Preventing weight gain in first year college students: an online intervention to prevent the "freshman fifteen". Innovative Self-Regulation Strategies to Reduce Weight Gain in Young Adults: The Study of Novel Approaches to Weight Gain Prevention (SNAP) Randomized Clinical Trial. A theory-based online health behaviour intervention for new university students (U@Uni:LifeGuide): results from a repeat randomized controlled trial A theory-based online health behaviour intervention for new university students (U@Uni): results from a randomised controlled trial The Natural History of the Development of Obesity in a Cohort of Young U.S. Adults between 1981 and 1998 A Mobile Health Lifestyle Program for Prevention of Weight Gain in Young Adults (TXT2BFiT): Nine-Month Outcomes of a Randomized Controlled Trial Use of Theory in Behavior Change Interventions Feasibility and preliminary efficacy of the ‘HEYMAN’ healthy lifestyle program for young men: a pilot randomised controlled trial A causal modelling approach to the development of theory-based behaviour change programmes for trial evaluation. The connecting health and technology study: a 6-month randomized controlled trial to improve nutrition behaviours using a mobile food record and text messaging support in young adults Weight Gain Prevention for College Freshmen: Comparing Two Social Cognitive Theory-Based Interventions with and without Explicit Self-Regulation Training Effective Strategies to Recruit Young Adults Into the TXT2BFiT mHealth Randomized Controlled Trial for Weight Gain Prevention Elearning approaches to prevent weight gain in young adults: A randomized controlled study. Weight-Gain Reduction Among 2-Year College Students: The CHOICES RCT. Impact of an Online Healthful Eating and Physical Activity Program for College Students My Student Body: Effects of an Internet-Based Prevention Program to Decrease Obesity Among College Students A mobile health intervention for weight management among young adults: a pilot randomised controlled trial. The effects of Young Adults Eating and Active for Health (YEAH): a theory-based Web-delivered intervention. Frequent Self-Weighing with Electronic Graphic Feedback to Prevent Age-Related Weight Gain in Young Adults. Effect and Process Evaluation of a Smartphone App to Promote an Active Lifestyle in Lower Educated Working Young Adults: Cluster Randomized Controlled Trial Examining the theory‐effectiveness hypothesis: A systematic review of systematic reviews Healthy Lifestyle Change and Subclinical Atherosclerosis in Young Adults: Coronary Artery Risk Development in Young Adults (CARDIA) Study
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 IMPORTANCE Weight gain occurs commonly in young adults and has adverse effects on health . OBJECTIVE To compare 2 self-regulation interventions vs control in reducing weight gain in young adults over a mean follow-up of 3 years . DESIGN , SETTING , AND PARTICIPANTS R and omized clinical trial in 2 academic setting s of 599 participants aged 18 to 35 years with body mass index ( BMI , calculated as weight in kilograms divided by height in meters squared ) of 21.0 to 30.0 , recruited via mailings and emails from August 2010 to February 2012 . Data were analyzed from January 2015 to January 2016 . INTERVENTIONS Participants were r and omized to control , self-regulation plus small changes , or self-regulation plus large changes . Both interventions focused on frequent self-weighing to cue behavior changes . " Small changes " taught participants to reduce intake and increase activity , both by approximately 100 calories per day . " Large changes " focused on losing 2.3 to 4.5 kg initially to buffer against expected weight gain . MAIN OUTCOMES AND MEASURES Changes in weight from baseline over mean follow-up of 3 years . Secondary outcomes included proportion gaining at least 0.45 kg from baseline , proportion developing obesity ( BMI , ≥30.0 ) , and weight change baseline to 2 years . RESULTS Among the 599 participants ( 22 % men ; 27 % minority ; mean [ SD ] age , 27.7 [ 4.4 ] years ; mean [ SD ] BMI , 25.4 [ 2.6 ] ) , mean ( SE ) weight changes over a mean follow-up of 3 years were 0.26 ( 0.22 ) , -0.56 ( 0.22 ) , and -2.37 ( 0.22 ) kg in the control , small-changes , and large-changes groups , respectively ( P < .001 ) . Differences among all 3 groups were significant ( large changes vs control , P < .001 ; small changes vs control , P = .02 ; large changes vs small changes , P < .001 ) . On secondary outcomes , both interventions significantly reduced incidence of obesity relative to control ( mean [ SE ] , 8.6 % [ 2.0 % ] , 7.9 % [ 2.0 % ] , and 16.9 % [ 2.7 % ] in the large-changes , small-changes , and control groups , respectively ; P = .02 for large changes vs control and P = .002 for small changes vs control ) ; a smaller percentage of participants in the large-changes group gained 0.45 kg or more ( mean [ SE ] , 23.6 % [ 2.8 % ] , 32.5 % [ 3.8 % ] , and 40.8 % [ 4.4 % ] , respectively ; P < .001 vs control and P = .02 vs small changes ) and weight change from baseline to 2 years was greater in control than in small or large changes ( mean [ SE ] , 0.54 [ 0.33 ] , -0.77 [ 0.33 ] , and -1.50 [ 0.34 ] kg , respectively ; P = .02 vs small changes and P < .001 vs large changes ) . CONCLUSIONS AND RELEVANCE Self-regulation with large or small changes both reduced weight gain in young adults over 3 years relative to control , but the large-changes intervention was more effective . TRIAL REGISTRATION clinical trials.gov Identifier : NCT01183689 Background This paper reports the results of a repeat trial assessing the effectiveness of an online theory-based intervention to promote healthy lifestyle behaviours in new university students . The original trial found that the intervention reduced the number of smokers at 6-month follow-up compared with the control condition , but had non-significant effects on the other targeted health behaviours . However , the original trial suffered from low levels of engagement , which the repeat trial sought to rectify . Methods Three weeks before staring university , all incoming undergraduate students at a large university in the UK were sent an email inviting them to participate in the study . After completing a baseline question naire , participants were r and omly allocated to intervention or control conditions . The intervention consisted of a self-affirmation manipulation , health messages based on the theory of planned behaviour and implementation intention tasks . Participants were followed-up 1 and 6 months after starting university . The primary outcome measures were portions of fruit and vegetables consumed , physical activity levels , units of alcohol consumed and smoking status at 6-month follow-up . Results The study recruited 2,621 students ( intervention n = 1346 , control n = 1275 ) , of whom 1495 completed at least one follow-up ( intervention n = 696 , control n = 799 ) . Intention-to-treat analyses indicated that the intervention had a non-significant effect on the primary outcomes , although the effect of the intervention on fruit and vegetable intake was significant in the per- protocol analyses . Secondary analyses revealed that the intervention had significant effects on having smoked at university ( self-report ) and on a biochemical marker of alcohol use . Conclusions Despite successfully increasing levels of engagement , the intervention did not have a significant effect on the primary outcome measures . The relatively weak effects of the intervention , found in both the original and repeat trials , may be due to the focus on multiple versus single health behaviours . Future interventions targeting the health behaviour of new university students should therefore focus on single health behaviours . Trial registration Current Controlled Trials IS RCT N07407344 Background Too few young people engage in behaviours that reduce the risk of morbidity and premature mortality , such as eating healthily , being physically active , drinking sensibly and not smoking . This study sought to assess the efficacy and cost-effectiveness of a theory-based online health behaviour intervention ( based on self-affirmation theory , the Theory of Planned Behaviour and implementation intentions ) targeting these behaviours in new university students , in comparison to a measurement-only control . Methods Two-weeks before starting university all incoming undergraduates at the University of Sheffield were invited to take part in a study of new students ’ health behaviour . A r and omised controlled design , with a baseline question naire , and two follow-ups ( 1 and 6 months after starting university ) , was used to evaluate the intervention . Primary outcomes were measures of the four health behaviours targeted by the intervention at 6-month follow-up , i.e. , portions of fruit and vegetables , metabolic equivalent of tasks ( physical activity ) , units of alcohol , and smoking status . Results The study recruited 1,445 students ( intervention n = 736 , control n = 709 , 58 % female , Mean age = 18.9 years ) , of whom 1,107 completed at least one follow-up ( 23 % attrition ) . The intervention had a statistically significant effect on one primary outcome , smoking status at 6-month follow-up , with fewer smokers in the intervention arm ( 8.7 % ) than in the control arm ( 13.0 % ; Odds ratio = 1.92 , p = .010 ) . There were no significant intervention effects on the other primary outcomes ( physical activity , alcohol or fruit and vegetable consumption ) at 6-month follow-up . Conclusions The results of the RCT indicate that the online health behaviour intervention reduced smoking rates , but it had little effect on fruit and vegetable intake , physical activity or alcohol consumption , during the first six months at university . However , engagement with the intervention was low . Further research is needed before strong conclusions can be made regarding the likely effectiveness of the intervention to promote health lifestyle habits in new university students . Trial registration Current Controlled Trials , IS RCT N67684181 Context Studies of the natural history of obesity have had limitations , such as cross-sectional design , short follow-up , or narrowly defined population s. Contribution Using data from a national study of Americans born between 1957 and 1964 and followed for nearly two decades , these investigators found that more than 25 % were obese by age 35 years . Obesity developed most quickly in black women , with moderate rapidity in Hispanic women , and most slowly in white women . Hispanic men developed obesity more quickly than other men . More recent birth cohorts became obese faster than earlier cohorts . Implication s Underst and ing ethnic differences in the age of onset and rate of progression of obesity may help efforts to prevent obesity . The Editors The proportion of Americans who are overweight or obese is increasing at an alarming rate . From 1960 to 1999 , the prevalence of excess weight ( body mass index [ BMI ] 25 kg/m2 ) increased from 44 % to 61 % of the adult population ( persons aged 20 to 74 years ) and the prevalence of obesity ( BMI 30 kg/m2 ) doubled from 13 % to 27 % ( 1 , 2 ) . Obesity has been linked to increased mortality and chronic morbidity from such diverse causes as hypertension , diabetes , sleep apnea , certain types of cancer , and depression . In the context of this rising prevalence , obesity is increasingly being recognized as an important medical and public health problem ( 3 - 6 ) . Treatment options are available for obesity . However , they can be expensive , often involve difficult lifestyle modifications , and pose adherence problems for many patients . In addition , weight loss , once achieved , is difficult to sustain . Because the health consequences are often long term , the costbenefit ratio of treatment may be more favorable if people who have recently become obese are targeted . Similarly , prevention should focus on those at immediate risk for becoming obese or overweight . Such approaches require a clear underst and ing of who is at highest risk for obesity , when this risk is greatest , and how excess weight develops over time . Although inactivity and high caloric intake are the primary risk factors for obesity , other risk factors have been established . Three of the most influential are age , sex , and race or ethnicity ( 1 , 7 - 9 ) . To better identify people at risk for obesity and those who might benefit from early intervention , we assessed the relationship between weight development and these influential factors . Despite the morbidity and mortality burden of obesity , its natural history has not been well characterized . Current knowledge is based largely on cross-sectional data . Although several large studies have examined weight development in adults , they have important limitations . Only a few tracked weight long enough to detect age-based trends . The first National Health and Nutrition Examination Survey ( NHANES I ) Epidemiologic Follow-up Study examined a representative group of U.S. residents but sample d only two time points , spaced 10 years apart , and had insufficient follow-up to track weight patterns in most minority groups ( 10 ) . The Coronary Artery Risk Development in Young Adults study followed weight development in a large cohort of young black and white Americans but did not provide data for other population s and was geographically restricted ( 8) . Other studies have been performed outside of the United States , but the results may not apply here ( 10 , 11 ) . We design ed