This study aimed to understand how college students participating in a 2-year randomized controlled trial (Project SMART: Social and Mobile Approach to Reduce Weight; N = 404) engaged their social networks and used social and mobile technologies to try and lose weight. Participants in the present study (n = 20 treatment, n = 18 control) were approached after a measurement visit and administered semi-structured interviews. Interviews were analyzed using principles from grounded theory. Treatment group participants appreciated the timely support provided by the study and the integration of content across multiple technologies. Participants in both groups reported using non-study-designed apps to help them lose weight, and many participants knew one another outside of the study. Individuals talked about weight-loss goals with their friends face to face and felt accountable to follow through with their intentions. Although seeing others' success online motivated many, there was a range of perceived acceptability in talking about personal health-related information on social media. The findings from this qualitative study can inform intervention trials using social and mobile technologies to promote weight loss. For example, weight-loss trials should measure participants' use of direct-to-consumer technologies and interconnectivity so that treatment effects can be isolated and cross-contamination accounted for.

BACKGROUND:Weight loss interventions based solely on text messaging (short message service [SMS]) have been shown to be modestly effective for short periods of time and in some populations, but limited evidence is available for positive longer-term outcomes and for efficacy in Hispanic populations. Also, little is known about the comparative efficacy of weight loss interventions that use SMS coupled with brief, technology-mediated contact with health coaches, an important issue when considering the scalability and cost of interventions. We examined the efficacy of a 1-year intervention designed to reduce weight among overweight and obese English- and Spanish-speaking adults via SMS alone (ConTxt) or in combination with brief, monthly health-coaching calls. ConTxt offered 2-4 SMS/day that were personalized, tailored, and interactive. Content was theory- and evidence-based and focused on reducing energy intake and increasing energy expenditure. Monthly health-coaching calls (5-10 minutes' duration) focused on goal-setting, identifying barriers to achieving goals, and self-monitoring. METHODS AND FINDINGS:English- and Spanish-speaking adults were recruited from October 2011 to March 2013. A total of 298 overweight (body mass index [BMI] 27.0 to 39.9 kg/m2) adults (aged 21-60 years; 77% female; 41% Hispanic; 21% primarily Spanish speaking; 44% college graduates or higher; 22% unemployed) were randomly assigned (1:1) to receive either ConTxt only (n = 101), ConTxt plus health-coaching calls (n = 96), or standard print materials on weight reduction (control group, n = 101). We used computer-based permuted-block randomization with block sizes of three or six, stratified by sex and Spanish-speaking status. Participants, study staff, and investigators were masked until the intervention was assigned. The primary outcome was objectively measured percent of weight loss from baseline at 12 months. Differences between groups were evaluated using linear mixed-effects regression within an intention-to-treat framework. A total of 261 (87.2%) and 253 (84.9%) participants completed 6- and 12-month visits, respectively. Loss to follow-up did not differ by study group. Mean (95% confidence intervals [CIs]) percent weight loss at 12 months was -0.61 (-1.99 to 0.77) in the control group, -1.68 (-3.08 to -0.27) in ConTxt only, and -3.63 (-5.05 to -2.81) in ConTxt plus health-coaching calls. At 12 months, mean (95% CI) percent weight loss, adjusted for baseline BMI, was significantly different between ConTxt plus health-coaching calls and the control group (-3.0 [-4.99 to -1.04], p = 0.003) but not between the ConTxt-only and the control group (-1.07 [-3.05 to 0.92], p = 0.291). Differences between ConTxt plus health-coaching calls and ConTxt only were not significant (-1.95 [-3.96 to 0.06], p = 0.057). These findings were consistent across other weight-related secondary outcomes, including changes in absolute weight, BMI, and percent body fat at 12 months. Exploratory subgroup analyses suggested that Spanish speakers responded more favorably to ConTxt plus health-coaching calls than English speakers (Spanish contrast: -7.90 [-11.94 to -3.86], p < 0.001; English contrast: -1.82 [-4.03 to 0.39], p = 0.107). Limitations include the unblinded delivery of the intervention and recruitment of a predominantly female sample from a single site. CONCLUSIONS:A 1-year intervention that delivered theory- and evidence-based weight loss content via daily personalized, tailored, and interactive SMS was most effective when combined with brief, monthly phone calls. TRIAL REGISTRATION:ClinicalTrials.gov NCT01171586.

