Understanding super engaged users in the 10,000 Steps online physical activity program: A qualitative study.

OBJECTIVE: Sustained engagement with Internet-based behavioural interventions is crucial to achieve successful behaviour change outcomes. As this has been problematic in many interventions, a lot of research has focused on participants with little or no engagement. However, few studies have attempted to understand users with continuous long-term engagement, the so called 'super engaged users', and why they keep on using programs when everybody else has long stopped. Therefore, the aim of this research was to qualitatively examine characteristics, usage profile and motivations of super engaged users in the 10,000 Steps program. METHODS: Twenty 10,000 Steps users (10 with more than 1 year of engagement, and 10 with more than 10 years of engagement) participated in semi-structured interviews, that were transcribed and thematically analysed. RESULTS: Participants were aged 60 years on average, with more than half being overweight/obese and/or suffering from chronic disease despite logging high step counts (219 million steps per participant on average) on the 10,000 Steps platform. Participants indicated that the reasons for sustained use were that engaging the program had become a habit, that the program kept them motivated, and that it was easy to use. Few participants had suggestions for improvement or expressed there were program elements they did not like. Uptake of program innovations (e.g., app-version, use of advanced activity tracker instead of pedometer) was modest among the super engaged users. CONCLUSION: The findings from this study emphasise the need for digital health programs to incorporate features that will support the development of habits as soon as participants start to engage with the program. While a program's usability, user-friendliness and acceptability are important to engage and retain new users, habit formation may be more important for sustained long-term engagement with the behaviour and the program.

The Association Between Logging Steps Using a Website, App, or Fitbit and Engaging With the 10,000 Steps Physical Activity Program: Observational Study.

BACKGROUND: Engagement is positively associated with the effectiveness of digital health interventions. It is unclear whether tracking devices that automatically synchronize data (eg, Fitbit) produce different engagement levels compared with manually entering data. OBJECTIVE: This study examines how different step logging methods in the freely available 10,000 Steps physical activity program differ according to age and gender and are associated with program engagement. METHODS: A subsample of users (n=22,142) of the free 10,000 Steps physical activity program were classified into one of the following user groups based on the step-logging method: Website Only (14,617/22,142, 66.01%), App Only (2100/22,142, 9.48%), Fitbit Only (1705/22,142, 7.7%), Web and App (2057/22,142, 9.29%), and Fitbit Combination (combination of web, app, and Fitbit; 1663/22,142, 7.51%). Generalized linear regression and binary logistic regression were used to examine differences between user groups' engagement and participation parameters. The time to nonusage attrition was assessed using Cox proportional hazards regression. RESULTS: App Only users were significantly younger and Fitbit user groups had higher proportions of women compared with other groups. The following outcomes were significant and relative to the Website Only group. The App Only group had fewer website sessions (odds ratio [OR] -6.9, 95% CI -7.6 to -6.2), whereas the Fitbit Only (OR 10.6, 95% CI 8.8-12.3), Web and App (OR 1.5, 95% CI 0.4-2.6), and Fitbit Combination (OR 8.0; 95% CI 6.2-9.7) groups had more sessions. The App Only (OR -0.7, 95% CI -0.9 to -0.4) and Fitbit Only (OR -0.5, 95% CI -0.7 to -0.2) groups spent fewer minutes on the website per session, whereas the Fitbit Combination group (OR 0.2, 95% CI 0.0-0.5) spent more minutes. All groups, except the Fitbit Combination group, viewed fewer website pages per session. The mean daily step count was lower for the App Only (OR -201.9, 95% CI -387.7 to -116.0) and Fitbit Only (OR -492.9, 95% CI -679.9 to -305.8) groups but higher for the Web and App group (OR 258.0, 95% CI 76.9-439.2). The Fitbit Only (OR 5.0, 95% CI 3.4-6.6), Web and App (OR 7.2, 95% CI 5.9-8.6), and Fitbit Combination (OR 15.6, 95% CI 13.7-17.5) groups logged a greater number of step entries. The App Only group was less likely (OR 0.65, 95% CI 0.46-0.94) and other groups were more likely to participate in Challenges. The mean time to nonusage attrition was 35 (SD 26) days and was lower than average in the Website Only and App Only groups and higher than average in the Web and App and Fitbit Combination groups. CONCLUSIONS: Using a Fitbit in combination with the 10,000 Steps app or website enhanced engagement with a real-world physical activity program. Integrating tracking devices that synchronize data automatically into real-world physical activity interventions is one strategy for improving engagement.