our study to address the limitations described earlier . We examined data from the National Longitudinal Survey of Youth 1979 ( NLSY79 ) . This large , prospect i ve cohort study allowed longitudinal examination of weight trends over a time frame sufficient to capture the dynamics of such a slowly changing problem and of an age range during which obesity becomes prevalent . Because not all weight gain has been documented to be harmful , our analysis focused on obesity onset ( defined as the time at which a person reaches obesity ) rather than weight gain . We used the clinical definition of obesity ( BMI 30 kg/m2 ) as our end point because it reflects a point at which mortality risk increases substantially ( 12 ) . Underst and ing how obesity develops over time , who is at greatest risk , and when that risk is highest may be essential in reversing the population trend toward excess weight . Methods Study Group and Obesity Measurement We analyzed data from the NLSY79 , which was initiated by the U.S. Department of Labor , Bureau of Labor Statistics . This survey was design ed to gather information about the labor market activities and other life events of young U.S. citizens . It has been used extensively in economic and sociologic analyses , and the sample design is described elsewhere ( 13 - 16 ) . The cohort of men and women , born between 1957 and 1964 , has been followed for more than two decades . It consists of a nationally representative group , with supplemental sample s overrepresenting minority racial and ethnic groups and poor persons . We excluded a sample of military personnel because this population was removed from the study in 1985 and because physical activity requirements for these individuals could lead to atypical weight patterns . We included only persons who reported that the ethnicity with which they most closely identified was Hispanic , black , or white ( or European origin ) . Height and weight data were self-reported ; height was reported in 1981 and 1985 , and weight was reported 12 times between 1981 and 1998 . Examination of Age-Specific Body Mass Index Patterns Age-specific BMI was calculated for all participants . Height was assumed to remain constant after age 21 years . St and ard clinical definitions were used for overweight ( BMI 25 to 29.9 kg/m2 ) and obesity ( BMI 30 kg/m2 ) . Trends in age-specific BMI were examined by race or ethnicity and birth year . Cohort Differences We examined whether rates of obesity onset differed for people maturing at different times in our sample . Birth cohorts were grouped by 2-year increments . To st and ardize relative rates to age rather than calendar year , time was expressed as the number of years until a person reached obesity , starting from a st and ard age . In the cohort analysis , obesity onset was evaluated from age 24 years ( the baseline age of the oldest participants ) . The outcome of interest was obesity , and the time variable was years from age 24 years to obesity . People who were already obese at age 24 years were excluded . KaplanMeier plots visually demonstrated differences in rates of obesity onset . Cox proportional-hazards modeling estimated the ratio of rates ( hazard ratio ) between groups . For this method to be correct , the ratio of rates must be constant over time ( proportional ) . To assess this assumption , we used two methods : a statistical test of the scaled Schoenfeld residuals , with a P value greater than 0.05 implying that the rates were proportional and a visual method with parallel lines implying proportional rates . In all our analyses , results of proportional hazards testing were reported whenever the assumption was violated . Timing of Obesity Onset by Race or Ethnicity and Sex We evaluated relative rates of obesity onset in 17- and 18-year-old persons of different race or ethnicity who were not obese at the start of the study ; different models were used for men and women . Time was expressed as the number of years from age 17 years until reaching obesity . To control for birth cohort differences , models were adjusted for birth year . As before , KaplanMeier plots were examined and hazard ratios were estimated by using Cox proportional-hazards modeling . To determine relative importance of weight gain during childhood compared with adulthood in terms of the timing of obesity onset , we adjusted the models for baseline BMI at 17 or 18 years of age and examined the effect on hazard ratio estimation . Prevalence and Incidence of Obesity in Early Adulthood For this analysis , we defined early adulthood as the period from 20 to 22 years of age to 35 to 37 years of age . Persons born between 1959 and 1963 were queried about their weight one to two times during each of these age intervals . We calculated the prevalence and incidence of obesity across the early adulthood range . Logistic regression modeling predicted obesity status at age 35 to 37 years from an individual 's race or ethnicity , sex , and BMI at age 20 to 22 years . The model was adjusted in 2-year increments for year of birth . Its predictive ability was quantified by using receiver-operating characteristic ( ROC ) curves . This study was evaluated and exempted from review by the Institutional Review Board of the University of North Carolina at Chapel Hill . Role of the Funding Sources Primary funding was through the Robert Wood Johnson Clinical Scholars Program , with additional support from the National Institute of Child Health and Human Development . Neither entity had a role in the design , conduct , or reporting of this study . Results Description of the Study Sample The total sample included 9179 people : 19 % Hispanic , 31 % black , and 50 % white ( Table ) . People who did not report ethnicity ( n = 106 ) were not included . Age ( sample year minus birth year ) ranged from 17 to 24 years in 1981 to 34 to 41 years in 1998 , and participants were equally distributed across 8 years of birth . Baseline weight was 31.7 to 136.1 kg , and baseline BMI was 11.3 to 51.5 kg/m2 . Table . Sample Characteristics in 1981 Relationship of Body Mass Index to Time Mean age-specific BMI increased with time . This relationship between weight and time has two components , illustrated with data from the oldest and youngest birth cohorts of our sample ( Figure 1 ) . The first is the natural history of body weight : Average BMI increased with age throughout early adulthood . The second is a secular weight trend : Persons born in later calendar years tended to have larger age-specific BMI values . In every case in which the same age was sample d for both birth cohorts , the group born in 1957 had a lower mean BMI than the group born Background The unprecedented rise in obesity among young adults , who have limited interaction with health services , has not been