human
***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 Obesity remains a serious issue in many countries . Web-based programs offer good potential for delivery of weight loss programs . Yet , many Internet-delivered weight loss studies include support from medical or nutritional experts , and relatively little is known about purely web-based weight loss programs . Objective To determine whether supportive features and personalization in a 12-week web-based lifestyle intervention with no in-person professional contact affect retention and weight loss . Methods We assessed the effect of different features of a web-based weight loss intervention using a 12-week repeated- measures r and omized parallel design . We developed 7 sites representing 3 functional groups . A national mass media promotion was used to attract overweight/obese Australian adults ( based on body mass index [ BMI ] calculated from self-reported heights and weights ) . Eligible respondents ( n = 8112 ) were r and omly allocated to one of 3 functional groups : information-based ( n = 183 ) , supportive ( n = 3994 ) , or personalized-supportive ( n = 3935 ) . Both supportive sites included tools , such as a weight tracker , meal planner , and social networking platform . The personalized-supportive site included a meal planner that offered recommendations that were personalized using an algorithm based on a user ’s preferences for certain foods . Dietary and activity information were constant across sites , based on an existing and tested 12-week weight loss program ( the Total Wellbeing Diet ) . Before and /or after the intervention , participants completed demographic ( including self-reported weight ) , behavioral , and evaluation question naires online . Usage of the website and features was objective ly recorded . All screening and data collection procedures were performed online with no face-to-face contact . Results Across all 3 groups , attrition was high at around 40 % in the first week and 20 % of the remaining participants each week . Retention was higher for the supportive sites compared to the information-based site only at week 12 ( P = .01 ) . The average number of days that each site was used varied significantly ( P = .02 ) and was higher for the supportive site at 5.96 ( SD 11.36 ) and personalized-supportive site at 5.50 ( SD 10.35 ) , relative to the information-based site at 3.43 ( SD 4.28 ) . In total , 435 participants provided a valid final weight at the 12-week follow-up . Intention-to-treat analyses ( using multiple imputations ) revealed that there were no statistically significant differences in weight loss between sites ( P = .42 ) . On average , participants lost 2.76 % ( SE 0.32 % ) of their initial body weight , with 23.7 % ( SE 3.7 % ) losing 5 % or more of their initial weight . Within supportive conditions , the level of use of the online weight tracker was predictive of weight loss ( model estimate = 0.34 , P < .001 ) . Age ( model estimate = 0.04 , P < .001 ) and initial BMI ( model estimate = -0.03 , P < .002 ) were associated with frequency of use of the weight tracker . Conclusions Relative to a static control , inclusion of social networking features and personalized meal planning recommendations in a web-based weight loss program did not demonstrate additive effects for user weight loss or retention . These features did , however , increase the average number of days that a user engaged with the system . For users of the supportive websites , greater use of the weight tracker tool was associated with greater weight loss The transition to college has been identified as a critical period for increases in overweight status . Overweight college students are at-risk of becoming obese adults , and , thus prevention efforts targeting college age individuals are key to reducing adult obesity rates . The current study evaluated an Internet intervention with first year college students ( N=170 ) r and omly assigned to one of four treatment conditions : 1 ) no treatment , 2 ) 6-week online intervention 3 ) 6-week weight and caloric feedback only ( via email ) , and 4 ) 6-week combined feedback and online intervention . The combined intervention group had lower BMI s at post-testing than the other three groups . This study demonstrated the effectiveness and feasibility of an online intervention to prevent weight gain among college students CONTEXT Rapid increases in access to the Internet have made it a viable mode for public health intervention . No controlled studies have evaluated this re source for weight loss . OBJECTIVE To determine whether a structured Internet behavioral weight loss program produces greater initial weight loss and changes in waist circumference