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: The main objective of this pilot study was to test the effectiveness of an  online , interactive physical activity intervention that also incorporated gaming components . The intervention design included an activity planner , progress monitoring , and gamification components and used SMS text as a secondary delivery channel and feedback to improve engagement in the intervention content . Healthy adults ( n = 21 ) recruited through ads in local newspapers ( age 35–73 ) were r and omized to the intervention or the control condition . Both groups reported physical activity using daily report forms in four registration weeks during the three-month study : only the experiment condition received access to the intervention . Analyses showed that the intervention group had significantly more minutes of physical activity in weeks five and nine . We also found a difference in the intensity of exercise in week five . Although the intervention group reported more minutes of physical activity at higher intensity levels , we were not able to find a significant effect at the end of the study period . In conclusion , this study adds to the research on the effectiveness of using the Internet and SMS text messages for delivering physical activity interventions and supports gamification as a viable intervention tool Background Web-based computer-tailored interventions have shown to be effective in improving health behavior ; however , high dropout attrition is a major issue in these interventions . Objective The aim of this study is to assess whether people with a lower educational level drop out from studies more frequently compared to people with a higher educational level and to what extent this depends on evaluation of these interventions . Methods Data from 7 r and omized controlled trials of Web-based computer-tailored interventions were used to investigate dropout rates among participants with different educational levels . To be able to compare higher and lower educated participants , intervention evaluation was assessed by pooling data from these studies . Logistic regression analysis was used to assess whether intervention evaluation predicted dropout at follow-up measurements . Results In 3 studies , we found a higher study dropout attrition rate among participants with a lower educational level , whereas in 2 studies we found that middle educated participants had a higher dropout attrition rate compared to highly educated participants . In 4 studies , no such significant difference was found . Three of 7 studies showed that participants with a lower or middle educational level evaluated the interventions significantly better than highly educated participants ( “ Alcohol-Everything within the Limit ” : F 2,376=5.97 , P=.003 ; “ My Healthy Behavior ” : F 2,359=5.52 , P=.004 ; “ Master Your Breath ” : F 2,317=3.17 , P=.04 ) . One study found lower intervention evaluation by lower educated participants compared to participants with a middle educational level ( “ Weight in Balance ” : F 2,37=3.17 , P=.05 ) . Low evaluation of the interventions was not a significant predictor of dropout at a later follow-up measurement in any of the studies . Conclusions Dropout attrition rates were higher among participants with a lower or middle educational level compared with highly educated participants . Although lower educated participants evaluated the interventions better in approximately half of the studies , evaluation did not predict dropout attrition . Further research is needed to find other explanations for high dropout rates among lower educated participants Data from two r and omized clinical trials ( RCT ) were used to examine the extent to which a health promotion intervention affected changes in growth trajectories of psychosocial constructs and if so , whether these constructs in turn explained changes in  physical activity ( PA ) . PA and psychosocial measures on 842 overweight adults in the United States were collected in two RCTs evaluating Internet-based behavior change interventions with assessment s at baseline , 6 and 12 months . A physical activity latent variable at 12 months was created using indicators of self-reported walking and leisure time activities . Intervention-mediated effects on  PA  at 12 months were found via latent growth curves representing self-efficacy and behavioral strategies , where increasing growth curves across time were associated with higher  PA values at 12 months . These findings provide some evidence that web-based self-help intervention programs worked through targeted behavior change constructs to influence physical activity levels in overweight adults Purpose : The purpose of this study was to test the effect of keeping daily activity records on physical activity levels and self-efficacy for physical activity in adults with type 2 diabetes , and to examine the feasibility and acceptability of this intervention from the perspective of the participants . Methods : This intervention study included 58 individuals