Background

Few weight loss interventions are evaluated for longer than a year, and even fewer employ social and mobile technologies commonly used among young adults. We assessed the efficacy of a 2 year, theory-based, weight loss intervention that was remotely and adaptively delivered via integrated user experiences with Facebook, mobile apps, text messaging, emails, a website, and technology-mediated communication with a health coach (the SMART intervention).

Methods

In this parallel-group, randomised, controlled trial, we enrolled overweight or obese college students (aged 18-35 years) from three universities in San Diego, CA, USA. Participants were randomly assigned (1:1) to receive either the intervention (SMART intervention group) or general information about health and wellness (control group). We used computer-based permuted-block randomisation with block sizes of four, stratified by sex, ethnicity, and college. Participants, study staff, and investigators were masked until the intervention was assigned. The primary outcome was objectively measured weight in kg at 24 months. Differences between groups were evaluated using linear mixed-effects regression within an intention-to-treat framework. Objectively measured weight at 6, 12, and 18 months was included as a secondary outcome. The trial is registered with ClinicalTrials.gov, number NCT01200459.

Findings

Between May 18, 2011, and May 17, 2012, 404 individuals were randomly assigned to the intervention (n=202) or control (n=202). Participants' mean (SD) age was 22·7 (3·8) years. 284 (70%) participants were female and 125 (31%) were Hispanic. Mean (SD) body-mass index at baseline was 29·0 (2·8) kg/m(2). At 24 months, weight was assessed in 341 (84%) participants, but all 404 were included in analyses. Weight, adjusted for sex, ethnicity, and college, was not significantly different between the groups at 24 months (-0·79 kg [95% CI -2·02 to 0·43], p=0·204). However, weight was significantly less in the intervention group compared with the control group at 6 months (-1·33 kg [95% CI -2·36 to -0·30], p=0·011) and 12 months (-1·33 kg [-2·30 to -0·35], p=0·008), but not 18 months (-0·67 kg [95% CI -1·69 to 0·35], p=0·200). One serious adverse event in the intervention group (gallstones) could be attributable to rapid and excessive weight loss.

Interpretation

Social and mobile technologies did not facilitate sustained reductions in weight among young adults, although these approaches might facilitate limited short-term weight loss.

Funding

The National Heart, Lung, and Blood Institute of the National Institutes of Health (U01 HL096715).

Objective

The goal of the present study was to deconstruct the 17 treatment arms used in the Early Adult Reduction of weight through LifestYle (EARLY) weight management trials.

Methods

Intervention materials were coded to reflect behavioral domains and behavior change techniques (BCTs) within those domains planned for each treatment arm. The analytical hierarchy process was employed to determine an emphasis profile of domains in each intervention.

Results

The intervention arms used BCTs from all of the 16 domains, with an average of 29.3 BCTs per intervention arm. All 12 of the interventions included BCTs from the six domains of Goals and Planning, Feedback and Monitoring, Social Support, Shaping Knowledge, Natural Consequences, and Comparison of Outcomes; 11 of the 12 interventions shared 15 BCTs in common across those six domains.

Conclusions

Weight management interventions are complex. The shared set of BCTs used in the EARLY trials may represent a core intervention that could be studied to determine the required emphases of BCTs and whether additional BCTs add to or detract from efficacy. Deconstructing interventions will aid in reproducibility and understanding of active ingredients.

Advances in information technology and near ubiquity of the Internet have spawned novel modes of communication and unprecedented insights into human behavior via the digital footprint. Health behavior randomized controlled trials (RCTs), especially technology-based, can leverage these advances to improve the overall clinical trials management process and benefit from improvements at every stage, from recruitment and enrollment to engagement and retention. In this paper, we report the results for recruitment and retention of participants in the SMART study and introduce a new model for clinical trials management that is a result of interdisciplinary team science. The MARKIT model brings together best practices from information technology, marketing, and clinical research into a single framework to maximize efforts for recruitment, enrollment, engagement, and retention of participants into a RCT. These practices may have contributed to the study's on-time recruitment that was within budget, 86% retention at 24 months, and a minimum of 57% engagement with the intervention over the 2-year RCT. Use of technology in combination with marketing practices may enable investigators to reach a larger and more diverse community of participants to take part in technology-based clinical trials, help maximize limited resources, and lead to more cost-effective and efficient clinical trial management of study participants as modes of communication evolve among the target population of participants.