Scott Lloyd

Does Brief Telephone Support Improve Engagement With a Web-Based Weight Management Intervention? Randomized Controlled Trial

Background 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. Objective 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. Methods 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. Results 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 (F 2,782=12.421, P<.001). Both intervention groups reported more weight loss than the waiting list control group. Weight loss was slightly, but not significantly, greater in the POWeR plus coaching group. A large proportion of participants assigned to POWeR plus coaching refused phone calls or were not contactable (57.9%, 143/247). Exploratory analyses identified health and sociodemographic differences between those who did and did not engage in coaching when it was made available to them. Users who engaged with coaching used the intervention more and lost more weight than those who did not. Conclusions 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. Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN): 98176068; http://www.controlled-trials.com/ISRCTN98176068 (Archived by WebCite at http://www.webcitation.org/6OKRjM2oy).

Reasons for participating and not participating in a e-health workplace physical activity intervention

Purpose – The purpose of this paper is to investigate the reasons for participating and not participating in an e-health workplace physical activity (PA) intervention. Design/methodology/approach – Semi-structured interviews and two focus groups were conducted with a purposive sample of employees who enrolled and participated in the intervention and with those who did not complete enrolment, hence did not participate in it. Data were examined using thematic analysis according to the clusters of “reasons for participation” and for “non-participation”. Findings – Reported reasons for participation included a need to be more active, to increase motivation to engage in PA, and to better manage weight. Employees were attracted by the perceived ease of use of the programme and by the promise of receiving reminders. Many felt encouraged to enrol by managers or peers. Reported reasons for non-participation included lack of time, loss of interest towards the programme, or a lack of reminders to complete enrolment. Practical implications – Future e-health workplace behavioural interventions should consider focusing on employees’ needs and motivators to behaviour change, provide regular reminders for participants to complete enrolment and ensure that procedures are completed successfully. Barriers to participation could be identified through formative research with the target population and feasibility studies. Originality/value – This study combines a qualitative analysis of the reasons why some employees decided to enrol in a workplace PA intervention and why some others did not. This study highlights factors to consider when designing, implementing and promoting similar interventions and that could inform strategies to enhance participation in workplace PA interventions.

The effect of timing and frequency of push notifications on usage of a smartphone-based stress management intervention: An exploratory trial

Push notifications offer a promising strategy for enhancing engagement with smartphone-based health interventions. Intelligent sensor-driven machine learning models may improve the timeliness of notifications by adapting delivery to a user’s current context (e.g. location). This exploratory mixed-methods study examined the potential impact of timing and frequency on notification response and usage of Healthy Mind, a smartphone-based stress management intervention. 77 participants were randomised to use one of three versions of Healthy Mind that provided: intelligent notifications; daily notifications within pre-defined time frames; or occasional notifications within pre-defined time frames. Notification response and Healthy Mind usage were automatically recorded. Telephone interviews explored participants’ experiences of using Healthy Mind. Participants in the intelligent and daily conditions viewed (d = .47, .44 respectively) and actioned (d = .50, .43 respectively) more notifications compared to the occasional group. Notification group had no meaningful effects on percentage of notifications viewed or usage of Healthy Mind. No meaningful differences were indicated between the intelligent and non-intelligent groups. Our findings suggest that frequent notifications may encourage greater exposure to intervention content without deterring engagement, but adaptive tailoring of notification timing does not always enhance their use. Hypotheses generated from this study require testing in future work. Trial registration number: ISRCTN67177737

Effects of text messaging in addition to emails on physical activity among university and college employees in the UK

Objectives To test the effects of adding text messages to weekly email communications on recipients’ total physical activity (leisure-time; workplace; domestic and garden; and active transportation) in employees of universities and colleges in the UK. Methods A randomised trial with two study groups (email only or email plus text messaging for 12 weeks) was implemented at five workplaces. Data were collected at baseline, immediately after, and four weeks after the intervention. Intervention effects on physical activity were evaluated using latent growth modelling. Results Total physical activity decreased over time in both groups but the decrease was non-significant. The only significant difference between groups was found for workplace physical activity, with the group receiving emails and text messages having a linear decrease of 2.81 Metabolic Equivalent h/week (β = −0.31, p = 0.035) compared to the email only group. Conclusions Sending employees two additional text messages resulted in less physical activity. Further investigation is needed to understand whether text messaging may play a beneficial role in promoting physical activity in workplace settings.

Comparing usage of a web and app stress management intervention : an observational study.

Choices in the design and delivery of digital health behaviour interventions may have a direct influence on subsequent usage and engagement. Few studies have been able to make direct, detailed comparisons of differences in usage between interventions that are delivered via web or app. This study compared the usage of two versions of a digital stress management intervention, one delivered via a website (Healthy Paths) and the other delivered via an app (Healthy Mind). Design modifications were introduced within Healthy Mind to take account of reported differences in how individuals engage with websites compared to apps and mobile phones. Data were collected as part of an observational study nested within a broader exploratory trial of Healthy Mind. Objective usage of Healthy Paths and Healthy Mind were automatically recorded, including frequency and duration of logins, access to specific components within the intervention and order of page/screen visits. Usage was compared for a two week period following initial registration. In total, 381 participants completed the registration process for Healthy Paths (web) and 162 participants completed the registration process for Healthy Mind (app). App users logged in twice as often (Mdn = 2.00) as web users (Mdn = 1.00), U = 13,059.50, p ≤ 0.001, but spent half as much time (Mdn = 5.23 min) on the intervention compared to web users (Mdn = 10.52 min), U = 19,740.00, p ≤ 0.001. Visual exploration of usage patterns over time revealed that a significantly higher proportion of app users (n = 126, 82.35%) accessed both types of support available within the intervention (i.e. awareness and change-focused tools) compared to web users (n = 92, 40.17%), χ2(1, n = 382) = 66.60, p < 0.001. This study suggests that the digital platform used to deliver an intervention (i.e. web versus app) and specific design choices (e.g. navigation, length and volume of content) may be associated with differences in how the intervention content is used. Broad summative usage data (e.g. total time spent on the intervention) may mask important differences in how an intervention is used by different user groups if it is not complemented by more fine-grained analyses of usage patterns over time. Trial registration number: ISRCTN67177737.

Presentation 2: An individualised approach – MoveM8! E-mail and SMS physical activity communication in the workplace

Kinematic research into the golf swing has focused on significant differences based on handicap. Within these studies shot outcome has not been quantified or measured. The aim of this study was to determine whether kinematic and temporal differences exist, based on quality of shot, in skilled players.Physical activity promotion through activeThree-dimensional motions commonly models segments with six degrees of freedom (6 DOF) from which joint angles are determined. Implicitly it is assumed that, based on their position and orientations in the standing calibration, segments do not separate. However, marker movement artefacts and measurement error during tracking may lead to exaggerated motion about some of the degrees of freedom. Inverse kinematics (IK) is an alternative approach where joint constraints are explicitly defined and generalised coordinates required by the kinematic chain to achieve a desired pose are determined. The aim of this study was to compare lower limb joint kinematics during the golf swing using 6 DOF and IK models.