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Recent reviews suggest Web-based interventions are promising approaches for weight management but they identify difficulties with suboptimal usage. The literature suggests that offering some degree of human support to website users may boost usage and outcomes.
We disseminated the POWeR (“Positive Online Weight Reduction”) Web-based weight management intervention in a community setting. POWeR consisted of weekly online sessions that emphasized self-monitoring, goal-setting, and cognitive/behavioral strategies. Our primary outcome was intervention usage and we investigated whether this was enhanced by the addition of brief telephone coaching. We also explored group differences in short-term self-reported weight loss.
Participants were recruited using a range of methods including targeted mailouts, advertisements in the local press, notices on organizational websites, and social media. A total of 786 adults were randomized at an individual level through an online procedure to (1) POWeR only (n=264), (2) POWeR plus coaching (n=247), or (3) a waiting list control group (n=275). Those in the POWeR plus coaching arm were contacted at approximately 7 and 28 days after randomization for short coaching telephone calls aimed at promoting continued usage of the website. Website usage was tracked automatically. Weight was assessed by online self-report.
Of the 511 participants allocated to the two intervention groups, the median number of POWeR sessions completed was just one (IQR 0-2 for POWeR only, IQR 0-3 for POWeR plus coach). Nonetheless, a substantial minority completed at least the core three sessions of POWeR: 47 participants (17.8%, 47/264) in the POWeR-only arm and 64 participants (25.9%, 64/247) in the POWeR plus coaching arm. Participants in the POWeR plus coaching group persisted with the intervention for longer and were 1.61 times more likely to complete the core three sessions than the POWeR-only group (χ2
1=4.93; OR 1.61, 95% CI 1.06-2.47; n=511). An intention-to-treat analysis showed between-group differences in weight loss (
In common with most Web-based intervention studies, usage of POWeR was suboptimal overall. However, our findings suggest that supplementing Web-based weight management with brief human support could improve usage and outcomes in those who take it up.
International Standard Randomized Controlled Trial Number (ISRCTN): 98176068; http://www.controlled-trials.com/ISRCTN98176068 (Archived by WebCite at http://www.webcitation.org/6OKRjM2oy).
Internationally, obesity is one of the biggest public health concerns [
Despite holding promise as potentially cost-effective interventions, recent reviews of Web-based weight loss interventions have found that effect sizes for weight loss tend to be fairly modest, with substantial heterogeneity in outcomes, and many online programs suffer from suboptimal engagement [
One possible explanation for variations in the efficacy of and engagement with Web-based interventions is the variation in the human contact participants have to support them as they participate in the Web-based program. Human support may be in various formats including face-to-face individual or group meetings, telephone calls, text messages, emails, or online chat. It may be from health professionals, researchers, or technicians and may serve various purposes ranging from answering technical queries, to encouraging prolonged use, to providing substantial therapeutic input. Taken as a whole, the eHealth literature suggests that engagement and behavioral or health outcomes for Web-based interventions tend to be better when usage is accompanied by some form of human contact [
Overall, there has been insufficient research focused on how to use human contact to boost engagement with Web interventions. This is an important research topic since extensive reach and low marginal cost per additional user are among the key proposed benefits of Web-based interventions [
In the current study, we disseminated “POWeR” (Positive Online Weight Reduction), a completely automated Web-based weight management intervention (described in detail below). Other RCTs (ISRCTN31685626 and ISRCTN21244703) are examining the efficacy of POWeR for weight loss in a primary care setting with nurse support. In contrast, the current study sought to investigate engagement with this intervention in a high-reach, low-cost public health context. Unlike previous Web-based weight management trials, our research procedures were handled automatically by our intervention software, which meant that the trial took place without participants having contact with the researchers at registration, baseline, and follow-up. We examined engagement with the intervention and self-reported weight change in this more remote context and tested whether the provision of brief human support influenced this.
Our primary aim was to assess whether human support in the form of brief telephone coaching, based around the Supportive Accountability framework [
Ethics and research governance approvals were granted by the University of Southampton and the trial was registered (ISRCTN98176068). A variety of methods were used to recruit participants from community settings in the North East of the United Kingdom between June 2012 and January 2013. We mailed out written invitations to 15,000 homes, which resulted in 287 registrations—a 1.91% response rate. Other recruitment methods included local press releases, posters in community settings, and information on local government and NHS (National Health Service) public health websites and intranet, as well as paid advertising on Facebook and posts/tweets on organizational social media.