successfully abated . Objective The objective of this study was to assess the maintenance outcomes of a 12-week mHealth intervention on prevention of weight gain in young adults and lifestyle behaviors at 9 months from baseline . Methods A two-arm , parallel , r and omized controlled trial ( RCT ) with subjects allocated to intervention or control 1:1 was conducted in a community setting in Greater Sydney , Australia . From November 2012 to July 2014 , 18- to 35-year-old overweight individuals with a body mass index ( BMI ) of 25 - 31.99 kg/m2 and those with a BMI ≥ 23 kg/m2 and a self-reported weight gain of ≥ 2 kg in the past 12 months were recruited . A 12-week mHealth program “ TXT2BFiT ” was administered to the intervention arm . This included 5 coaching calls , 96 text messages , 12 emails , apps , and downloadable re sources from the study website . Lifestyle behaviors addressed were intake of fruits , vegetables , sugar-sweetened beverages ( SSBs ) , take-out meals , and physical activity . The control group received 1 phone call to introduce them to study procedures and 4 text messages over 12 weeks . After 12 weeks , the intervention arm received 2 further coaching calls , 6 text messages , and 6 emails with continued access to the study website during 6-month follow-up . Control arm received no further contact . The primary outcome was weight change ( kg ) with weight measured at baseline and at 12 weeks and self-report at baseline , 12 weeks , and 9 months . Secondary outcomes were change in physical activity ( metabolic equivalent of task , MET-mins ) and categories of intake for fruits , vegetables , SSBs , and take-out meals . These were assessed via Web-based surveys . Results Two hundred and fifty young adults enrolled in the RCT . Intervention participants weighed less at 12 weeks compared with controls ( model β=−3.7 , 95 % CI −6.1 to −1.3 ) and after 9 months ( model β=− 4.3 , 95 % CI − 6.9 to − 1.8 ) . No differences in physical activity were found but all diet behaviors showed that the intervention group , compared with controls at 9 months , had greater odds of meeting recommendations for fruits ( OR 3.83 , 95 % CI 2.10 - 6.99 ) ; for vegetables ( OR 2.42 , 95 % CI 1.32 - 4.44 ) ; for SSB ( OR 3.11 , 95 % CI 1.47 - 6.59 ) ; and for take-out meals ( OR 1.88 , 95 % CI 1.07 - 3.30 ) . Conclusions Delivery of an mHealth intervention for prevention of weight gain result ed in modest weight loss at 12 weeks with further loss at 9 months in 18- to 35-year-olds . Although there was no evidence of change in physical activity , improvements in dietary behaviors occurred , and were maintained at 9 months . Owing to its scalable potential for widespread adoption , replication trials should be conducted in diverse population s of overweight young adults . Trial Registration Australian and New Zeal and Clinical Trials Registry ( ANZCTR ) : ACTRN12612000924853 ; ( Archived by WebCite at http://www.webcitation.org/6i6iRag55 Objective . Theory use may enhance effectiveness of behavioral interventions , yet critics question whether theory-based interventions have been sufficiently scrutinized . This study applied a framework to evaluate theory use in physical activity interventions for breast cancer survivors . The aims were to ( 1 ) evaluate theory application intensity and ( 2 ) assess the association between extensiveness of theory use and intervention effectiveness . Methods . Studies were previously identified through a systematic search , including only r and omized controlled trials published from 2005 to 2013 , that addressed physical activity behavior change and studied survivors who were < 5 years posttreatment . Eight theory items from Michie and Prestwich ’s coding framework were selected to calculate theory intensity scores . Studies were classified into three subgroups based on extensiveness of theory use ( Level 1 = sparse ; Level 2 = moderate ; and Level 3 = extensive ) . Results . Fourteen r and omized controlled trials met search criteria . Most trials used the  transtheoretical model  ( n = 5 ) or  social cognitive theory  ( n = 3 ) . For extensiveness of theory use , 5 studies were classified as Level 1 , 4 as Level 2 , and 5 as Level 3 . Studies in the extensive group ( Level 3 ) had the largest overall effect size ( g = 0.76 ) . Effects were more modest in Level 1 and 2 groups with overall effect sizes of g = 0.28 and g = 0.36 , respectively . Conclusions . Theory use is often viewed as essential to behavior change , but theory application varies widely . In this study , there was some evidence to suggest that extensiveness of theory use enhanced intervention effectiveness . However , there is more to learn about how theory can improve interventions for breast cancer survivors 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 Theory-based intervention programmes to support health-related behaviour change aim to increase health impact and improve underst and ing of mechanisms of behaviour change . However , the science of intervention development remains at an early stage . We present a causal modelling approach to developing complex interventions for evaluation in r and omized trials . In this approach a generic model links behavioural determinants , causally through behaviour , to physiological and biochemical variables , and health outcomes . It is tailored to context , target population , behaviours and health outcomes . The development of a specific causal model based on theory and evidence is illustrated by the ProActive programme , supporting increased physical activity  among individuals at risk of Type 2 diabetes . The model provides a rational guide to appropriate measures , intervention points and intervention techniques , and can be tested quantitatively . Causal modelling is critically compared to other approaches to intervention development and evaluation , and research directions are indicated Background Early adulthood represents the transition to independent living which is a period when changes in diet and body weight are likely to occur . This presents an ideal time for health interventions to reduce the effect of health problems and risk factors for chronic disease in later life . As young adults are high users of mobile devices , interventions that use this technology may improve engagement . The Connecting Health and Technology study aim ed to evaluate the effectiveness of tailored dietary feedback and weekly text messaging to improve dietary intake of fruit , vegetables and junk food over 6 months among a population -based sample of men and women ( aged 18–30 years ) . Methods A three-arm , parallel , r and omized control trial was conducted . After baseline assessment s , participants were r and omized to one of three groups : A ) dietary feedback and weekly text messages , B ) dietary feedback only or C ) control group .  