than a weight loss education Web site . DESIGN R and omized , controlled trial conducted from April to December 1999 . SETTING AND PARTICIPANTS Ninety-one healthy , overweight adult hospital employees aged 18 to 60 years with a body mass index of 25 to 36 kg/m(2 ) . Analyses were performed for the 65 who had complete follow-up data . INTERVENTIONS Participants were r and omly assigned to a 6-month weight loss program of either Internet education ( education ; n = 32 with complete data ) or Internet behavior therapy ( behavior therapy ; n = 33 with complete data ) . All participants were given 1 face-to-face group weight loss session and access to a Web site with organized links to Internet weight loss re sources . Participants in the behavior therapy group received additional behavioral procedures , including a sequence of 24 weekly behavioral lessons via e-mail , weekly online su bmi ssion of self-monitoring diaries with individualized therapist feedback via e-mail , and an online bulletin board . MAIN OUTCOME MEASURES Body weight and waist circumference , measured at 0 , 3 , and 6 months , compared the 2 intervention groups . RESULTS Repeated- measures analyses showed that the behavior therapy group lost more weight than the education group ( P = .005 ) . The behavior therapy group lost a mean ( SD ) of 4.0 ( 2.8 ) kg by 3 months and 4.1 ( 4.5 ) kg by 6 months . Weight loss in the education group was 1.7 ( 2.7 ) kg at 3 months and 1.6 ( 3.3 ) kg by 6 months . More participants in the behavior therapy than education group achieved the 5 % weight loss goal ( 45 % vs 22 % ; P = .05 ) by 6 months . Changes in waist circumference were also greater in the behavior therapy group than in the education group at both 3 months ( P = .001 ) and 6 months ( P = .005 ) . CONCLUSIONS Participants who were given a structured behavioral treatment program with weekly contact and individualized feedback had better weight loss compared with those given links to educational Web sites . Thus , the Internet and e-mail appear to be viable methods for delivery of structured behavioral weight loss programs Background The Internet has potential as a medium for health behavior change programs , but no controlled studies have yet evaluated the impact of a fully automated physical activity intervention over several months with real-time objective feedback from a monitor . Objective The aim was to evaluate the impact of a physical activity program based on the Internet and mobile phone technology provided to individuals for 9 weeks . Methods A single-center , r and omized , stratified controlled trial was conducted from September to December 2005 in Bedfordshire , United Kingdom , with 77 healthy adults whose mean age was 40.4 years ( SD = 7.6 ) and mean body mass index was 26.3 ( SD = 3.4 ) . Participants were r and omized to a test group that had access to an Internet and mobile phone – based physical activity program  ( n = 47 ) or to a control group ( n = 30 ) that  received no support . The test group received tailored solutions for perceived barriers , a schedule to plan weekly exercise sessions with mobile phone and email reminders , a message board to share their experiences with others , and feedback on their level of physical activity . Both groups were issued a wrist-worn accelerometer to monitor their level of physical activity ;  only the test group received real-time feedback via the Internet . The main outcome measures were accelerometer data and self-report of physical activity . Results At the end of the study period , the test group reported a significantly greater increase over baseline than did the control group for perceived control ( P < .001 ) and intention/expectation to exercise ( P < .001 ) . Intent-to-treat analyses of both the accelerometer data ( P = .02 ) and leisure time self-report data ( P = .03 ) found a higher level of moderate physical activity in the test group . The average increase ( over the control group ) in accelerometer-measured moderate physical activity was 2 h 18 min per week . The test group also lost more percent body fat than the control group ( test group : −2.18 , SD = 0.59 ; control group : −0.17 , SD = 0.81 ; P = .04 ) . Conclusions A fully automated Internet and mobile phone – based motivation and action support system can significantly increase and maintain the level of physical activity in healthy adults This study aims to evaluate the cost-effectiveness of a long-term workplace health promotion programme on physical activity ( PA ) and nutrition . In total , 924 participants enrolled in a 2-year cluster r and omized controlled trial , with departments ( n = 74 ) within companies ( n = 6 ) as the unit of r and omization . The