Recruitment materials invited members of the public to try a new online weight management program as part of a research trial. Recruitment materials and participant information sheets carried the organization name and logo of the local NHS public health organization and also emphasized the involvement of academics and clinicians from the University of Southampton in the development of the intervention. Participation was free and no financial incentives were provided.
All recruitment procedures including study information, eligibility screening, obtaining informed consent, baseline data collection, and randomization were conducted online using automated procedures. To proceed through the registration process, participants had to report being UK-resident adults with a body mass index (BMI) of ≥23 and having regular Internet access. Users were cautioned to consult a health professional prior to using POWeR if they reported having a condition that might make changing diet and exercise inappropriate.
The first author’s email address was provided for asking questions prior to signing up (no questions were received). A “POWeR” email address was provided once participants were in the trial. Brief email contact between participants and the first author took place if participants needed to report technical problems or request withdrawal or cancellation of automatic email prompts or reminders. With the exception of coach phone calls and emails received by the POWeR plus coaching participants, there was no other human contact with participants while they were in the trial.
Randomization was at the individual level and stratified by BMI (lower BMI <27.5 vs higher BMI ≥27.5) to ensure that the arms were reasonably balanced in terms of overweight, obese, and morbidly obese participants. Participants were allocated with a balanced ratio to one of three arms. The “POWeR only” arm was granted immediate access to the POWeR intervention. The “POWeR plus coaching” arm was granted immediate access to the intervention plus telephone coaching (described below). The waiting list “Control” arm was blocked from using POWeR for 8 weeks. They were not given specific instructions to abstain from weight management or avoid using other interventions during this time. At the end of the 8 weeks, they were provided with access to POWeR (without coaching). It was impossible to blind participants or coaches to trial arm assignment. Researchers were not blinded but did not interact with or collect data from participants directly, as usage was tracked automatically and self-report data was collected via online questionnaires.
The sample size was calculated a priori using GPOWER v3.1 [
POWeR is a fully automated, tailored, Web-based weight management intervention constructed using the LifeGuide open access intervention authoring software [
Intended use of POWeR is the completion of one session per week. Each time a session is completed the subsequent session becomes available 7 days later and remains available until the user next logs in. Participants received automatic email reminders to advise them that their new session is ready, provide a description of what will be covered, and invite them to log in to use it. They also received one automatic email reminder one week later if they had not logged on. A total of 12 different sessions are available and users can continue to complete sessions for as long as they are finding it useful and log in to complete weekly weight and goal reviews even after all sessions have been completed. In the current trial, we followed up with participants and examined their engagement with the intervention and weight loss 8 weeks after randomization.
During the trial, the intervention content was “frozen” and no changes or bug fixes were made to the POWeR website.
The coaching calls aimed to promote continued usage of the POWeR website and adherence to the recommendations within the website. Coaches were postgraduate students and research assistants affiliated with the health psychology research center at the University of Southampton who had been provided with training in the coaching procedures and a brief introduction to the POWeR website. Coaching procedures were developed based on the Supportive Accountability model [
Summary of content of coaching telephone calls.
Call | Content |
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Welcome participant to POWeR |
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Build a friendly relationship |
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Explain what the role of the coach is/is not |
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Explain how progress monitoring will be conducted and reassure that it will be done in a supportive and encouraging way |
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Review POWeR use so far (with reference to data available in the coach portal) |
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Praise/encourage any POWeR use (or gently explore reasons for non-use and encourage future use) |
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Ask about questions and concerns and point in direction of POWeR tools/future sessions |
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Ask about eating goals and plans (with reference to data available in the coach portal) and offer encouragement |
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Remind about on-going monitoring and another phone call in week 4 |
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Build a friendly relationship |
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Remind about reason for today’s call |
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Review POWeR use (with reference to data available in the coach portal) |
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Praise/encourage any POWeR use (or gently explore reasons for non-use and encourage future use). |
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If relevant, congratulate on weight loss (with reference to data available in the coach portal) |
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Ask about questions and concerns and point in direction of POWeR tools/future sessions |
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Ask about eating and physical activity goals and plans (with reference to data available in the coach portal) and offer encouragement |
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Mention coaching is ending and suggest considering support from elsewhere |
The primary outcome variable (usage of the Web-based intervention) was automatically logged by the intervention software. The LifeGuide software logs all usage data including which pages were viewed, in what order, when, and for how long. For the current analyses, we analyzed the number of POWeR sessions each participant had completed by 8-week follow-up.