Dietary intake was assessed using a mobile food record App ( mFR ) where participants captured images of foods and beverages consumed over 4-days at baseline and post-intervention . The primary outcomes were changes in serves of fruits , vegetables , energy-dense nutrient-poor ( EDNP ) foods and sugar-sweetened beverages ( SSB ) . The intervention effects were assessed using linear mixed effect models for change in food group serves . Results Young adults ( n = 247 ) were r and omized to group A ( n = 82 ) , group B ( n = 83 ) , or group C ( n = 82 ) . Overall , no changes in food group serves for either intervention groups were observed . An unanticipated outcome was a mean weight reduction of 1.7 kg ( P = .02 ) among the dietary feedback only . Men who received dietary feedback only , significantly reduced their serves of EDNP foods by a mean of 1.4 serves/day ( P = .02 ) . Women who received dietary feedback only significantly reduced their intake of SSB ( P = .04 ) by an average of 0.2 serves/day compared with controls . Conclusions Tailored dietary feedback only result ed in a decrease in EDNP foods in men and SSB in women , together with a reduction in body weight . Using a mobile food record for dietary assessment and tailored feedback has great potential for future health promotion interventions targeting diet and weight in young adults . Trial Registration Australian Clinical Trials Registry Registration number : ACTRN12612000250831 The college transition represents a critical period for maintaining a healthy weight , yet intervention participation and retention represent significant challenges . The objective of this investigation was to evaluate the preliminary efficacy and acceptability of two interventions to prevent freshman weight gain .  One intervention provided opportunities to improve outcome expectations and self-efficacy within a social cognitive theory framework ( SCT ) , while the other targeted the same variables but focused on explicit training in self-regulation skills ( SCTSR ) . Methods . Freshmen ( n = 45 ) aged > 18 years were r and omized to a 14-week intervention , SCT or SCTSR ; both included online modules and in-class meetings . Of the 45 students r and omized , 5 withdrew before the classes began and 39 completed pre- and posttesting . Primary outcomes included body weight/composition , health behaviors , and program acceptability . Analyses included independent sample t-tests , repeated measures ANOVA , and bivariate correlational analyses . Results . Body weight increased over the 14-week period , but there was no group difference . Percent body fat increased in SCTSR but not SCT ( mean difference : SCTSR , + 1.63 ± 0.52 % ; SCT , −0.25 ± 0.45 % ; P = 0.01 ) . Class attendance was 100 % ( SCTSR ) and 98 % ( SCT ) ; SCTSR students ( > 50 % ) remarked that the online tracking required “ too much time . ” Conclusions . The intervention was well received , although there were no improvements in weight outcomes Background Younger adults are difficult to engage in preventive health , yet in Australia they are gaining more weight and increasing in waist circumference faster than middle-to-older adults . A further challenge to engaging 18- to 35-year-olds in interventions is the limited reporting of outcomes of recruitment strategies . Objective This paper describes the outcomes of strategies used to recruit young adults to a r and omized controlled trial ( RCT ) , healthy lifestyle mHealth program , TXT2BFiT , for prevention of weight gain . The progression from enquiry through eligibility check to r and omization into the trial and the costs of recruitment strategies are reported . Factors associated with nonparticipation are explored . Methods Participants were recruited either via letters of invitation from general practitioners ( GPs ) or via electronic or print advertisements , including Facebook and Google — social media and advertising — university electronic newsletters , printed posters , mailbox drops , and newspapers .  Participants recruited from  GP invitation letters had an appointment booked with their GP for eligibility screening . Those recruited from other methods were sent an information pack to seek approval to participate from their own GP . The total number and source of enquiries were categorized according to eligibility and subsequent completion of steps to enrolment . Cost data and details of recruitment strategies were recorded . Results From 1181 enquiries in total from all strategies , 250 ( 21.17 % ) participants were r and omized . A total of 5311 invitation letters were sent from 12 GP practice s—16 participating GPs . A total of 131 patients enquired with 68 participants r and omized ( 68/74 of those eligible , 92 % ) . The other recruitment methods yielded the remaining 182 r and omized participants .  Enrolment from print media was 26 % of enquiries , from electronic media was 20 % , and from other methods was 3 % . Across all strategies the average cost of recruitment was Australian Dollar ( AUD ) $ 139 per person . The least expensive modality was electronic ( AUD $ 37 ) , largely due to a free feature story on one university Web home page , despite Facebook advertising costing AUD $ 945 per enrolment . The most expensive was print media at AUD $ 213 and GP letters at AUD $ 145 per enrolment . Conclusions The research indicated that free electronic media was the most cost-effective strategy , with GP letters the least expensive of the paid strategies in comparison to the other strategies . This study is an important contribution for future research into efficacy , translation , and implementation of cost-effective programs for the prevention of weight gain  in young adults .  Procedural frameworks for recruitment protocol s are required , along with systematic reporting of recruitment strategies to reduce unnecessary expenditure and allow for valuable public health prevention programs to go beyond the research setting . Trial Registration Australian New Zeal and Clinical Trials Registry ( ANZCTR ) : ACTRN12612000924853 ; https://www.anzctr.org.au/Trial/ Registration /Trial Review .aspx?id=362872 ( Archived by WebCite at http://www.webcitation.org/6YpNfv1gI ) OBJECTIVE Preventing obesity among young adults should be a preferred public health approach given the limited efficacy of treatment interventions . This study examined whether weight gain can be prevented by online approaches using two different behavioral models , one overtly directed at obesity and the other covertly . METHODS A three-group parallel r and omized controlled intervention was conducted in 2012 - 2013 ; 20,975 young adults were allocated a priori to one control and two " treatment " groups . Two treatment groups were offered online