The effect of neighborhood walkability on changes in physical activity and sedentary behavior during a 12-week pedometer-facilitated intervention.

BACKGROUND: Pedometer-facilitated interventions encourage physical activity via the accumulation of steps. Mixed evidence suggests that neighborhood walkability might influence the effectiveness of physical activity interventions, including pedometer-facilitated interventions. Our study investigated the moderating effect of neighborhood walkability on immediate (4-week) and short-term (12-week) changes in self-reported neighborhood-specific leisure and transportation walking, leisure-based moderate and vigorous-intensity physical activity, and leisure-based screen time during a pedometer-facilitated intervention (UWALK). METHODS: This quasi-experiment undertaken in Calgary (Canada) compared behavior changes during the 12-week intervention between two neighborhood groups classified as 'walkable' or 'car dependent' based on Walk Score®. Of the 573 volunteers (adults in the contemplation and preparation stages of physical activity behavior change), 466 participated in UWALK. Surveys captured sociodemographic characteristics, perceived neighborhood walkability, neighborhood preferences, motivation, physical activity and screen-based leisure. Covariate-adjusted linear mixed models estimated the differences in physical activity and leisure screen time between the neighborhood walkability groups at baseline, 4-weeks, and 12-weeks. RESULTS: UWALK participants included mostly females (83%) and had an average age of 49.2 years. Weekly minutes of walking for transport inside the neighborhood was higher (p < .001) among participants from walkable versus car dependent neighborhoods at baseline (42.5 vs. 21.1), 4-weeks (81.2 vs. 48.2), and 12-weeks (87.2 vs. 48.0). Regardless of neighborhood walkability, all physical activity outcomes were higher and leisure screen time lower at 4-weeks and 12-weeks compared with baseline. We found no significant neighborhood group by time interactions. CONCLUSIONS: Pedometer-facilitated interventions may be effective for supporting short-term changes in physical activity and sedentary behavior even among adults residing in low walkable neighborhoods.

Acceptability, usefulness, and satisfaction with a web-based video-tailored physical activity intervention: The TaylorActive randomized controlled trial.

PURPOSE: This study aimed to examine the usage, acceptability, usability, perceived usefulness, and satisfaction of a web-based video-tailored physical activity (PA) intervention (TaylorActive) in adults. METHODS: In 2013-2014, 501 Australian adults aged 18+ years were randomized into a video-tailored intervention, text-tailored intervention, or control group. Over 3 months, the intervention groups received access to 8 sessions of personally tailored PA advice delivered via the TaylorActive website. Only the delivery method differed between the intervention groups: video-tailored vs. text-tailored. Google Analytics and telephone surveys conducted at post intervention (3 months) were used to assess intervention usage, acceptability, usability, perceived usefulness, and satisfaction. Quantitative and qualitative process data were analyzed using descriptive statistics and thematic content analysis. RESULTS: Of 501 recruited adults, 259 completed the 3-month post-intervention survey (52% retention). Overall, usage of the TaylorActive website with respect to number of website visits, intervention sessions, and action plans completed was modest in both the video-tailored (7.6 ± 7.2 visits, mean ± SD) and text-tailored (7.3 ± 5.4 visits) groups with no significant between-group differences. The majority of participants in all groups used the TaylorActive website less than once in 2 weeks (66.7% video-tailored, 62.7% text-tailored, 87.5% control; p < 0.001). Acceptability was rated mostly high in all groups and, in some instances, significantly higher in the intervention groups compared to the control group (p < 0.010). Usability was also rated high; mean Systems Usability Scores were 77.3 (video-tailored), 75.7 (text-tailored), and 74.1 (control) with no significant between-group differences. Perceived usefulness of the TaylorActive intervention was low, though mostly rated higher in the intervention groups compared to the control group (p < 0.010). Satisfaction with the TaylorActive website was mixed. Participants in both intervention groups liked its ease of use, personalized feedback, and tracking of progress, but also found completing action plans and survey questions for each session repetitive and tedious. CONCLUSION: Providing personally tailored PA advice on its own (through either video or text) is likely insufficient to ensure good retention, usage, perceived usefulness, and satisfaction with a web-based PA intervention. Strategies to address this may include the incorporation of additional intervention components such as activity trackers, social interactions, gamification, as well as the use of advanced artificial intelligence and machine learning technologies to allow more personalized dialogue with participants.