All self-report data were collected using Web-based questionnaires. To ensure we had complete data on our participants at baseline, all baseline questionnaires were mandatory (ie, the participant could not progress without submitting a response). The follow-up point was 8 weeks post-randomization. Automatically generated emails requested participants to complete a brief follow-up questionnaire and included a hyperlink to Web-based questionnaires. Up to three reminder emails were automatically issued after 5, 10, and 15 days of non-response.
At baseline, we collected demographic data including: age, gender, marital status, ethnicity, highest education level, employment status, postcode (from which we derived an Index of Multiple Deprivation [IMD]), health literacy (a single-item measure) [
At follow-up, participants in all treatment arms were asked to enter their current weight and whether they had followed any other weight loss programs over the last 8 weeks. Participants in both of the active treatment arms were also administered the Supportive Accountability Questionnaire [
All analyses were conducted in SPSS version 20. Means and standard deviations were computed for continuous variables, and “n” and percentage were computed for categorical variables. We used an alpha level of .05 for all statistical tests.
For the primary analysis, we planned to conduct independent
To examine our between-arm differences in self-reported weight loss, we used ANCOVA (analysis of covariance), with follow-up weight as a dependent variable, baseline weight as a covariate, and trial arm as the independent variable. We performed an intention-to-treat (ITT) analysis. Where weight at follow-up was missing, this was imputed using the “Multiple Imputation” procedure in SPSS. We performed 100 imputations using baseline variables and any available weight measurements as predictors. ANCOVA was performed and the pooled results from the multiple imputation reported. We also conducted a completers analysis by repeating another ANCOVA on the sample of participants who had completed follow-up measures. We also categorized participants according to whether or not they had lost at least 3 kg at 8-week follow-up. Such weight loss would correspond to approximately 0.4 kg (just under 1 lb) weight loss per week and would indicate a rate of weight loss in line with the POWeR program recommendations, which emphasize building healthy habits rather than rapid weight loss. We reported the percentage of participants in each arm meeting this criterion.
We produced descriptive statistics to summarize coaching uptake and used
The primary outcome, website usage, was successfully tracked for 100% of randomized participants. However, loss to follow-up was very high for the self-report measures. Full or partial self-report follow-up data at 8 weeks was provided by only 58.9% (162/275) of control, 15.2% (40/264) of POWeR only, and 21.5% (53/247) of POWeR plus coach participants. A total of 246 participants provided weight data at follow-up; 540 did not. Chi-square tests showed that missingness of weight data at 8 weeks was related to trial arm, with control participants more likely to provide data than participants in the two intervention arms. Looking within the two intervention arms, missingness was also related to website usage, with those having used POWeR the most (≥3 sessions) being more likely to provide follow-up data than those with lower usage (<3 sessions). Most baseline demographic, health, or weight-related variables were unrelated to missingness but participants who were older, less deprived, and university educated were more likely to provide follow-up data. All baseline variables, including those that were significantly associated with failure to provide follow-up data, were included as predictors in the multiple imputation model.
Flow of participants through the trial.
Participant characteristics.