with type 2 diabetes aged 40 to 65 years . Participants were r and omly assigned : individuals in the intervention group kept daily activity records for 6 weeks , mailed to the research er every 2 weeks . Data collection was completed at the beginning of the study and 6 weeks later , using the habitual physical activity index and the self-efficacy for exercise scale . Participants in the intervention group also completed the perceived feasibility checklist . Results : The intervention result ed in enhanced self-efficacy . Physical activity improved in both the intervention and control groups . Activity recording was judged to be acceptable and feasible . Conclusions : Daily activity recording can be used as part of a program to increase physical activity self-efficacy levels . Focused interactions between health care providers and patients may be enough to motivate people to higher levels of physical activity . The relationship between self-efficacy and behavior is complex and should be the subject of further research Background Computer-tailored physical activity ( PA ) interventions delivered through the Internet represent a promising and appealing method to promote PA at a population level . However , personalized advice is mostly provided based on subjectively measured PA , which is not very accurate and might result in the delivery of advice that is not credible or effective . Therefore , an innovative computer-tailored PA advice was developed , based on objective ly pedometer-measured PA . Objective The study aim was to evaluate the effectiveness of a computer-tailored , pedometer-based PA intervention in working adults . Methods Participants ( ≥18 years ) were recruited between May and December 2012 from eight Flemish workplaces . These workplaces were allocated r and omly to an intervention or control group . Intervention group participants ( n=137 ) received ( 1 ) a booklet with information on how to increase their steps , ( 2 ) a non-blinded pedometer , and ( 3 ) an Internet link to request computer-tailored step advice . Control group participants ( n=137 ) did not receive any of the intervention components . Self-reported and pedometer-based PA  were assessed at baseline ( T0 ) , and 1 month ( T1 ) and 3 months ( T2 ) months post baseline . Repeated measures analyses of covariance were used to examine intervention effects for both the total sample and the at-risk sample ( ie , adults not reaching 10,000 steps a day at baseline ) . Results The recruitment process result ed in 274 respondents ( response rate of 15.1 % ) who agreed to participate , of whom 190 ( 69.3 % ) belonged to the at-risk sample . Between T0 and T1 ( 1-month post baseline ) , significant intervention effects were found for participants ’ daily step counts in both the total sample ( P=.004 ) and the at-risk sample ( P=.001 ) . In the at-risk sample , the intervention effects showed a daily step count increase of 1056 steps in the intervention group , compared to a decrease of 258 steps in the control group . Comparison of participants ’ self-reported PA revealed a significant intervention effect for time spent walking in the at-risk sample ( P=.02 ) . Intervention effects were still significant 3 months post baseline for participants ’ daily step counts in both the total sample ( P=.03 ) and the at-risk sample ( P=.02 ) ; however , self-reported PA differences were no longer significant . Conclusions A computer-tailored , pedometer-based PA intervention was effective in increasing both pedometer-based and self-reported PA levels , mainly in the at-risk participants . However , more effort should be devoted to recruit and retain participants in order to improve the public health impact of the intervention . Trial Registration Clinical Trials.gov : NCT02080585 ; https:// clinical trials.gov/ct2/show/NCT02080585 ( Archived by WebCite at http://www.webcitation.org/6VvQnRQSy ) Background Our main objective in the current study was to evaluate the long-term effectiveness ( 12 months from baseline ) of I Move ( a web-based computer tailored physical activity intervention , based on self-determination theory and motivational interviewing ) . To this end , we compared I Move to a web-based computer tailored physical activity intervention based on traditional health behavior theories ( Active Plus ) , and to a no-intervention control group . As a secondary objective , the present study aim ed to identify participant characteristics that moderate the long term effects of I Move and Active Plus . Methods A r and omized controlled trial was conducted , comparing three research conditions : 1 ) the I Move condition  ,  participants in this condition received I Move ;  2 ) the Active Plus condition  , participants in this condition received Active Plus ; 3 ) the control condition ; participants in  this condition received no intervention and were placed on a waiting list . Main outcome measures were weekly minutes of moderate to vigorous physical activity and weekly days with minimal 30 min of physical activity . All measurements