Impact of COVID-19 on Physical Activity Among 10,000 Steps Members and Engagement With the Program in Australia: Prospective Study.

BACKGROUND: Physical activity is an important health behavior, due to its association with many physical and mental health conditions. During distressing events, such as the COVID-19 pandemic, there is a concern that physical activity levels may be negatively impacted. However, recent studies have shown inconsistent results. Additionally, there is a lack of studies in Australia on this topic. OBJECTIVE: The aim of this study is to investigate changes in physical activity reported through the 10,000 Steps program and changes in engagement with the program during the COVID-19 pandemic. METHODS: Data between January 1, 2018, and June 30, 2020, from registered members of the 10,000 Steps program, which included 3,548,825 days with step data, were used. The number of daily steps were logged manually by the members or synced automatically from their activity trackers connected to the program. Measures on program usage were the number of new registered members per day, the number of newly registered organizations per day, the number of steps logged per day, and the number of step entries per day. Key dates used for comparison were as follows: the first case with symptoms in Wuhan, China; the first case reported in Australia; the implementation of a 14-day ban for noncitizens arriving in Australia from China; the start of the lockdown in Australia; and the relaxing of restrictions by the Australian Government. Wilcoxon signed-rank tests were used to test for significant differences in number of steps between subgroups, between engagement measures in 2019 versus 2020, and before and after an event. RESULTS: A decrease in steps was observed after the first case in Australia was reported (1.5%; P=.02) and after the start of the lockdown (3.4%; P<.001). At the time that the relaxing of restrictions started, the steps had already recovered from the lockdown. Additionally, the trends were consistent across genders and age groups. New South Wales, Australian Capital Territory, and Victoria had the greatest step reductions, with decreases of 7.0% (P<.001), 6.2% (P=.02), and 4.7% (P<.001), respectively. During the lockdown, the use of the program increased steeply. On the peak day, there were more than 9000 step entries per day, with nearly 100 million steps logged per day; in addition, more than 450 new users and more than 15 new organizations registered per day, although the numbers decreased quickly when restrictions were relaxed. On average per day, there were about 55 new registered users (P<.001), 2 new organizations (P<.001), 25.6 million steps (P<.001), and 2672 log entries (P<.001) more in 2020 compared to the same period in 2019. CONCLUSIONS: The pandemic has had negative effects on steps among Australians across age groups and genders. However, the effect was relatively small, with steps recovering quickly after the lockdown. There was a large increase in program usage during the pandemic, which might help minimize the health impact of the lockdown and confirms the important role of physical activity programs during times of distress and lockdowns.

Every Step Counts: Understanding the Success of Implementing The 10,000 Steps Project.

The 10,000 Steps program originated from a landmark whole-of-community multi-strategy intervention to increase physical activity (PA) in Rockhampton, Australia in 2001-2003. It used a social ecological framework to promote physical activity at the individual, population, environmental and policy level. Two of the fundamental aspects of the original program were goal setting (10,000 steps per day) and self-monitoring (use of a pedometer for daily step counts). A project website (www.10000steps.org.au) allowed registered participants to record their physical activity. Over time the program morphed into an e- & mHealth intervention without face-to-face elements. The program is now delivered via website and smartphone apps and employs activity trackers (pedometers, Fitbit, Garmin). To date the project has signed-up over 425,000 members who have logged 221 billion steps (∼43 million a day) on the website or app. More than 14,000 workplaces and community organisations have been involved with the program. A central element of the program, the 'Workplace Challenge' has been used by ∼65% of 10,000 Steps members, which on average increases physical activity by 159 min/week for those who participate in it. In 2011, the Queensland Government designated the 10,000 Steps program as their key physical activity workplace health promotion strategy. Multiple factors underpin the success of the program. The message is simple and clear: the project name, with its distinctive logo and tagline ('Every Step Counts') provides a clear and prescriptive target for the physical activity 'dose'. Using effective behaviour change techniques: goal setting (the 10,000 Steps concept), self-monitoring (steps are tracked), social support (participants organise as 'teams' to reach certain step goals) and gamification (teams competing against each other creating 'friendly competition'). Ongoing redevelopment: since inception, there have been three complete redesigns of the website (including a branding redesign), and new smartphone apps. More recently, the website was modified to allow syncing of steps using popular activity trackers. Resources to support implementation: the program provides resources (e.g. 'Active Workplace Guide') and has dedicated staff to respond to queries from workplaces and individuals to help overcome implementation barriers. Project staff continuously promote the program via media interviews, attendance at events, social media and marketing, advertising, and networking and collaboration. Ongoing evaluation has contributed to continuous funding: to ensure the program remains successful in a fast-changing technology environment, continuous evaluation has been necessary. These evaluation strategies, the success of the original project and the strong partnership with the program funder (Queensland Health) have all contributed to the long-term (19 years) support for the project.