Characteristic | Full sample (n=786) | Control (n=275) | POWeR only (n=264) | POWeR plus coaching (n=247) | |
Age in years, mean (SD) | 44.0 (12.7) | 44.2 (13.0) | 43.3 (12.5) | 44.4 (12.6) | |
Female gender, n (%) | 628 (79.9%) | 216 (78.5%) | 217 (82.5%) | 195 (78.9%) | |
White British ethnicity, n (%) | 760 (96.7%) | 265 (96.4%) | 253 (95.8%) | 242 (98.0%) | |
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Married | 444 (56.5%) | 154 (56.0%) | 147 (55.7%) | 143 (57.9%) |
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Living with partner | 120 (15.3%) | 41 (14.9%) | 37 (14.0%) | 42 (17.0%) |
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Single | 123 (15.6%) | 44 (16.0%) | 44 (16.7%) | 35 (14.2%) |
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Divorced or separated | 78 (9.9%) | 32 (11.7%) | 22 (8.4%) | 24 (9.7%) |
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Widowed | 15 (1.9%) | 2 (0.7%) | 10 (3.8%) | 3 (1.2%) |
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No formal | 42 (5.3%) | 16 (5.8%) | 11 (4.2%) | 15 (6.1%) |
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GCSEaor equivalent | 178 (22.6%) | 60 (21.8%) | 62 (23.5%) | 56 (22.7%) |
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A levels or equivalent | 110 (14.0%) | 35 (12.7%) | 39 (14.8%) | 36 (14.6%) |
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University (undergraduate or postgraduate) | 253 (32.2%) | 98 (35.7%) | 86 (32.6%) | 69 (27.9%) |
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Diploma / professional / vocational qualification | 197 (25.1%) | 64 (23.6%) | 63 (23.8%) | 69 (27.9%) |
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Full or part time employment / self-employment | 555 (70.6%) | 189 (68.6%) | 184 (69.8%) | 182 (73.6%) |
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Not working due to sickness or disability | 22 (2.8%) | 6 (2.2%) | 7 (2.7%) | 9 (3.6%) |
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Unemployed | 20 (2.5%) | 7 (2.5%) | 7 (2.7%) | 6 (2.4%) |
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Homemaker | 31 (3.9%) | 14 (5.1%) | 11 (4.2%) | 6 (2.4%) |
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Student | 65 (8.3%) | 21 (7.6%) | 26 (8.9%) | 18 (7.3%) |
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Retired | 75 (9.5%) | 33 (12.0%) | 21 (8.0%) | 21 (8.5%) |
IMDbscore (higher is more deprived), mean (SD) | 25.9 (15.3) | 25.2 (14.5) | 26.4 (15.5) | 26.0 (16.0) | |
Health literacy (1-5, higher is poorer literacy), mean (SD) | 1.1 (0.4) | 1.1 (0.4) | 1.1 (0.4) | 1.1 (0.4) | |
Internet usage (typical hours per week), mean (SD) | 13.0 (12.0) | 13.6 (13.6) | 13.0 (10.7) | 12.4 (11.5) | |
BMIc, mean (SD) | 33.0 (7.0) | 32.9 (6.8) | 33.1 (6.4) | 33.1 (7.8) | |
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Upper part of normal / healthy range (23-24.9) | 48 (6.1%) | 18 (6.5%) | 17 (6.4%) | 13 (5.3%) |
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Overweight (25-29.9) | 267 (34.0%) | 100 (36.4%) | 80 (30.3%) | 87 (35.2%) |
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Obese (30-39.9) | 353 (44.9%) | 111 (40.4%) | 128 (48.5%) | 114 (46.2%) |
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Morbidly obese (40+) | 118 (15.0%) | 46 (16.7%) | 39 (14.8%) | 33 (13.4%) |
Has one or more of the following health conditions (hypertension, diabetes, heart disease, asthma, stroke) | 276 (35.1%) | 96 (35.3%) | 85 (33.2%) | 95 (39.4%) | |
Ever advised to lose weight by a health professional | 417 (53.1%) | 150 (55.1%) | 141 (54.2%) | 126 (52.1%) | |
Ever referred to a weight management service / program by a health professional | 163 (20.7%) | 61 (22.3%) | 53 (20.5%) | 49 (20.6%) | |
Current / recent attempt to manage weight | 383 (48.7%) | 128 (46.5%) | 136 (51.5%) | 119 (48.2%) |
aGCSE: General Certificate of Secondary Education
bIMD: Index of Mass Deprivation score
cBMI: Body Mass Index
Website usage patterns were analyzed in the 511 participants allocated to the two active intervention arms. Overall, the number of POWeR sessions completed was low. The median number of sessions completed was 1 in both the POWeR only and the POWeR plus coaching arm (IQR 0-2 for POWeR only, IQR 0-3 for POWeR plus coaching). The data were positively skewed because around one-third of participants (94/264, 35.6% of POWeR only; 80/247, 32.4% of POWeR plus coaching) never completed a session and many participants completed only one or two sessions. Nonetheless, a substantial minority completed at least the core three sessions of POWeR (ie, the meaningful usage threshold) (
Usage of POWeR sessions.
Usage | POWeR only (n=264), |
POWeR plus coaching (n=247), |
Did not reach the meaningful usage threshold (<3 sessions) | 217 (82.2%) | 183 (74.1%) |
Reached the meaningful usage threshold (≥3 sessions) | 47 (17.8%) | 64 (25.9%) |
Weight data for the 246 follow-up completers is shown in (
Weight change by treatment arm (ITT analysis).