intervention was compared with a st and ard programme consisting of a physical health check with face-to-face advice and personal feedback on a website . The intervention consisted of several additional website functionalities : action-oriented feedback , self-monitoring , possibility to ask questions and monthly e-mail messages . Primary outcomes were meeting the guidelines for PA and fruit and vegetable intake . Secondary outcomes were self-perceived health , obesity , elevated blood pressure , elevated cholesterol level and maximum oxygen uptake . Direct and indirect costs were calculated from a societal perspective , and a process evaluation was performed . Of the 924 participants , 72 % participated in the first and 60 % in the second follow-up . No statistically significant differences were found on primary and secondary outcomes , nor on costs . Average direct costs per participant over the 2-year period were € 376 , and average indirect costs were € 9476 . In conclusion , no additional benefits were found in effects or cost savings . Therefore , the programme in its current form can not be recommended for implementation BACKGROUND Several studies have shown that e-mail counseling improves weight loss achieved in self-directed Internet programs . Computer-tailored feedback offers a population -based alternative to human e-mail counseling . METHODS One hundred ninety-two adults , aged 49.2 + /- 9.8 years , having a body mass index ( calculated as weight in kilograms divided by height in meters squared ) of 32.7 + /- 3.5 , were r and omized to 1 of 3 Internet treatment groups : No counseling , computer-automated feedback , or human e-mail counseling .  All participants received 1 weight loss group session , coupons for meal replacements , and access to an interactive Web site . The human e-mail counseling and computer-automated feedback groups also had access to an electronic diary and message board . The human e-mail counseling group received weekly e-mail feedback from a counselor , and the computer-automated feedback group received automated , tailored messages . RESULTS Retention was 82 % at 3 months and 80 % at 6 months for all 3 groups . At 3 months , completers in both the computer-automated feedback ( -5.3 + /- 4.2 kg ) and human e-mail counseling ( -6.1 + /- 3.9 kg ) groups had significantly greater weight losses compared with the no counseling group ( -2.8 + /- 3.5 kg ) and these groups did not differ from each other . At 6 months , weight losses were significantly greater in the human e-mail counseling group ( -7.3 + /- 6.2 kg ) than in the computer-automated feedback ( -4.9 + /- 5.9 kg ) or no counseling ( -2.6 + /- 5.7 kg ) groups . Intent-to-treat analyses using single or multiple imputation techniques showed the same pattern of significance . CONCLUSIONS Providing automated computer-tailored feedback in an Internet weight loss program was as effective as human e-mail counseling at 3 months . Further research is needed to improve the efficacy of automated computer-tailored feedback as a population -based weight loss approach Background : Internet-based weight-loss programs appear promising in the short-term but , to data , have not been able to produce the level of weight loss seen in traditional in-person treatment ; thus , novel approaches are necessary . Using a combination of interactive technology and in-person support has been beneficial in other areas of medicine . Purpose : The aim of this study is to compare 12-month weight-loss outcomes of an Internet-only behavioral weight-loss treatment with the same program supplemented with monthly in-person meetings . Methods : One hundred and twenty-three participants were r and omized to an Internet-only ( n=62 ) or an Internet + in-person treatment ( I+IPS ; n=61 ) . All participants then participated in a 12-month behavioral weight-loss program conducted over the Internet . The groups met online weekly for the first 6 months and biweekly for the second half of the intervention . The I+IPS group had access to the same Web site as the Internet-only group but , once a month , attended an in-person meeting in place of an online chat . Assessment s included body weight , program adherence , and social support measures . Results : An intent-to-treat analysis ( n=123 ) revealed there were no significant Group x Time differences ( p=.15 ) in weight loss at either 6 ( −6.8±7.8 vs. −5.1±4.8 , p=.15 ) or 12 months ( −5.1±7.1 kg vs. −3.5±5.1 kg , p=.17 , for Internet-only and I+IPS , respectively ) . Differences between groups for those completing all measures ( n=77 ) also revealed no significant differences at 6 months ( −9.2±7.0 kg vs. −6.9±4.2 kg , p=.08 ) or 12 months ( −8.0±7.5 kg vs. −5.6±5.5 kg , p=. 