Successes and Challenges of an IT-Based Health Behaviour Change Program to Increase Physical Activity.

Health behaviour change programs that utilise IT-based delivery have great potential to improve health. Whilst more static Web 1.0 technologies have been somewhat effective, they often failed to promote longer-term user engagement required for greater health promotion impact. With Web 2.0 technologies, however, there is potential for greater engagement and retention, through allowing individuals to determine how information is generated, modified, and shared collaboratively. The WALK 2.0 study utilised a Web 2.0-based platform to engage participants in health behaviour change aimed at increasing physical activity levels. The program included two trials: (1) a three-arm randomised controlled trial (RCT) that compared the effectiveness of Web 2.0, Web 1.0, and paper-based logbook interventions; and (2) a real-world randomised ecological trial (RET) that compared a Web 2.0 and Web 1.0 intervention. The aim of this paper is not to focus on the research trial results per se, but rather the success factors and challenges in both the RCT and RET. Both the RCT and RET demonstrated successful outcomes, with greater improvements in physical activity for the Web 2.0 groups. A range of challenges, however, were identified in designing, implementing, and evaluating such interventions. These include IT-based intervention development within a research context, the ability to establish a self-sustaining online community, the rapid pace of change in web-based technology and implications for trial design, the selection of best outcome measures for ecological trials, and managing engagement, non-usage and study attrition in real-world trials. Future research and developments in this area must look to broader research designs that allow for the ever-changing IT-user landscape and behaviour, and greater reliance on development and testing in real-world settings.

Impact of a Social Media Campaign on Reach, Uptake, and Engagement with a Free Web- and App-Based Physical Activity Intervention: The 10,000 Steps Australia Program.

Social media campaigns provide broad-reach and convenience for promoting freely-available health programs. However, their effectiveness and subsequent engagement of new users is unknown. This study aimed to assess the reach and new member registration rates resulting from a dedicated 10,000 Steps social media campaign (SMC) and to compare program engagement and time to non-usage attrition of new users from the SMC with other users. SMC reach (using Facebook, Instagram, and display advertisements engagement metrics), new-user numbers, engagement (usage of the website and its features), and time to non-usage attrition were assessed using generalized linear regression, binary logistic regression, and Cox proportion hazards regression models. During the SMC, Instagram and display advertisement impressions, Facebook reach and new daily registrations were significantly higher compared with six weeks and one year prior. There were no between-group differences in the average usage of most website/program features. Risk of non-usage attrition was higher among new users from the SMC than new users from one year prior. The SMC was effective in promoting awareness of the 10,000 Steps program. Further research to identify long-term engagement strategies and the most effective combination of social media platforms for promotion of, and recruitment to, health programs is warranted.

A RE-AIM Evaluation of a Workplace Physical Activity Microgrant Initiative: The 10,000 Steps Workplace Challenge.