were taken by web-based question naires via the study website . Intervention effects were analyzed using multilevel linear regression analyses . Results At 12 months from baseline , I Move was found to be effective in increasing weekly minutes of moderate to vigorous physical activity ( ES = .13 ) , while Active Plus was not . In contrast , Active Plus was found to be effective in increasing weekly days with ≥ 30 min PA at 12 months ( ES = .11 ) , while I Move was not . No moderators of the effects of I Move were found . Conclusions The results suggest that web-based computer tailored physical activity interventions might best include elements based on both self-determination theory/motivational interviewing and traditional health behavioral theories . To be more precise , it is arguable that the focus of the theoretical foundations , used in new web-based PA interventions should depend on the intended program outcome . In order to draw firm conclusions , however , more research on the effects of self-determination theory and motivational interviewing in web-based physical activity promotion is needed . Trial registration Dutch Trial Register The aim of this study was to evaluate the effectiveness of a computer-tailored physical activity intervention delivered through the Internet in a real-life setting . Healthy adults ( n=526 ) , recruited in six worksites , between 25 and 55 years of age were r and omized to one of three conditions receiving , respectively , ( i ) online-tailored physical activity advice + stage-based reinforcement e-mails , ( ii ) online-tailored physical activity advice only , ( iii ) online non-tailored st and ard physical activity advice . At 6-month follow-up , no differences in physical activity between study conditions were found ; total physical activity , physical activity at moderate intensity and physical activity in leisure time significantly increased in all study conditions between baseline and follow-up . Further evaluation of the intervention material s showed that the tailored advice was more read , printed and discussed with others than the st and ard advice . Most of the respondents in the e-mail group indicated to be satisfied about the number , frequency and usefulness of the stage-based e-mails . In conclusion , although tailored advice was appreciated more than st and ard advice , no evidence was found that an online-tailored physical activity intervention program outperformed online st and ard information Background Inactive people are often not aware of the fact that they are insufficiently active . Providing insight into their actual physical activity ( PA ) levels may raise awareness and could , in combination with tailored PA advice , stimulate a physically active lifestyle . Objective This study evaluated the feasibility and effectiveness of a 3-month intervention in which Dutch office workers were provided with a personal activity monitor ( PAM ) coupled to simple and concise Web-based tailored PA advice ( PAM COACH ) . Method Participants were r and omly assigned to the 3-month PAM intervention ( n = 51 ) or received a single written information brochure with brief general PA recommendations ( n = 51 ) . Study outcome measures were changes in PA ( recall of minutes per week spent on PA , as measured by the Activity Question naire for Adolescents and Adults ) , determinants of PA , aerobic fitness , and body composition . Follow-up measurements were performed immediately after the 3-month intervention and at 8-months , 5 months after the end of the 3-month intervention period . Results A total of 102 workers , 23 to 39 years old , completed the baseline measurement at the worksite . 48 completed the 3-month follow up and 38 the 8-month follow-up in the intervention group , 50 completed the 3-month follow up and 42 the 8-month follow up in the control group . 35 out of 48 ( 73 % ) participants in the PAM intervention group reported wearing the PAM regularly , and the PAM COACH was used almost once a week ; 24 out of 46 ( 52 % ) PAM users set a personal goal , and 33 ( 72 % ) entered their favorite activities on the website . Main reasons for not using these items were lack of interest or not being able to find the item on the website . The majority of PAM users ( 34 out of 46 , 74 % ) read the advice , of whom 14 ( 39 % ) found it unappealing . After the 3-month intervention , no significant intervention effect was observed ( adjusted difference in min/week ) for sedentary behavior ( β = 10 , 95 % CI = −435 to 455 ) , light-intensity PA ( β = −129 , 95 % CI = −337 to 79 ) , moderate-intensity PA ( β = −13 , 95 % CI = −89 to 63 ) , vigorous-intensity PA ( β= −6 , 95 % CI = −75 to 62 ) , and moderate- to vigorous-intensity PA ( β = −23 , 95 % CI = −121 to 76 ) . No significant intervention effect was observed in the PA outcomes at the 8-month follow-up . For the determinants of PA , aerobic fitness , and body composition , no statistically significant intervention effect was observed in the total study population immediately after the 3 