Weight | Control (n=275) | POWeR only (n=264) | POWeR plus coaching (n=247) |
Weight at baseline (kg), mean (SD) | 91.64 (20.31) | 92.02 (20.09) | 91.86 (20.96) |
Weight at follow-up (kg), mean (SD) | 91.34 (20.15) | 90.00 (19.89) | 89.59 (20.65) |
Weight change (kg), mean (SD) | −0.30 (2.82) | −2.01 (3.45) | −2.27 (3.41) |
Weight change by treatment arm (follow-up responders only).
Weight | Control (n=158) | POWeR only (n=39) | POWeR plus coaching (n=49) |
Weight at baseline (kg), mean (SD) | 91.85 (20.42) | 90.53 (16.86) | 94.80 (23.64) |
Weight at follow-up (kg), mean (SD) | 91.38 (20.47) | 87.67 (16.10) | 91.63 (23.17) |
Weight change (kg), mean (SD) | −0.41 (2.43) | −2.86 (4.42) | −3.17 (3.61) |
Percentage of participants self-reporting a weight loss of ≥3 kg at 8-week follow-up by treatment arm.
Overall, uptake of coaching calls was low. More than half (57.9%, 143/247) of those in the POWeR plus coaching arm actually received no coaching calls. Of the 104 participants that had coaching, most (n=58, 55.8%) had just one call. Only 46 participants (18.6%, 46/247) received both calls (ie, a full dose of coaching as per protocol). When coaching calls occurred, they tended to last for roughly 7.5 minutes each. The low rate of coaching calls can be partially explained by participant withdrawal, as 54 (21.9%, 54/247) POWeR plus coaching arm participants withdrew during the 8-week study period (see
Compared to POWeR plus coaching participants who did not receive full coaching, participants that had the full “dose” of coaching (ie, both calls) tended to be older (
Differences in usage, weight outcomes, and supportive accountability in the active treatment arms depending on whether full coaching was received.
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POWeR only n=264 | POWeR plus coaching n=247 | |
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Did not receive full coaching |
Received full coaching |
Number of weekly POWeR sessions completed, median (IQR) | 1 (0-2) | 1 (0-2) | 4 (2-6) |
Number of participants completing the 3 core POWeR sessions, n (%) | 47 (17.8%) | 37 (18.4%) | 27 (58.7%) |
Weight change (kg), mean (SD) | −0.80 (2.22) | −0.77 (1.78) | −2.79 (3.48) |
Participants achieving recommended amount of weight loss, ie, 3 kg or more,n (%) | 27 (10.2%) | 19 (9.5%) | 16 (34.8%) |
Supportive Accountability, mean (SD)a | 3.63 (1.30) | 3.72 (1.08) | 4.11 (0.94) |
aData based on responders to follow-up from both active treatment arms (n=40 in Web only, n=25 who received full coaching, and n=27 who did not receive full coaching).
In common with most studies of Web-based interventions [
Despite the overall pattern of light usage, in our secondary analyses of weight loss we showed that both of our intervention arms reported losing more weight than the control arm. Furthermore, a substantial minority of participants in the POWeR only and the POWeR plus coaching arm had high engagement with website sessions and reported losing clinically important amounts of weight (≥3 kg) at short-term follow-up. Hence, even though the effect sizes of the interventions were small overall, the impact at public health level could be considerable, given the low costs associated with entirely automated (POWeR only) or minimally-supported (POWeR plus coaching) Web-based interventions.
Encouragingly, our exploratory analyses tentatively indicated that the higher engagement seen in the POWeR plus coaching arm may have been associated with improved effectiveness of the Web-based intervention. Differences in weight loss between the POWeR only and the POWeR plus coaching arm were not significant overall, but substantial effect sizes were observed when comparing participants in the coaching arm who actually received both coaching phone calls to those who did not.
The impact of coaching on both usage and weight loss outcomes is likely to have been reduced by low uptake, as less than one in five participants in the coaching arm actually received both phone calls. The reasons for low uptake of coaching are not entirely clear. Some participants might have welcomed the opportunity for coaching but were unreachable by telephone when the calls were attempted—even though coaches made several attempts to contact participants and tried to accommodate their preferred contact times. However, some participants may have found the prospect of coaching off-putting. Indeed, the higher rate of withdrawal from the study observed in the coach arm compared to the website-only arm (n=54 vs n=10) might be taken as an indication that some participants disliked the prospect of coaching. Although most participants did not provide a reason for their withdrawal (typically they simply emailed “please withdraw me from the POWeR study”), we noted that most withdrawals happened shortly after allocation to the coach arm, or around the time participants were expecting the first coaching call. This raises the possibility that offering coaching may have multiple impacts: for some, it may boost usage but for others it might actually increase the likelihood of attrition. Whether certain groups of Web intervention users would be more comfortable with and responsive to human support if it was provided through different channels is an interesting question, requiring further study. It may be that there are groups of users who would cease using the intervention, whatever support was provided, and some who actually prefer to have no human contact and see the privacy and independence associated with Web-based interventions as a benefit.