OBJECTIVE: This study examines the reach, effectiveness, adoption, implementation, and maintenance of the 10,000 Steps Pedometer Microgrant Scheme using the RE-AIM framework. METHODS: The study used a mixed methods pre-post design. RE-AIM indicators were examined using employee surveys and workplace reports of microgrant implementation, adoption, and maintenance. RESULTS: A total of 259 microgrants and 21,211 pedometers were awarded (reach). Significant increases in physical activity were observed (P < 0.05) (effectiveness). Many (78%) workplaces reported using at least one challenge resource (adoption). Barriers were higher (26.5%) or lower (20.5%) than anticipated participation rates (implementation). Fifty percent of workplaces would continue to promote physical activity (maintenance). CONCLUSIONS: The microgrant reached a large number of employees and workplaces, increased physical activity, and achieved good levels of adoption and implementation. Employee and workplace levels of maintenance were mixed and need to be improved.

The effectiveness of a web 2.0 physical activity intervention in older adults - a randomised controlled trial.

BACKGROUND: Interactive web-based physical activity interventions using Web 2.0 features (e.g., social networking) have the potential to improve engagement and effectiveness compared to static Web 1.0 interventions. However, older adults may engage with Web 2.0 interventions differently than younger adults. The aims of this study were to determine whether an interaction between intervention (Web 2.0 and Web 1.0) and age group (<55y and ≥55y) exists for website usage and to determine whether an interaction between intervention (Web 2.0, Web 1.0 and logbook) and age group (<55y and ≥55y) exists for intervention effectiveness (changes in physical activity). METHODS: As part of the WALK 2.0 trial, 504 Australian adults were randomly assigned to receive either a paper logbook (n = 171), a Web 1.0 (n = 165) or a Web 2.0 (n = 168) physical activity intervention. Moderate to vigorous physical activity was measured using ActiGraph monitors at baseline 3, 12 and 18 months. Website usage statistics including time on site, number of log-ins and number of step entries were also recorded. Generalised linear and intention-to-treat linear mixed models were used to test interactions between intervention and age groups (<55y and ≥55y) for website usage and moderate to vigorous physical activity changes. RESULTS: Time on site was higher for the Web 2.0 compared to the Web 1.0 intervention from baseline to 3 months, and this difference was significantly greater in the older group (OR = 1.47, 95%CI = 1.01-2.14, p = .047). Participants in the Web 2.0 group increased their activity more than the logbook group at 3 months, and this difference was significantly greater in the older group (moderate to vigorous physical activity adjusted mean difference = 13.74, 95%CI = 1.08-26.40 min per day, p = .03). No intervention by age interactions were observed for Web 1.0 and logbook groups. CONCLUSIONS: Results partially support the use of Web 2.0 features to improve adults over 55 s' engagement in and behaviour changes from web-based physical activity interventions. TRIAL REGISTRATION: ACTRN ACTRN12611000157976 , Registered 7 March 2011.

Effectiveness of a Web 2.0 Intervention to Increase Physical Activity in Real-World Settings: Randomized Ecological Trial.

BACKGROUND: The translation of Web-based physical activity intervention research into the real world is lacking and becoming increasingly important. OBJECTIVE: To compare usage and effectiveness, in real-world settings, of a traditional Web 1.0 Web-based physical activity intervention, providing limited interactivity, to a Web 2.0 Web-based physical activity intervention that includes interactive features, such as social networking (ie, status updates, online "friends," and personalized profile pages), blogs, and Google Maps mash-ups. METHODS: Adults spontaneously signing up for the freely available 10,000 Steps website were randomized to the 10,000 Steps website (Web 1.0) or the newly developed WALK 2.0 website (Web 2.0). Physical activity (Active Australia Survey), quality of life (RAND 36), and body mass index (BMI) were assessed at baseline, 3 months, and 12 months. Website usage was measured continuously. Analyses of covariance were used to assess change over time in continuous outcome measures. Multiple imputation was used to deal with missing data. RESULTS: A total of 1328 participants completed baseline assessments. Only 3-month outcomes (224 completers) were analyzed due to high attrition at 12 months (77 completers). Web 2.0 group participants increased physical activity by 92.8 minutes per week more than those in the Web 1.0 group (95% CI 28.8-156.8; P=.005); their BMI values also decreased more (-1.03 kg/m2, 95% CI -1.65 to -0.41; P=.001). For quality of life, only the physical functioning domain score significantly improved more in the Web 2.0 group (3.6, 95% CI 1.7-5.5; P<.001). The time between the first and last visit to the website (3.57 vs 2.22 weeks; P<.001) and the mean number of days the website was visited (9.02 vs 5.71 days; P=.002) were significantly greater in the Web 2.0 group compared to the Web 1.0 group. The difference in time-to-nonusage attrition was not statistically significant between groups (Hazard Ratio=0.97, 95% CI 0.86-1.09; P=.59). Only 21.99% (292/1328) of participants (n=292 summed for both groups) were still using either website after 2 weeks and 6.55% (87/1328) were using either website after 10 weeks. CONCLUSIONS: The website that provided more interactive and social features was more effective in improving physical activity in real-world conditions. While the Web 2.0 website was visited significantly more, both groups nevertheless displayed high nonusage attrition and low intervention engagement. More research is needed to examine the external validity and generalizability of Web-based physical activity interventions. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12611000253909; https://anzctr.org.au /Trial/Registration/TrialReview.aspx?id=336588&isReview=true (Archived by WebCite at http://www.webcitation.org/6ufzw 2HxD).