    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: The main objective of this pilot study was to test the effectiveness of an  online , interactive physical activity intervention that also incorporated gaming components . The intervention design included an activity planner , progress monitoring , and gamification components and used SMS text as a secondary delivery channel and feedback to improve engagement in the intervention content . Healthy adults ( n = 21 ) recruited through ads in local newspapers ( age 35–73 ) were r and omized to the intervention or the control condition . Both groups reported physical activity using daily report forms in four registration weeks during the three-month study : only the experiment condition received access to the intervention . Analyses showed that the intervention group had significantly more minutes of physical activity in weeks five and nine . We also found a difference in the intensity of exercise in week five . Although the intervention group reported more minutes of physical activity at higher intensity levels , we were not able to find a significant effect at the end of the study period . In conclusion , this study adds to the research on the effectiveness of using the Internet and SMS text messages for delivering physical activity interventions and supports gamification as a viable intervention tool Background Web-based computer-tailored interventions have shown to be effective in improving health behavior ; however , high dropout attrition is a major issue in these interventions . Objective The aim of this study is to assess whether people with a lower educational level drop out from studies more frequently compared to people with a higher educational level and to what extent this depends on evaluation of these interventions . Methods Data from 7 r and omized controlled trials of Web-based computer-tailored interventions were used to investigate dropout rates among participants with different educational levels . To be able to compare higher and lower educated participants , intervention evaluation was assessed by pooling data from these studies . Logistic regression analysis was used to assess whether intervention evaluation predicted dropout at follow-up measurements . Results In 3 studies , we found a higher study dropout attrition rate among participants with a lower educational level , whereas in 2 studies we found that middle educated participants had a higher dropout attrition rate compared to highly educated participants . In 4 studies , no such significant difference was found . Three of 7 studies showed that participants with a lower or middle educational level evaluated the interventions significantly better than highly educated participants ( “ Alcohol-Everything within the Limit ” : F 2,376=5.97 , P=.003 ; “ My Healthy Behavior ” : F 2,359=5.52 , P=.004 ; “ Master Your Breath ” : F 2,317=3.17 , P=.04 ) . One study found lower intervention evaluation by lower educated participants compared to participants with a middle educational level ( “ Weight in Balance ” : F 2,37=3.17 , P=.05 ) . Low evaluation of the interventions was not a significant predictor of dropout at a later follow-up measurement in any of the studies . Conclusions Dropout attrition rates were higher among participants with a lower or middle educational level compared with highly educated participants . Although lower educated participants evaluated the interventions better in approximately half of the studies , evaluation did not predict dropout attrition . Further research is needed to find other explanations for high dropout rates among lower educated participants Data from two r and omized clinical trials ( RCT ) were used to examine the extent to which a health promotion intervention affected changes in growth trajectories of psychosocial constructs and if so , whether these constructs in turn explained changes in  physical activity ( PA ) . PA and psychosocial measures on 842 overweight adults in the United States were collected in two RCTs evaluating Internet-based behavior change interventions with assessment s at baseline , 6 and 12 months . A physical activity latent variable at 12 months was created using indicators of self-reported walking and leisure time activities . Intervention-mediated effects on  PA  at 12 months were found via latent growth curves representing self-efficacy and behavioral strategies , where increasing growth curves across time were associated with higher  PA values at 12 months . These findings provide some evidence that web-based self-help intervention programs worked through targeted behavior change constructs to influence physical activity levels in overweight adults Purpose : The purpose of this study was to test the effect of keeping daily activity records on physical activity levels and self-efficacy for physical activity in adults with type 2 diabetes , and to examine the feasibility and acceptability of this intervention from the perspective of the participants . Methods : This intervention study included 58 individuals with