    Output:
    
agent
***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 Obesity remains a serious issue in many countries . Web-based programs offer good potential for delivery of weight loss programs . Yet , many Internet-delivered weight loss studies include support from medical or nutritional experts , and relatively little is known about purely web-based weight loss programs . Objective To determine whether supportive features and personalization in a 12-week web-based lifestyle intervention with no in-person professional contact affect retention and weight loss . Methods We assessed the effect of different features of a web-based weight loss intervention using a 12-week repeated- measures r and omized parallel design . We developed 7 sites representing 3 functional groups . A national mass media promotion was used to attract overweight/obese Australian adults ( based on body mass index [ BMI ] calculated from self-reported heights and weights ) . Eligible respondents ( n = 8112 ) were r and omly allocated to one of 3 functional groups : information-based ( n = 183 ) , supportive ( n = 3994 ) , or personalized-supportive ( n = 3935 ) . Both supportive sites included tools , such as a weight tracker , meal planner , and social networking platform . The personalized-supportive site included a meal planner that offered recommendations that were personalized using an algorithm based on a user ’s preferences for certain foods . Dietary and activity information were constant across sites , based on an existing and tested 12-week weight loss program ( the Total Wellbeing Diet ) . Before and /or after the intervention , participants completed demographic ( including self-reported weight ) , behavioral , and evaluation question naires online . Usage of the website and features was objective ly recorded . All screening and data collection procedures were performed online with no face-to-face contact . Results Across all 3 groups , attrition was high at around 40 % in the first week and 20 % of the remaining participants each week . Retention was higher for the supportive sites compared to the information-based site only at week 12 ( P = .01 ) . The average number of days that each site was used varied significantly ( P = .02 ) and was higher for the supportive site at 5.96 ( SD 11.36 ) and personalized-supportive site at 5.50 ( SD 10.35 ) , relative to the information-based site at 3.43 ( SD 4.28 ) . In total , 435 participants provided a valid final weight at the 12-week follow-up . Intention-to-treat analyses ( using multiple imputations ) revealed that there were no statistically significant differences in weight loss between sites ( P = .42 ) . On average , participants lost 2.76 % ( SE 0.32 % ) of their initial body weight , with 23.7 % ( SE 3.7 % ) losing 5 % or more of their initial weight . Within supportive conditions , the level of use of the online weight tracker was predictive of weight loss ( model estimate = 0.34 , P < .001 ) . Age ( model estimate = 0.04 , P < .001 ) and initial BMI ( model estimate = -0.03 , P < .002 ) were associated with frequency of use of the weight tracker . Conclusions Relative to a static control , inclusion of social networking features and personalized meal planning recommendations in a web-based weight loss program did not demonstrate additive effects for user weight loss or retention . These features did , however , increase the average number of days that a user engaged with the system . For users of the supportive websites , greater use of the weight tracker tool was associated with greater weight loss The transition to college has been identified as a critical period for increases in overweight status . Overweight college students are at-risk of becoming obese adults , and , thus prevention efforts targeting college age individuals are key to reducing adult obesity rates . The current study evaluated an Internet intervention with first year college students ( N=170 ) r and omly assigned to one of four treatment conditions : 1 ) no treatment , 2 ) 6-week online intervention 3 ) 6-week weight and caloric feedback only ( via email ) , and 4 ) 6-week combined feedback and online intervention . The combined intervention group had lower BMI s at post-testing than the other three groups . This study demonstrated the effectiveness and feasibility of an online intervention to prevent weight gain among college students CONTEXT Rapid increases in access to the Internet have made it a viable mode for public health intervention . No controlled studies have evaluated this re source for weight loss . OBJECTIVE To determine whether a structured Internet behavioral weight loss program produces greater initial weight loss and changes in waist