Associations between quality of life and duration and frequency of physical activity and sedentary behaviour: Baseline findings from the WALK 2.0 randomised controlled trial.

While physical and mental health benefits of regular physical activity are well known, increasing evidence suggests that limiting sedentary behaviour is also important for health. Evidence shows associations of physical activity and sedentary behaviour with health-related quality of life (HRQoL), however, these findings are based predominantly on duration measures of physical activity and sedentary behaviour (e.g., minutes/week), with less attention on frequency measures (e.g., number of bouts). We examined the association of HRQoL with physical activity and sedentary behaviour, using both continuous duration (average daily minutes) and frequency (average daily bouts≥10 min) measures. Baseline data from the WALK 2.0 trial were analysed. WALK 2.0 is a randomised controlled trial investigating the effects of Web 2.0 applications on engagement, retention, and subsequent physical activity change. Daily physical activity and sedentary behaviour (duration = average minutes, frequency = average number of bouts ≥10 minutes) were measured (ActiGraph GT3X) across one week, and HRQoL was assessed with the 'general health' subscale of the RAND 36-Item Health Survey. Structural equation modelling was used to evaluate associations. Participants (N = 504) were 50.8±13.1 (mean±SD) years old with a BMI of 29.3±6.0. The 465 participants with valid accelerometer data engaged in an average of 24.0±18.3 minutes and 0.64±0.74 bouts of moderate-vigorous physical activity per day, 535.2±83.8 minutes and 17.0±3.4 bouts of sedentary behaviour per day, and reported moderate-high general HRQoL (64.5±20.0). After adjusting for covariates, the duration measures of physical activity (path correlation = 0.294, p<0.05) and sedentary behaviour were related to general HRQoL (path coefficient = -0.217, p<0.05). The frequency measure of physical activity was also significant (path coefficient = -0.226, p<0.05) but the frequency of sedentary behaviour was not significantly associated with general HRQoL. Higher duration levels of physical activity in fewer bouts, and lower duration of sedentary behaviour are associated with better general HRQoL. Further prospective studies are required to investigate these associations in different population groups over time.

Using Web 2.0 applications to promote health-related physical activity: findings from the WALK 2.0 randomised controlled trial.

BACKGROUND/AIM: Web 2.0 internet technology has great potential in promoting physical activity. This trial investigated the effectiveness of a Web 2.0-based intervention on physical activity behaviour, and the impact on website usage and engagement. METHODS: 504 (328 women, 126 men) insufficiently active adult participants were randomly allocated to one of two web-based interventions or a paper-based Logbook group. The Web 1.0 group participated in the existing 10 000 Steps programme, while the Web 2.0 group participated in a Web 2.0-enabled physical activity intervention including user-to-user interaction through social networking capabilities. ActiGraph GT3X activity monitors were used to assess physical activity at four points across the intervention (0, 3, 12 and 18 months), and usage and engagement were assessed continuously through website usage statistics. RESULTS: Treatment groups differed significantly in trajectories of minutes/day of physical activity (p=0.0198), through a greater change at 3 months for Web 2.0 than Web 1.0 (7.3 min/day, 95% CI 2.4 to 12.3). In the Web 2.0 group, physical activity increased at 3 (mean change 6.8 min/day, 95% CI 3.9 to 9.6) and 12 months (3.8 min/day, 95% CI 0.5 to 7.0), but not 18 months. The Logbook group also increased physical activity at 3 (4.8 min/day, 95% CI 1.8 to 7.7) and 12 months (4.9 min/day, 95% CI 0.7 to 9.1), but not 18 months. The Web 1.0 group increased physical activity at 12 months only (4.9 min/day, 95% CI 0.5 to 9.3). The Web 2.0 group demonstrated higher levels of website engagement (p=0.3964). CONCLUSIONS: In comparison to a Web 1.0 intervention, a more interactive Web 2.0 intervention, as well as the paper-based Logbook intervention, improved physical activity in the short term, but that effect reduced over time, despite higher levels of engagement of the Web 2.0 group. TRIAL REGISTRATION NUMBER: ACTRN12611000157976.

