers . The Consoli date d St and ards of Reporting Trials ( CONSORT ) statement was developed to improve the suboptimal reporting of r and omized controlled trials ( RCTs ) . While the CONSORT statement can be applied to provide broad guidance on how eHealth and mHealth trials should be reported , RCTs of web-based interventions pose very specific issues and challenges , in particular related to reporting sufficient details of the intervention to allow replication and theory-building . Objective To develop a checklist , dubbed CONSORT-EHEALTH ( Consoli date d St and ards of Reporting Trials of Electronic and Mobile HEalth Applications and onLine TeleHealth ) , as an extension of the CONSORT statement that provides guidance for authors of eHealth and mHealth interventions . Methods A literature review was conducted , followed by a survey among eHealth experts and a workshop . Results A checklist instrument was constructed as an extension of the CONSORT statement . The instrument has been adopted by the Journal of Medical Internet Research ( JMIR ) and authors of eHealth RCTs are required to su bmi t an electronic checklist explaining how they addressed each subitem . Conclusions CONSORT-EHEALTH has the potential to improve reporting and provides a basis for evaluating the validity and applicability of eHealth trials . Subitems describing how the intervention should be reported can also be used for non- RCT evaluation reports . As part of the development process , an evaluation component is essential ; therefore , feedback from authors will be solicited , and a before-after study will evaluate whether reporting has been improved Developing an evidence base for making public health decisions will require using data from evaluation studies with r and omized and nonr and omized design s. Assessing individual studies and using studies in quantitative research syntheses require transparent reporting of the study , with sufficient detail and clarity to readily see differences and similarities among studies in the same area . The Consoli date d St and ards of Reporting Trials ( CONSORT ) statement provides guidelines for transparent reporting of r and omized clinical trials . We present the initial version of the Transparent Reporting of Evaluations with Nonr and omized Design s ( TREND ) statement . These guidelines emphasize the reporting of theories used and descriptions of intervention and comparison conditions , research design , and methods of adjusting for possible biases in evaluation studies that use nonr and omized design Background Women ’s physical activity levels decline during their transition to parenthood . Facebook is widely used by Australian mothers and provides the opportunity to target social networks in order to maintain and increase physical activity . Method This mixed method study aim ed to pilot and assess the usability of the Mums Step It Up Facebook app , a new team-based physical activity intervention for mothers with young children . A purposive sample of five “ Captain ” women with young children , were recruited through personal contacts . These women used the app to recruit 3–7 Facebook friends ( with children under 5 ) to join their respective teams ( total n = 25 ) . The app encourages women to take 10,000 steps a day measured by a pedometer . Women used the app for 28 days to log steps , interact with team mates and monitor progress . Physical activity was assessed at two time points ( baseline and final week ) using the Active Australia Survey . Usability testing with the five “ Captain ” women took place over two one hour face-to-face sessions . A question naire seeking feedback on the app was completed at time point two . Results  Participants ’ total physical activity increased by an average of 177 minutes per week ( p = 0.01 ) . The complexity of the team forming process and issues using the Facebook environment , where a variety of devices and software platforms are used , was highlighted . Discussion A team-based Facebook app shows considerable promise for the recruitment and retention of participants to a social network-based physical activity intervention . A r and omised controlled trial to further evaluate the effectiveness of the intervention is warranted BACKGROUND Despite the increasing popularity of activity trackers , little evidence exists that they can improve health outcomes . We aim ed to investigate whether use of activity trackers , alone or in combination with cash incentives or charitable donations , lead to increases in physical activity and improvements in health outcomes . METHODS In this r and omised controlled trial , employees from 13 organisations in Singapore were r and omly assigned ( 1:1:1:1 ) with a computer generated assignment schedule to control ( no tracker or incentives ) , Fitbit Zip activity tracker , tracker plus charity incentives , or tracker plus cash incentives .  