circumference than a weight loss education Web site . DESIGN R and omized , controlled trial conducted from April to December 1999 . SETTING AND PARTICIPANTS Ninety-one healthy , overweight adult hospital employees aged 18 to 60 years with a body mass index of 25 to 36 kg/m(2 ) . Analyses were performed for the 65 who had complete follow-up data . INTERVENTIONS Participants were r and omly assigned to a 6-month weight loss program of either Internet education ( education ; n = 32 with complete data ) or Internet behavior therapy ( behavior therapy ; n = 33 with complete data ) . All participants were given 1 face-to-face group weight loss session and access to a Web site with organized links to Internet weight loss re sources . Participants in the behavior therapy group received additional behavioral procedures , including a sequence of 24 weekly behavioral lessons via e-mail , weekly online su bmi ssion of self-monitoring diaries with individualized therapist feedback via e-mail , and an online bulletin board . MAIN OUTCOME MEASURES Body weight and waist circumference , measured at 0 , 3 , and 6 months , compared the 2 intervention groups . RESULTS Repeated- measures analyses showed that the behavior therapy group lost more weight than the education group ( P = .005 ) . The behavior therapy group lost a mean ( SD ) of 4.0 ( 2.8 ) kg by 3 months and 4.1 ( 4.5 ) kg by 6 months . Weight loss in the education group was 1.7 ( 2.7 ) kg at 3 months and 1.6 ( 3.3 ) kg by 6 months . More participants in the behavior therapy than education group achieved the 5 % weight loss goal ( 45 % vs 22 % ; P = .05 ) by 6 months . Changes in waist circumference were also greater in the behavior therapy group than in the education group at both 3 months ( P = .001 ) and 6 months ( P = .005 ) . CONCLUSIONS Participants who were given a structured behavioral treatment program with weekly contact and individualized feedback had better weight loss compared with those given links to educational Web sites . Thus , the Internet and e-mail appear to be viable methods for delivery of structured behavioral weight loss programs Background The Internet has potential as a medium for health behavior change programs , but no controlled studies have yet evaluated the impact of a fully automated physical activity intervention over several months with real-time objective feedback from a monitor . Objective The aim was to evaluate the impact of a physical activity program based on the Internet and mobile phone technology provided to individuals for 9 weeks . Methods A single-center , r and omized , stratified controlled trial was conducted from September to December 2005 in Bedfordshire , United Kingdom , with 77 healthy adults whose mean age was 40.4 years ( SD = 7.6 ) and mean body mass index was 26.3 ( SD = 3.4 ) . Participants were r and omized to a test group that had access to an Internet and mobile phone – based physical activity program  ( n = 47 ) or to a control group ( n = 30 ) that  received no support . The test group received tailored solutions for perceived barriers , a schedule to plan weekly exercise sessions with mobile phone and email reminders , a message board to share their experiences with others , and feedback on their level of physical activity . Both groups were issued a wrist-worn accelerometer to monitor their level of physical activity ;  only the test group received real-time feedback via the Internet . The main outcome measures were accelerometer data and self-report of physical activity . Results At the end of the study period , the test group reported a significantly greater increase over baseline than did the control group for perceived control ( P < .001 ) and intention/expectation to exercise ( P < .001 ) . Intent-to-treat analyses of both the accelerometer data ( P = .02 ) and leisure time self-report data ( P = .03 ) found a higher level of moderate physical activity in the test group . The average increase ( over the control group ) in accelerometer-measured moderate physical activity was 2 h 18 min per week . The test group also lost more percent body fat than the control group ( test group : −2.18 , SD = 0.59 ; control group : −0.17 , SD = 0.81 ; P = .04 ) . Conclusions A fully automated Internet and mobile phone – based motivation and action support system can significantly increase and maintain the level of physical activity in healthy adults This study aims to evaluate the cost-effectiveness of a long-term workplace health promotion programme on physical activity ( PA ) and nutrition . In total , 924 participants enrolled in a 2-year cluster r and omized controlled trial , with departments ( n = 74 ) within companies ( n = 6 ) as the unit of r and omization . The intervention