What is the impact of obtaining medical clearance to participate in a randomised controlled trial examining a physical activity intervention on the socio-demographic and risk factor profiles of included participants?

BACKGROUND: Requiring individuals to obtain medical clearance to exercise prior to participation in physical activity interventions is common. The impact this has on the socio-demographic characteristic profiles of participants who end up participating in the intervention is not clear. METHODS: As part of the multi-component eligibility screening for inclusion in a three-arm randomised controlled trial examining the efficacy of a web-based physical activity intervention, individuals interested in participating were required to complete the Physical Activity Readiness Questionnaire (PAR-Q). The PAR-Q identified individuals as having lower or higher risk. Higher-risk individuals were required to obtain medical exercise clearance prior to enrolment. Comparisons of the socio-demographic characteristics of the lower- and higher-risk individuals were performed using t tests and chi-square tests (p = 0.05). RESULTS: A total of 1244 individuals expressed interest in participating, and 432 were enrolled without needing to undergo further screening. Of the 251 individuals required to obtain medical clearance, 148 received clearance, 15 did not receive clearance and 88 did not return any form of clearance. A total of 105 individuals were enrolled after obtaining clearance, and the most frequent reason for being required to seek clearance was for using blood pressure/heart condition medication. Higher-risk individuals were significantly older, had a higher body mass index and engaged in more sedentary behaviour than lower-risk individuals. CONCLUSIONS: Use of more inclusive participant screening protocols that maintain high levels of participant safety are encouraged. Allowing individuals to obtain medical clearance to participate can result in including a more diverse population likely to benefit most from participation. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ( ACTRN12611000157976 ). Registered on 9 February 2011.

Recruitment, screening, and baseline participant characteristics in the WALK 2.0 study: A randomized controlled trial using web 2.0 applications to promote physical activity.

OBJECTIVE: To describe in detail the recruitment methods and enrollment rates, the screening methods, and the baseline characteristics of a sample of adults participating in the Walk 2.0 Study, an 18 month, 3-arm randomized controlled trial of a Web 2.0 based physical activity intervention. METHODS: A two-fold recruitment plan was developed and implemented, including a direct mail-out to an extract from the Australian Electoral Commission electoral roll, and other supplementary methods including email and telephone. Physical activity screening involved two steps: a validated single-item self-report instrument and the follow-up Active Australia Questionnaire. Readiness for physical activity participation was also based on a two-step process of administering the Physical Activity Readiness Questionnaire and, where needed, further clearance from a medical practitioner. RESULTS: Across all recruitment methods, a total of 1244 participants expressed interest in participating, of which 656 were deemed eligible. Of these, 504 were later enrolled in the Walk 2.0 trial (77% enrollment rate) and randomized to the Walk 1.0 group (n = 165), the Walk 2.0 group (n = 168), or the Logbook group (n = 171). Mean age of the total sample was 50.8 years, with 65.2% female and 79.1% born in Australia. CONCLUSION: The results of this recruitment process demonstrate the successful use of multiple strategies to obtain a diverse sample of adults eligible to take part in a web-based physical activity promotion intervention. The use of dual screening processes ensured safe participation in the intervention. This approach to recruitment and physical activity screening can be used as a model for further trials in this area.

Physical activity screening to recruit inactive randomized controlled trial participants: how much is too much?