Participants had to be English speaking , full-time employees , aged 21 - 65 years , able to walk at least ten steps continuously , and non-pregnant . Incentives were tied to weekly steps , and the primary outcome , moderate-to-vigorous physical activity ( MVPA ) bout min per week , was measured via a sealed accelerometer and assessed on an intention-to-treat basis at 6 months ( end of intervention ) and 12 months ( after a 6 month post-intervention follow-up period ) . Other outcome measures included steps , participants meeting 70 000 steps per week target , and health-related outcomes including weight , blood pressure , and quality -of-life measures . This trial is registered at Clinical Trials.gov , number NCT01855776 . FINDINGS Between June 13 , 2013 , and Aug 15 , 2014 , 800 participants were recruited and r and omly assigned to the control ( n=201 ) , Fitbit ( n=203 ) , charity ( n=199 ) , and cash ( n=197 ) groups . At 6 months , compared with control , the cash group logged an additional 29 MVPA bout min per week ( 95 % CI 10 - 47 ; p=0·0024 ) and the charity group an additional 21 MVPA bout min per week ( 2 - 39 ; p=0·0310 ) ; the difference between Fitbit only and control was not significant ( 16 MVPA bout min per week [ -2 to 35 ; p=0·0854 ] ) . Increases in MVPA bout min per week in the cash and charity groups were not significantly greater than that of the Fitbit group . At 12 months , the Fitbit group logged an additional 37 MVPA bout min per week ( 19 - 56 ; p=0·0001 ) and the charity group an additional 32 MVPA bout min per week ( 12 - 51 ; p=0·0013 ) compared with control ; the difference between cash and control was not significant ( 15 MVPA bout min per week [ -5 to 34 ; p=0·1363 ] ) . A decrease in physical activity of -23 MVPA bout min per week ( 95 % CI -42 to -4 ; p=0·0184 ) was seen when comparing the cash group with the Fitbit group . There were no improvements in any health outcomes ( weight , blood pressure , etc ) at either assessment . INTERPRETATION The cash incentive was most effective at increasing MVPA bout min per week at 6 months , but this effect was not sustained 6 months after the incentives were discontinued . At 12 months , the activity tracker with or without charity incentives were effective at stemming the reduction in MVPA bout min per week seen in the control group , but we identified no evidence of improvements in health outcomes , either with or without incentives , calling into question the value of these devices for health promotion . Although other incentive strategies might generate greater increases in step activity and improvements in health outcomes , incentives would probably need to be in place long term to avoid any potential decrease in physical activity result ing from discontinuation . FUNDING Ministry of Health , Singapore Background While there has been an explosion of mobile device applications ( apps ) promoting healthful behaviors , including physical activity and sedentary patterns , surprisingly few have been based explicitly on strategies drawn from behavioral theory and evidence . Objective This study provided an initial 8-week evaluation of three different customized physical activity-sedentary behavior apps drawn from conceptually distinct motivational frames in comparison with a commercially available control app . Study Design and Methods Ninety-five underactive adults ages 45 years and older with no prior smartphone experience were r and omized to use an analytically framed app , a socially framed app , an affectively framed app , or a diet-tracker control app .  Daily physical activity and sedentary behavior were measured using the smartphone ’s built-in accelerometer and daily self-report measures . Results Mixed-effects models indicated that , over the 8-week period , the social app users showed significantly greater overall increases in weekly accelerometry-derived moderate to vigorous physical activity relative to the other three arms ( P values for between-arm differences = .04-.005 ; Social vs. Control app : d = 1.05 , CI = 0.44,1.67 ; Social vs. Affect app : d = 0.89 , CI = 0.27,1.51 ; Social vs. Analytic app : d = 0.89 , CI = 0.27,1.51 ) , while more variable responses were observed among users of the other two motivationally framed apps . Social app users also had significantly lower overall amounts of accelerometry-derived sedentary behavior relative to the other three arms ( P values for between-arm differences = .02-.001 ; Social vs. Control app : d = 1.10,CI = 0.48,1.72 ; Social vs. Affect app : d = 0.94 , CI = 0.32,1.56 ; Social vs. Analytic app : d = 1.24 , CI = 0.59,1.89 ) . Additionally , Social and Affect app users reported lower overall sitting time compared to the other two arms ( P values for between-arm differences < .001 ; Social vs. Control app : d = 1.59,CI = 0.92 , 2.25 ; Social vs. Analytic app : d = 1.89,CI = 1.17 , 2.61 ; Affect vs. Control app : d = 1.19,CI = 0.56 , 1.81 ; Affect vs. Analytic app : d = 1.41,CI = 0.74 , 2.07 ) . Conclusion The results provide initial support for the use of a smartphone-delivered social frame in the early induction of both physical activity and sedentary behavior changes . The information obtained also sets the stage for further investigation of subgroups that might particularly benefit from different motivationally framed apps in these two key health promotion areas . Trial Registration Clinical Trials.gov Background In young men , unhealthy lifestyle behaviours can be detrimental to their physical and /or mental health and set them on a negative health trajectory into adulthood . Despite this , there is a lack of evidence to guide development of effective health behaviour change interventions for young men . This study assessed the feasibility and preliminary efficacy of the ‘ HEYMAN ’ ( Harnessing Ehealth to enhance Young men ’s Mental health , Activity and Nutrition ) healthy lifestyle program for young men . Methods A pilot RCT with 50 young men aged 18–25 years r and omised to the HEYMAN intervention ( n = 26 ) or waitlist control ( n = 24 ) .  HEYMAN was a 3-month intervention , targeted for young men to improve eating habits , activity levels and well-being . Intervention development was informed by a participatory research model ( PRECEDE-PROCEED ) . Intervention components included eHealth support ( website , wearable device , Facebook support group ) , face-to-face sessions ( group and individual ) , a personalised food and nutrient report , home-based resistance training equipment and a portion control tool . Outcomes included : feasibility of research procedures ( recruitment , r and omisation , data collection and retention ) and of intervention components . Generalized linear mixed models estimated the treatment effect at 3-months for the primary outcomes : pedometer steps/day , diet quality , well-being and several secondary outcomes . Results A 7-week recruitment period was required to enrol 50 young men .  A retention rate of 94 % was achieved at 3-months post-intervention . Retained intervention participants ( n = 24 ) demonstrated reasonable usage levels for most program components and also reported reasonable levels of program component acceptability for attractiveness , comprehension , usability , support , satisfaction and ability to persuade , with scores ranging from 3.0 to 4.6 ( maximum 5 ) . No significant intervention effects were observed for the primary outcomes of steps/day ( 1012.7 , 95 % CI = −506.2 , 2531.6 , p = 0.191 , d = 0.36 ) , diet quality score ( 3.6 , 95 % CI = −0.4 , 7.6 , p = 0.081 , d = 0.48 ) or total well-being score ( 0.4 , 95 % CI = −1.6 , 2.5 , p = 0.683 , d = 0.11 ) . Significant intervention effects were found for daily vegetable servings , energy-dense , nutrient-poor foods , MVPA , weight , BMI , fat mass , waist circumference and cholesterol ( all p < 0.05 ) . Conclusions The HEYMAN program demonstrated feasibility in assisting young men to make some positive lifestyle changes . This provides support for the conduct of a larger , fully-powered RCT , but with minor amendments to research procedures and intervention components required . Trial registration Australian New Zeal and Clinical Trials Registry ACTRN12616000350426 BACKGROUND This pilot study evaluated the feasibility and preliminary effectiveness of a 10-week WhatsApp-based intervention aim ed at enhancing health-related physical fitness components and cardiovascular disease ( CVD ) risk factors compared with a face-to- 
    Output:
    
Users ’ preferences of social features  were mixed : some felt more motivated by social support and competition , while others expressed concerns about comparison , indicating that a one-size-fits-all approach is insufficient .
In summary , this is an emerging area of research , with limited evidence suggesting that social features may increase user engagement .