courses over 19 weeks on ( 1 ) personal weight control ( " Not the Ice Cream Van , " NTICV ) and , ( 2 ) political , environmental , and social issues around food ( " Goddess Demetra , " " GD " ) . Control group received no contact . The primary outcome was weight change over 40 weeks . RESULTS Within-group 40-week weight changes were different between groups ( P < 0.001 ) : Control ( n = 2,134 ) : + 2.0 kg ( 95 % CI = 1.5 , 2.3 kg ) ; NTICV ( n = 1,810 ) : -1.0 kg ( 95 % CI = -1.3 , -0.5 ) ; and GD ( n = 2,057 ) : -1.35 kg ( 95 % CI = -1.4 to -0.7 ) . Relative risks for weight gain vs. CONTROL NTICV = 0.13 kg ( 95 % CI = 0.10 , 0.15 ) , P < 0.0001 ; GD = 0.07 kg ( 95 % CI = 0.05 , 0.10 ) , P < 0.0001 . CONCLUSIONS Both interventions were associated with prevention of the weight gain observed among control subjects . This low-cost intervention could be widely transferable as one tool against the obesity epidemic . Outside the r and omized controlled trial setting , it could be enhanced using supporting advertising and social media INTRODUCTION The young adult years have been recognized as an influential period for excess weight gain . Non-traditional students and those attending 2-year community colleges are at particularly high risk for a range of adverse weight-related outcomes . DESIGN Choosing Healthy Options in College Environments and Setting s was an RCT with students r and omly assigned into a control or intervention condition after baseline assessment . The study was design ed to evaluate if a 24-month weight-gain prevention intervention reduces the expected increase in BMI and overweight prevalence in young adults attending 2-year colleges . Two cohorts were recruited , corresponding to the fall and spring semesters . Data collection occurred at four time points for each cohort , with baseline occurring in fall 2011 for Cohort 1 and spring 2012 for Cohort 2 . The 24-month follow-up occurred in fall 2013 for Cohort 1 and spring 2014 for Cohort 2 . Data analysis occurred in 2015 - 2016 . SETTING / PARTICIPANTS This research was conducted with 441 students from three community colleges in Minnesota . INTERVENTION The 24-month intervention began with a 1-credit college course on healthy weight behaviors . A social networking and social support website was introduced as part of the course and participation encouraged for the duration of the trial . MAIN OUTCOME MEASURES Changes in BMI , weight , body fat percentage , waist circumference , and weight status were assessed . RESULTS Retention of the cohorts at 24 months was 83.4 % . There was not a statistically significant difference in BMI between conditions at the end of the trial . However , there was a statically significant difference in the prevalence of overweight/obesity between treatment conditions at 24 months . Also , participants r and omized to the intervention who were overweight or obese at baseline were more than three times as likely to transition to a healthy weight by the end of the trial as compared with control students . CONCLUSIONS The intervention was not successful in achieving BMI differences between treatment groups . However , an 8 % reduction in the prevalence of overweight and obesity over time may have population -level significance . TRIAL REGISTRATION This study is registered at www . clinical trials.gov NCT01134783 Purpose . To identify impact of an online nutrition and physical activity program for college students . Design . R and omized , controlled trial using online question naires and on-site physical and fitness assessment s with measurement intervals of 0 ( baseline ) , 3 ( postintervention ) , and 15 months ( follow-up ) . Setting . Online intervention delivered to college students ; a central ized Web site was used for recruitment , data collection , data management , and intervention delivery . Subjects . College students ( 18–24 years old , n = 1689 ) , from eight universities ( Michigan State University , South Dakota State University , Syracuse University , The Pennsylvania State University , Tuskegee University , University of Rhode Isl and , University of Maine , and University of Wisconsin ) . Intervention . A 10-lesson curriculum focusing on healthful eating and physical activity , stressing nondieting principles such as size acceptance and eating competence ( software developer : Rainstorm , Inc , Orono , Maine ) . Measures . Measurements included anthropometrics , cardiorespiratory fitness , fruit/vegetable ( FV ) intake , eating competence , physical activity , and psychosocial stress . Analysis . Repeated measures analysis of variance for outcome variables . Results . Most subjects were white , undergraduate females ( 63 % ) , with 25 % either overweight or obese . Treatment group completion rate for the curriculum was 84 % . Over 15 months , the treatment group had significantly higher FV intake ( + .5 cups/d ) and physical activity participation ( + 270 metabolic equivalent minutes per week ) than controls . For both groups , anthropometric values and stress increased , and fitness levels decreased . Gender differences were present for most variables . First-year males and females gained more weight than participants in other school years . Conclusion . A 10-week online nutrition and physical activity intervention to encourage competence in making healthful food and eating decisions had a positive , lasting effect on FV intake and maintained baseline levels of physical activity in a population that otherwise experiences significant declines in these healthful behaviors Abstract Objective : To determine the impact of My Student Body (MSB)–Nutrition , an Internet-based obesity prevention program for college students . Participants : Three hundred and twenty ethnically diverse undergraduate students were r and omly assigned to 1 of 3 conditions : MSB-Nutrition program , an on-campus weight management course , and a comparison group . Methods : Students completed baseline and follow-up surveys regarding their nutrition and physical activity behaviors , self-efficacy , stress , attitudes , and body weight . Results : Compared with the on-campus course and a comparison group , the MSB-Nutrition program increased fruit and vegetable consumption , reduced stress , and increased fruit and vegetable self-efficacy but had no significant effect on students ’ exercise self-efficacy , exercise behavior , or weight loss . Conclusions : The MSB-Nutrition program was effective in changing students ’ nutrition behaviors but had no effect on physical activity behaviors or weight loss . Suggestions for improving Internet-based interventions aim ed at decreasing obesity rates among college students are offered BACKGROUND Today 's generation of young adults are gaining weight faster than their parents ; however , there remains insufficient evidence to inform interventions to prevent this weight gain .  