UNLABELLED: Screening physical activity levels is common in trials to increase physical activity in inactive populations. Commonly applied single-item screening tools might not always be effective in identifying those who are inactive. We applied the more extensive Active Australia Survey to identify inactive people among those who had initially been misclassified as too active using a single-item measure. Those enrolled after the Active Australia Survey screening had significantly higher physical activity levels at subsequent baseline assessment. Thus, more extensive screening measures might result in the inclusion of participants who would otherwise be excluded, possibly introducing unwanted bias. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN12611000157976.

Assessing user engagement in a health promotion website using social networking.

Remote provision of supportive mechanisms for preventive health is a fast-growing area in eHealth. Web-based interventions have been suggested as an effective way to increase adoption and maintenance of healthy lifestyle behaviours. This paper describes results obtained in the "Walk 2.0" trial to promote physical activity through a self-managed walking programme, using a social networking website that provided an online collaborative environment. Engagement of participants with the website was assessed by monitoring usage of the individual social networking functions (e.g. status post). The results demonstrate that users generally preferred contributing non-interactive public posts of information concerned with their individual physical activity levels, and more occasionally communicating privately to friends. Further analysis of topics within posts was done by classifying word usage frequencies. Results indicated that the dominant topics are well aligned with the social environment within which physical activity takes place. Topics centred around four main areas: description of the activity, timing of the activity, affective response to the activity, and context within which the activity occurs. These findings suggest that strong levels of user awareness and communication occur in the social networking setting, indicative of beneficial self-image and self-actualisation effects.

WALK 2.0: examining the effectiveness of Web 2.0 features to increase physical activity in a 'real world' setting: an ecological trial.

INTRODUCTION: Low levels of health-enhancing physical activity require novel approaches that have the potential to reach broad populations. Web-based interventions are a popular approach for behaviour change given their wide reach and accessibility. However, challenges with participant engagement and retention reduce the long-term maintenance of behaviour change. Web 2.0 features present a new and innovative online environment supporting greater interactivity, with the potential to increase engagement and retention. In order to understand the applicability of these innovative interventions for the broader population, 'real-world' interventions implemented under 'everyday conditions' are required. The aim of this study is to investigate the difference in physical activity behaviour between individuals using a traditional Web 1.0 website with those using a novel Web 2.0 website. METHODS AND ANALYSIS: In this study we will aim to recruit 2894 participants. Participants will be recruited from individuals who register with a pre-existing health promotion website that currently provides Web 1.0 features (http://www.10000steps.org.au). Eligible participants who provide informed consent will be randomly assigned to one of the two trial conditions: the pre-existing 10 000 Steps website (with Web 1.0 features) or the newly developed WALK 2.0 website (with Web 2.0 features). Primary and secondary outcome measures will be assessed by self-report at baseline, 3 months and 12 months, and include: physical activity behaviour, height and weight, Internet self-efficacy, website usability, website usage and quality of life. ETHICS AND DISSEMINATION: This study has received ethics approval from the University of Western Sydney Human Research Ethics Committee (Reference Number H8767) and has been funded by the National Health and Medical Research Council (Reference Number 589903). Study findings will be disseminated widely through peer-reviewed publications, academic conferences and local community-based presentations. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry Number: ACTRN12611000253909, WHO Universal Trial Number: U111-1119-1755.

A pilot study of the feasibility of an Internet-based electronic Outpatient Cardiac Rehabilitation (eOCR) program in rural primary care.

BACKGROUND: Interventions that facilitate access to cardiac rehabilitation and secondary prevention programs are in demand. METHODS: This pilot study used a mixed methods design to evaluate the feasibility of an Internet-based, electronic Outpatient Cardiac Rehabilitation (eOCR). Patients who had suffered a cardiac event and their case managers were recruited from rural primary practices. Feasibility was evaluated in terms of the number of patients enrolled and patient and case manager engagement with the eOCR website. RESULTS: Four rural general practices, 16 health professionals (cardiologists, general practitioners, nurses and allied health) and 24 patients participated in the project and 11 (46%) completed the program. Utilisation of the website during the 105 day evaluation period by participating health professionals was moderate to low (mean of 8.25 logins, range 0-28 logins). The mean login rate for patients was 16 (range 1-77 logins), mean time from first login to last (days using the website) was 51 (range 1-105 days). Each patient monitored at least five risk factors and read at least one of the secondary prevention articles. There was low utilisation of other tools such as weekly workbooks and discussion boards. CONCLUSIONS: It was important to evaluate how an eOCR website would be used within an existing healthcare setting. These results will help to guide the implementation of future internet based cardiac rehabilitation programs considering barriers such as access and appropriate target groups of participants.