type 2 diabetes aged 40 to 65 years . Participants were r and omly assigned : individuals in the intervention group kept daily activity records for 6 weeks , mailed to the research er every 2 weeks . Data collection was completed at the beginning of the study and 6 weeks later , using the habitual physical activity index and the self-efficacy for exercise scale . Participants in the intervention group also completed the perceived feasibility checklist . Results : The intervention result ed in enhanced self-efficacy . Physical activity improved in both the intervention and control groups . Activity recording was judged to be acceptable and feasible . Conclusions : Daily activity recording can be used as part of a program to increase physical activity self-efficacy levels . Focused interactions between health care providers and patients may be enough to motivate people to higher levels of physical activity . The relationship between self-efficacy and behavior is complex and should be the subject of further research Background Computer-tailored physical activity ( PA ) interventions delivered through the Internet represent a promising and appealing method to promote PA at a population level . However , personalized advice is mostly provided based on subjectively measured PA , which is not very accurate and might result in the delivery of advice that is not credible or effective . Therefore , an innovative computer-tailored PA advice was developed , based on objective ly pedometer-measured PA . Objective The study aim was to evaluate the effectiveness of a computer-tailored , pedometer-based PA intervention in working adults . Methods Participants ( ≥18 years ) were recruited between May and December 2012 from eight Flemish workplaces . These workplaces were allocated r and omly to an intervention or control group . Intervention group participants ( n=137 ) received ( 1 ) a booklet with information on how to increase their steps , ( 2 ) a non-blinded pedometer , and ( 3 ) an Internet link to request computer-tailored step advice . Control group participants ( n=137 ) did not receive any of the intervention components . Self-reported and pedometer-based PA  were assessed at baseline ( T0 ) , and 1 month ( T1 ) and 3 months ( T2 ) months post baseline . Repeated measures analyses of covariance were used to examine intervention effects for both the total sample and the at-risk sample ( ie , adults not reaching 10,000 steps a day at baseline ) . Results The recruitment process result ed in 274 respondents ( response rate of 15.1 % ) who agreed to participate , of whom 190 ( 69.3 % ) belonged to the at-risk sample . Between T0 and T1 ( 1-month post baseline ) , significant intervention effects were found for participants ’ daily step counts in both the total sample ( P=.004 ) and the at-risk sample ( P=.001 ) . In the at-risk sample , the intervention effects showed a daily step count increase of 1056 steps in the intervention group , compared to a decrease of 258 steps in the control group . Comparison of participants ’ self-reported PA revealed a significant intervention effect for time spent walking in the at-risk sample ( P=.02 ) . Intervention effects were still significant 3 months post baseline for participants ’ daily step counts in both the total sample ( P=.03 ) and the at-risk sample ( P=.02 ) ; however , self-reported PA differences were no longer significant . Conclusions A computer-tailored , pedometer-based PA intervention was effective in increasing both pedometer-based and self-reported PA levels , mainly in the at-risk participants . However , more effort should be devoted to recruit and retain participants in order to improve the public health impact of the intervention . Trial Registration Clinical Trials.gov : NCT02080585 ; https:// clinical trials.gov/ct2/show/NCT02080585 ( Archived by WebCite at http://www.webcitation.org/6VvQnRQSy ) Background Our main objective in the current study was to evaluate the long-term effectiveness ( 12 months from baseline ) of I Move ( a web-based computer tailored physical activity intervention , based on self-determination theory and motivational interviewing ) . To this end , we compared I Move to a web-based computer tailored physical activity intervention based on traditional health behavior theories ( Active Plus ) , and to a no-intervention control group . As a secondary objective , the present study aim ed to identify participant characteristics that moderate the long term effects of I Move and Active Plus . Methods A r and omized controlled trial was conducted , comparing three research conditions : 1 ) the I Move condition  ,  participants in this condition received I Move ;  2 ) the Active Plus condition  , participants in this condition received Active Plus ; 3 ) the control condition ; participants in  this condition received no intervention and were placed on a waiting list . Main outcome measures were weekly minutes of moderate to vigorous physical activity and weekly days with minimal 30 min of physical activity . All measurements were