Mobile phones are a popular means of communication that may provide a convenient , inexpensive means to deliver health intervention programmes . This pilot study aim ed to measure the effect of a 12-week mobile health ( mHealth ) intervention on body weight , body mass index and specific lifestyle behaviours addressed by the programme . METHODS University students and staff aged 18 - 35 years ( n = 51 ) were r and omised ( ratio 1 : 1 , intervention : control ) . Both groups received a printed diet booklet with instructions prepared by a dietitian . The intervention group also received Short Message Service ( SMS ) text messages ( four per week ) , e-mails ( four per week ) , and had access to smartphone applications and Internet forums . RESULTS Pre- to post-intervention , participants in the intervention group decreased their body weight [ mean ( SD ) ] [ -1.6 ( 2.6 ) kg ] , increased their light intensity activity [ 34 ( 35 ) min day(-1 ) ] and reported an increased vegetable ( 1.0 median serving day(-1 ) ) and decreased sugar-sweetened beverage intake [ -355 ( 836 ) mL week(-1 ) ] . Despite this , post-intervention changes in outcomes were not significantly different from controls . CONCLUSIONS The piloted mHealth programme provided some short-term positive changes in weight , nutrition and physical activity using a low cost , convenient delivery method for this population . However , changes were no different from those observed among controls . This might partly be explained by intervention participants ' low engagement with the programme , which is likely to require further modification to provide more regular , personalised , monitored support OBJECTIVE To assess the effectiveness of a tailored theory-based , Web-delivered intervention ( Young Adults Eating and Active for Health ) developed using community-based participatory research process . DESIGN A 15-month ( 10-week intensive intervention with a 12-month follow-up ) r and omized , controlled trial delivered via Internet and e-mail . SETTING Thirteen college campuses . PARTICIPANTS A total of 1,639 college students . INTERVENTION Twenty-one mini-educational lessons and e-mail messages ( called nudges ) developed with the non-diet approach and focusing on eating behavior , physical activity , stress management , and healthy weight management . Nudges were short , frequent , entertaining , and stage-tailored to each behavior , and reinforced lesson content . MAIN OUTCOME MEASURE All participants were assessed at baseline , postintervention ( 3 months from baseline ) , and follow-up ( 15 months from baseline ) for primary outcomes of weight , body mass index ( BMI ) , fruit and vegetable intake ( FVI ) , physical activity ( PA ) , and perceived stress ; and secondary outcomes of waist circumference , percent dietary fat , energy from sugar-sweetened beverages , servings of whole grains , self-instruction and regulation for mealtime behavior , hours of sleep , and stage of readiness for change for consuming 5 cups of FVI , completing 150 minutes of PA/wk , and managing stress on most days of the week . Demographics were collected at baseline . ANALYSIS Chi-square analysis and mixed-models repeated measures analysis were performed to determine differences between experimental and control outcomes . RESULTS There were no differences between experimental and control participants in BMI , weight , and waist circumference . There were small improvements in FVI ( P = .001 ) , vigorous PA in females ( P = .05 ) , fat intake ( P = .002 ) , self-instruction ( P = .001 ) , and regulation ( P = .004 ) for mealtime behavior , and hours of sleep ( P = .05 ) at postintervention , but improvements were not maintained at follow-up . At postintervention , a greater proportion of experimental participants were in the action/maintenance stages for FVI ( P = .019 ) and PA ( P = .002 ) than control . CONCLUSIONS AND IMPLICATION S Young Adults Eating and Active for Health is one of the first studies to use the community-based participatory research process of PRECEDE-PROCEED to develop a non-diet approach intervention . Although there were no differences between experimental and control participants in weight change or BMI , the intervention supported positive change in behaviors that may mediate excessive weight gain , such as increasing FVI and more healthful self-regulation mealtime behaviors immediately postintervention . Additional strategies to maintain the behavior changes need to be explored OBJECTIVE An intervention using Wi-Fi scales and graphic e-mail feedback , the caloric titration method ( CTM ) , to reduce age-related weight gain over 1 year among college students was evaluated . METHODS First-year college students ( n = 167 ) were r and omized to CTM or control ( C ) groups and provided Wi-Fi scales . The CTM group was instructed to weigh daily , view a weight graph e-mailed to them after weighing , and try to maintain their weight . The C group could weigh at any time but did not receive feedback . At 6 months and 1 year , the C group provided weights . For intention to treat analysis , an adjusted mixed model was used to analyze the effect of the intervention . RESULTS Baseline body mass index was 22.9 ± 3.0 kg/m(2 ) . Ninety-five percent of the CTM participants weighed ≥ 3 times/week , compared to 15 % in the C group ( P < 0.001 ) . After 1 year , the C group had gained 1.1 ± .4 kg whereas the CTM group lost 0.5 ± 3.7 kg ( F = 3.39 , P = 0.035 ) . The difference in weight change between the two groups at 1 year was significant ( P = 0.004 ) . Retention was 81 % . CONCLUSIONS CTM intervention was effective in preventing age-related weight gain in young adults over 1 year and thus offers promise to reduce overweight and obesity Background Mobile technologies have great potential to promote an active lifestyle in lower educated working young adults , an under research ed target group at a high risk of low activity levels . Objective The objective of our study was to examine the effect and process evaluation of the newly developed evidence - and theory-based smartphone app “ Active Coach ” on the objective ly measured total daily physical activity ; self-reported , context -specific physical activity ; and self-reported psychosocial variables among lower educated working young adults . Methods We recruited 130 lower educated working young adults in this 2-group cluster r and omized controlled trial and assessed outcomes at baseline , posttest ( baseline+9 weeks ) , and follow-up ( posttest+3 months ) . Intervention participants ( n=60 ) used the Active Coach app ( for 9 weeks ) combined with a Fitbit activity tracker . Personal goals , practical tips , and educational facts were provided to encourage