A positive finding was that uptake of coaching calls was greatest among users who seemed particularly suitable candidates for weight management interventions (ie, more overweight, more likely to have hypertension, and to have been referred to a weight management program by a health professional). Future studies could build on this work to investigate further the users who are most likely to use and benefit from human support for Web interventions and how best to overcome barriers to uptake.
While the current study focused on a telephone-based form of human support, different approaches to boosting engagement have either capitalized on more recent technology or have emphasized peer support as an alternative to a health professional or coach. For example, Web-based health interventions have made use of email contact [
One of our study objectives was to explore whether coaching, based around the Supportive Accountability model [
A strength of this research is that our coaching protocols were well-documented, specific in their aims, and based on a theoretical model of engagement with digital interventions. Such explicit explanation of the aims and nature of human contact is rare in the reporting of Web-based interventions. Furthermore, the coach contact was brief (around 15 minutes for participants receiving the full dose) and delivered by providers with minimal training. This type of additional human support should be replicable in future studies and might prove feasible to implement and cost-effective for improving engagement and boosting intervention effectiveness even if effect sizes are modest.
The current study benefited from having primary outcome data available from all participants (by automatically tracking website usage), allowing this analysis to include all randomized participants. However, our pragmatic research design, which included minimal contact between researchers and participants and which probably attracted participants who were curious but not committed to following an online weight management program, may have contributed to the very high loss to follow-up for the secondary outcome data collected via self-reported questionnaires. Low follow-up rates are common in Web-based intervention trials, especially when research methodologies are more in line with a pragmatic trial than an efficacy trial. However, the large amount of missing data at follow-up limited statistical power and reduced our ability to draw firm conclusions about change and group differences in the self-reported follow-up data. Therefore, our secondary and exploratory analyses based on these measures need to be interpreted with caution.
Due to the large number and wide geographical dispersion of participants, only self-reported weight data could be obtained. Most Web-based weight loss trials have obtained objective weight data at face-to-face baseline and follow-up assessments [
This study chose to use the number of sessions completed as the indicator of participant engagement with the intervention. This has several advantages, including that it allowed us to obtain objective data unobtrusively for every participant and gave a reliable indication of the “dose” of the intervention that participants had been exposed to and which aspects they had seen. It is, however, not the only way to usefully investigate participant engagement and only gives a rudimentary picture of the extent to which participants were absorbing, understanding, and applying material presented on the Web pages. Future research may wish to use alternative ways of operationalizing engagement in order to investigate how deeply participants are engaging with intervention content. The challenge facing researchers, however, is how to measure engagement without relying on self-report follow-up data, which in many Web-based trials is unlikely to be provided by the majority of users.
In common with most Web-based intervention studies, usage of POWeR was suboptimal overall. Our findings suggest that supplementing Web-based weight management with brief human support might have a modest effect on persistence with the Web-based sessions, might improve weight loss outcomes, and could prove cost-effective. However, uptake of telephone support may be low overall, with particular types of users more likely to engage with it. Further research is needed to understand and optimize strategies to keep users engaged with Web-based weight interventions.
Screenshots from POWeR.
Coaching protocol.
CONSORT-EHEALTH checklist V1.6.2 [
analysis of covariance
body mass index
Index of Multiple of Deprivation
intention to treat
National Health Service
Positive Online Weight Reduction intervention
randomized controlled trial
This study was conducted with the support of a grant from the Engineering and Physical Sciences Research Council (EP/I032673/1, UBhave: ubiquitous and social computing for positive behaviour change). The authors would like to acknowledge the contribution of the Health Improvement Specialists: Claire Spence (Stockton-on-Tees Borough Council), Lindsay Johnson (Middlesbrough Council), and Carole Johnson (Hartlepool Borough Council), and thank the POWeR coaches (Ingrid Muller, Jeff Lambert, Rachel Ryves, Gülcan Garip, Jenny McSharry, Emily Smith, Rosie Essery, and Lisa McDermott).
None declared.