was compared with a st and ard programme consisting of a physical health check with face-to-face advice and personal feedback on a website . The intervention consisted of several additional website functionalities : action-oriented feedback , self-monitoring , possibility to ask questions and monthly e-mail messages . Primary outcomes were meeting the guidelines for PA and fruit and vegetable intake . Secondary outcomes were self-perceived health , obesity , elevated blood pressure , elevated cholesterol level and maximum oxygen uptake . Direct and indirect costs were calculated from a societal perspective , and a process evaluation was performed . Of the 924 participants , 72 % participated in the first and 60 % in the second follow-up . No statistically significant differences were found on primary and secondary outcomes , nor on costs . Average direct costs per participant over the 2-year period were € 376 , and average indirect costs were € 9476 . In conclusion , no additional benefits were found in effects or cost savings . Therefore , the programme in its current form can not be recommended for implementation BACKGROUND Several studies have shown that e-mail counseling improves weight loss achieved in self-directed Internet programs . Computer-tailored feedback offers a population -based alternative to human e-mail counseling . METHODS One hundred ninety-two adults , aged 49.2 + /- 9.8 years , having a body mass index ( calculated as weight in kilograms divided by height in meters squared ) of 32.7 + /- 3.5 , were r and omized to 1 of 3 Internet treatment groups : No counseling , computer-automated feedback , or human e-mail counseling .  All participants received 1 weight loss group session , coupons for meal replacements , and access to an interactive Web site . The human e-mail counseling and computer-automated feedback groups also had access to an electronic diary and message board . The human e-mail counseling group received weekly e-mail feedback from a counselor , and the computer-automated feedback group received automated , tailored messages . RESULTS Retention was 82 % at 3 months and 80 % at 6 months for all 3 groups . At 3 months , completers in both the computer-automated feedback ( -5.3 + /- 4.2 kg ) and human e-mail counseling ( -6.1 + /- 3.9 kg ) groups had significantly greater weight losses compared with the no counseling group ( -2.8 + /- 3.5 kg ) and these groups did not differ from each other . At 6 months , weight losses were significantly greater in the human e-mail counseling group ( -7.3 + /- 6.2 kg ) than in the computer-automated feedback ( -4.9 + /- 5.9 kg ) or no counseling ( -2.6 + /- 5.7 kg ) groups . Intent-to-treat analyses using single or multiple imputation techniques showed the same pattern of significance . CONCLUSIONS Providing automated computer-tailored feedback in an Internet weight loss program was as effective as human e-mail counseling at 3 months . Further research is needed to improve the efficacy of automated computer-tailored feedback as a population -based weight loss approach Background : Internet-based weight-loss programs appear promising in the short-term but , to data , have not been able to produce the level of weight loss seen in traditional in-person treatment ; thus , novel approaches are necessary . Using a combination of interactive technology and in-person support has been beneficial in other areas of medicine . Purpose : The aim of this study is to compare 12-month weight-loss outcomes of an Internet-only behavioral weight-loss treatment with the same program supplemented with monthly in-person meetings . Methods : One hundred and twenty-three participants were r and omized to an Internet-only ( n=62 ) or an Internet + in-person treatment ( I+IPS ; n=61 ) . All participants then participated in a 12-month behavioral weight-loss program conducted over the Internet . The groups met online weekly for the first 6 months and biweekly for the second half of the intervention . The I+IPS group had access to the same Web site as the Internet-only group but , once a month , attended an in-person meeting in place of an online chat . Assessment s included body weight , program adherence , and social support measures . Results : An intent-to-treat analysis ( n=123 ) revealed there were no significant Group x Time differences ( p=.15 ) in weight loss at either 6 ( −6.8±7.8 vs. −5.1±4.8 , p=.15 ) or 12 months ( −5.1±7.1 kg vs. −3.5±5.1 kg , p=.17 , for Internet-only and I+IPS , respectively ) . Differences between groups for those completing all measures ( n=77 ) also revealed no significant differences at 6 months ( −9.2±7.0 kg vs. −6.9±4.2 kg , p=.08 ) or 12 months ( −8.0±7.5 kg vs. −5.6±5.5 kg , p=. 
    Output:
    