physical activity . The control group received print-based generic physical activity information . Both groups wore accelerometers for objective measurement of physical activity , and individual interviews were conducted to assess the psychosocial variables and context -specific physical activity . Furthermore , intervention participants were asked process evaluation questions and generalized linear mixed models and descriptive statistics were applied . Results No significant intervention effects were found for objective ly measured physical activity , self-reported physical activity , and self-reported psychosocial variables ( all P>.05 ) . Intervention participants evaluated the Active Coach app and the combined use with the Fitbit wearable as self-explanatory ( 36/51 , 70.6 % ) , user friendly ( 40/51 , 78.4 % ) , and interesting ( 34/51 , 66.7 % ) . Throughout the intervention , we observed a decrease in the frequency of viewing graphical displays in the app ( P<.001 ) ; reading the tips , facts , and goals ( P<.05 ) ; and wearing the Fitbit wearable ( P<.001 ) . Few intervention participants found the tips and facts motivating ( 10/41 , 24.4 % ) , used them to be physically active ( 8/41 , 19.6 % ) , and thought they were tailored to their lifestyle ( 7/41 , 17.1 % ) . Conclusions The lack of significant intervention effects might be due to low continuous user engagement . Advice or feedback that was not perceived as adequately tailored and the difficulty to compete with many popular commercial apps on young people ’s smartphones may be responsible for a decrease in the engagement . A st and -alone app does not seem sufficient to promote an active lifestyle among lower educated working young adults ; therefore , multicomponent interventions ( using both technological and human support ) , as well as context -specific sensing to provide tailored advice , might be needed in this population . Trial Registration Clinical Trials.gov NCT02948803 ; https:// clinical trials.gov/ct2/show/ results /NCT02948803 ( Archived by WebCite at http://www.webcitation.org/71OPFwaoA PURPOSE Health interventions based on theory may be more effective than those that are not . This review of review s synthesizes all published r and omized controlled trial ( RCT ) meta-analytic evidence from the last decade to examine whether theory-based interventions were found to be associated with more effective  adult health behaviour change interventions . METHODS Systematic review s including meta-analyses were identified by search ing Medline , CINAHL , PsycINFO , and CDSR . A narrative synthesis was used to summarize and analyse the evidence . Only review s including RCTs of health behaviour change interventions with adults aged 18 + published from 2007 to 2017 were included . RESULTS Of 8,659 articles , nine systematic review s met inclusion criteria . The majority of review s ( n = 8) suggested no increased effectiveness for theory-based compared to non-theory-based interventions for effectiveness of outcomes relating to health behaviour . Less than half of the RCTs included in the review s reported the use of theory ( 85/183 ) . Two review s suggested interventions based on control theory , motivational interviewing , or self-determination theory were associated with greater effectiveness for physical activity and /or dietary interventions and outcomes . Method ological and reporting issues limit the conclusions . CONCLUSIONS Theory-based interventions as currently operationalized in systematic review s were not found to be more effective than non-theory-based interventions . Method ological and reporting issues at study and review level may not reflect the true utility of theory use within health behaviour interventions . The promotion of theory use may benefit from using a multifaceted argument , rather than a narrow focus of increased effectiveness . Statement of contribution What is already known on this subject ? Theory use is regularly promoted by cl aim ing that it will lead to more effective behaviour change interventions . Theory use has been frequently linked to effectiveness within systematic review s of behaviour change interventions . The theory-effectiveness hypothesis has not been systematic ally examined at the systematic review level . What does this study add ? Theory use as operationalized by systematic review authors was not associated with increased effectiveness within systematic review s examining r and omized controlled trials of behaviour change interventions in adults . Interventions based on control theory , motivational interviewing , or self-determination theory were associated with greater effectiveness for physical activity and /or dietary interventions and outcomes . Theory use should be promoted using a multifaceted argument , and assertions for increased effectiveness of theory-based interventions should only be used in domains where specific evidence exists to support this cl aim Background — The benefits of healthy habits are well established , but it is unclear whether making health behavior changes as an adult can still alter coronary artery disease risk . Methods and Results — The Coronary Artery Risk Development in Young Adults ( CARDIA ) prospect i ve cohort study ( n=3538 ) assessed 5 healthy lifestyle factors ( HLFs ) among young adults aged 18 to 30 years ( year 0 baseline ) and 20 years later ( year 20 ) : not overweight/obese , low alcohol intake , healthy diet , physically active , nonsmoker . We tested whether change from year 0 to 20 in a continuous composite HLF score ( HLF change ; range , −5 to + 5 ) is associated with sub clinical atherosclerosis ( coronary artery calcification and carotid intima-media thickness ) at year 20 , after adjustment for demographics , medications , and baseline HLFs . By year 20 , 25.3 % of the sample improved ( HLF change ≥+1 ) ; 40.4 % deteriorated ( had fewer HLFs ) ; 34.4 % stayed the same ; and 19.2 % had coronary artery calcification ( > 0 ) . Each increase in HLFs was associated with reduced odds of detectable coronary artery calcification ( odds ratio=0.85 ; 95 % confidence interval , 0.74–0.98 ) and lower intima-media thickness ( carotid bulb & bgr;=−0.024 , P=0.001 ) , and each decrease in HLFs was predictive to a similar degree of greater odds of coronary artery calcification ( odds ratio=1.17 ; 95 % confidence interval , 1.02–1.33 ) and greater intima-media thickness ( & bgr;=+0.020 , P<0.01 ) . Conclusions — Healthy lifestyle changes during young adulthood are associated with decreased risk and unhealthy lifestyle changes are associated with increased risk for sub clinical atherosclerosis in middle age
ABSTRACT This review assesses the extent of reported theory use in electronic health weight management interventions  targeting young adults aged 18–35 years .