taken by web-based question naires via the study website . Intervention effects were analyzed using multilevel linear regression analyses . Results At 12 months from baseline , I Move was found to be effective in increasing weekly minutes of moderate to vigorous physical activity ( ES = .13 ) , while Active Plus was not . In contrast , Active Plus was found to be effective in increasing weekly days with ≥ 30 min PA at 12 months ( ES = .11 ) , while I Move was not . No moderators of the effects of I Move were found . Conclusions The results suggest that web-based computer tailored physical activity interventions might best include elements based on both self-determination theory/motivational interviewing and traditional health behavioral theories . To be more precise , it is arguable that the focus of the theoretical foundations , used in new web-based PA interventions should depend on the intended program outcome . In order to draw firm conclusions , however , more research on the effects of self-determination theory and motivational interviewing in web-based physical activity promotion is needed . Trial registration Dutch Trial Register The aim of this study was to evaluate the effectiveness of a computer-tailored physical activity intervention delivered through the Internet in a real-life setting . Healthy adults ( n=526 ) , recruited in six worksites , between 25 and 55 years of age were r and omized to one of three conditions receiving , respectively , ( i ) online-tailored physical activity advice + stage-based reinforcement e-mails , ( ii ) online-tailored physical activity advice only , ( iii ) online non-tailored st and ard physical activity advice . At 6-month follow-up , no differences in physical activity between study conditions were found ; total physical activity , physical activity at moderate intensity and physical activity in leisure time significantly increased in all study conditions between baseline and follow-up . Further evaluation of the intervention material s showed that the tailored advice was more read , printed and discussed with others than the st and ard advice . Most of the respondents in the e-mail group indicated to be satisfied about the number , frequency and usefulness of the stage-based e-mails . In conclusion , although tailored advice was appreciated more than st and ard advice , no evidence was found that an online-tailored physical activity intervention program outperformed online st and ard information Background Inactive people are often not aware of the fact that they are insufficiently active . Providing insight into their actual physical activity ( PA ) levels may raise awareness and could , in combination with tailored PA advice , stimulate a physically active lifestyle . Objective This study evaluated the feasibility and effectiveness of a 3-month intervention in which Dutch office workers were provided with a personal activity monitor ( PAM ) coupled to simple and concise Web-based tailored PA advice ( PAM COACH ) . Method Participants were r and omly assigned to the 3-month PAM intervention ( n = 51 ) or received a single written information brochure with brief general PA recommendations ( n = 51 ) . Study outcome measures were changes in PA ( recall of minutes per week spent on PA , as measured by the Activity Question naire for Adolescents and Adults ) , determinants of PA , aerobic fitness , and body composition . Follow-up measurements were performed immediately after the 3-month intervention and at 8-months , 5 months after the end of the 3-month intervention period . Results A total of 102 workers , 23 to 39 years old , completed the baseline measurement at the worksite . 48 completed the 3-month follow up and 38 the 8-month follow-up in the intervention group , 50 completed the 3-month follow up and 42 the 8-month follow up in the control group . 35 out of 48 ( 73 % ) participants in the PAM intervention group reported wearing the PAM regularly , and the PAM COACH was used almost once a week ; 24 out of 46 ( 52 % ) PAM users set a personal goal , and 33 ( 72 % ) entered their favorite activities on the website . Main reasons for not using these items were lack of interest or not being able to find the item on the website . The majority of PAM users ( 34 out of 46 , 74 % ) read the advice , of whom 14 ( 39 % ) found it unappealing . After the 3-month intervention , no significant intervention effect was observed ( adjusted difference in min/week ) for sedentary behavior ( β = 10 , 95 % CI = −435 to 455 ) , light-intensity PA ( β = −129 , 95 % CI = −337 to 79 ) , moderate-intensity PA ( β = −13 , 95 % CI = −89 to 63 ) , vigorous-intensity PA ( β= −6 , 95 % CI = −75 to 62 ) , and moderate- to vigorous-intensity PA ( β = −23 , 95 % CI = −121 to 76 ) . No significant intervention effect was observed in the PA outcomes at the 8-month follow-up . For the determinants of PA , aerobic fitness , and body composition , no statistically significant intervention effect was observed in the total study population immediately after the 3 
    Output:
    