Prospective associations between intervention components and website engagement in a publicly available physical activity website: the case of 10,000 Steps Australia.

BACKGROUND: Effectiveness of and engagement with website-delivered physical activity interventions is moderate at best. Increased exposure to Internet interventions is reported to increase their effectiveness; however, there is a lack of knowledge about which specific intervention elements are able to maintain website engagement. OBJECTIVE: To prospectively study the associations of website engagement and exposure to intervention components for a publicly available physical activity website (10,000 Steps Australia). METHODS: Between June and July 2006 a total of 348 members of 10,000 Steps completed a Web-based survey to collect demographic characteristics. Website engagement was subsequently assessed over a 2-year period and included engagement data on website components; individual challenges, team challenges, and virtual walking buddies; and indicators of website engagement (average steps logged, days logging steps, and active users). RESULTS: On average participants logged steps on 169 (SD 228.25) days. Over a 2-year period this equated to an average of 1.6 logons per week. Binary logistic regression showed that individuals who participated in individual challenges were more likely to achieve an average of 10,000 steps per day (odds ratio [OR] = 2.80, 95% confidence interval [CI] 1.45-5.40), log steps on a higher than average number of days (OR = 6.81, 95% CI 2.87-13.31), and remain an active user (OR = 4.36, 95% CI 2.17-8.71). Additionally, those using virtual walking buddies (OR = 5.83, 95% CI 1.27-26.80) and of older age logged steps on a higher than average number of days. No significant associations were found for team challenges. CONCLUSIONS: Overall engagement with the 10,000 Steps website was high, and the results demonstrate the relative effectiveness of interactive components to enhance website engagement. However, only exposure to the interactive individual challenge feature was positively associated with all website engagement indicators. More research is needed to examine the influence of intervention components on website engagement, as well as the relationship between website engagement and physical activity change.

The development of an internet-based outpatient cardiac rehabilitation intervention: a Delphi study.

BACKGROUND: Face-to-face outpatient cardiac rehabilitation (OCR) programs are an important and effective component in the management of cardiovascular disease. However, these programs have low participation rates, especially among patients who live rural or remote. Hence, there is a need to develop OCR programs that provide an alternative to face-to-face contact such as by using the Internet. Only a very limited number of Internet-based OCR programs have been developed and evaluated. Therefore, the purpose of this study was to identify issues that are relevant to the development of an Internet-based OCR intervention. METHODS: A three-round Delphi study among cardiac rehabilitation experts was conducted. In the first round, 43 experts outlined opinions they had on the development of an online ORC platform into an open-ended electronic questionnaire. In the second round, 42 experts completed a structured (five-point scale) electronic questionnaire based on first round results, in which they scored items on their relevance. In the third round, the same experts were asked to re-rate the same items after feedback was given about the group median relevance score to establish a level of consensus. RESULTS: After the third round, high consensus was reached in 120 of 162 (74%) questionnaire items, of which 93 (57% of 162 items) also had high relevance according to the experts. The results indicate that experts strongly agreed on desired website content, data obtained from the patient, and level of interaction with patients that should be part of an Internet-based OCR intervention. CONCLUSION: The high rates of consensus and relevance observed among cardiac rehabilitation experts are an indication that they perceived the development and implementation of an Internet-based ORC intervention as feasible, and as a valuable alternative to face-to-face programs. In many ways the experts indicated that an Internet-based ORC program should mimic a traditional face-to-face program, and emphasize the crucial role of the cardiac rehabilitation manager who interacts with patients from a distance. The present study revealed practical insights into how Internet OCR interventions should be designed and opens the door for the development of such an intervention to be subsequently examined in a longitudinal and experimental study.