Determinants of physical activity among adults in the United Kingdom during the COVID-19 pandemic: The DUK-COVID study.

Objectives This study examined the impact of the COVID-19 lockdown on the physical activity (PA) of UK adults and potential motivational determinants of such behaviour. Design and methods A survey was conducted with 1,521 UK adults recruited through Prolific.co in early June 2020. Along with demographic information, questions assessed current PA, changes in PA modalities (i.e., overall, around the home, for transport, in the workplace, in the local neighbourhood, at recreation/sport facilities) related to the lockdown, and beliefs about capabilities, opportunities, and motivations according to the COM-B model. A series of logistic regressions were constructed to examine associations between shifts in the PA modalities and the COM-B components. Results The majority of respondents (57%) had either maintained or increased their levels of PA during the COVID-19 lockdown. However, the proportion meeting PA guidelines (31%) was low and engagement in sedentary-related behaviour for both work and leisure increased substantially during the lockdown. The components of the COM-B model were associated with shifts in PA. In particular, physical opportunity (odds ratios ranging from 1.14 to 1.20) and reflective motivation (odds ratios ranging from 1.11 to 1.25) appeared to be the most consistent predictors of behaviour. Conclusions If UK adults believed they had the physical opportunity and were motivated, they were more likely to have maintained or increased their PA during the COVID-19 lockdown. However, the majority of adults are not meeting the UK guidelines on PA and the prevalence of PA is substantially lower than national surveys prior to the pandemic. Statement of contribution What is already known on this subject? The COVID-19 pandemic has significantly disrupted the daily routines of citizens globally. Engagement in physical activity appears to have declined as a result of the requirement to self-isolate and stay in place. The COM-B model of behaviour change is a useful framework for identifying the correlates and determinants of behaviour. What does this study add? Though most UK adults maintained or increased their engagement in physical activity during the COVID-19 pandemic, the majority did not meet recommended guidelines. Reflective processes and physical opportunity were the primary predictors of change in physical activity.

Are web-based personally tailored physical activity videos more effective than personally tailored text-based interventions? Results from the three-arm randomised controlled TaylorActive trial.

OBJECTIVES: Some online, personally tailored, text-based physical activity interventions have proven effective. However, people tend to 'skim' and 'scan' web-based text rather than thoroughly read their contents. In contrast, online videos are more engaging and popular. We examined whether web-based personally tailored physical activity videos were more effective in promoting physical activity than personally tailored text and generic information. METHODS: 501 adults were randomised into a video-tailored intervention, text-tailored intervention or control. Over a 3-month period, intervention groups received access to eight sessions of web-based personally tailored physical activity advice. Only the delivery method differed between intervention groups: tailored video versus tailored text. The primary outcome was 7-day ActiGraph-GT3X+ measured moderate-to-vigorous physical activity (MVPA) assessed at 0, 3 and 9 months. Secondary outcomes included self-reported MVPA and website engagement. Differences were examined using generalised linear mixed models with intention-to-treat and multiple imputation. RESULTS: Accelerometer-assessed MVPA increased 23% in the control (1.23 (1.06, 1.43)), 12% in the text-tailored (1.12 (0.95, 1.32)) and 28% in the video-tailored (1.28 (1.06, 1.53)) groups at the 3-month follow-up only, though there were no significant between-group differences. Both text-tailored (1.77 (1.37, 2.28]) and video-tailored (1.37 (1.04, 1.79)) groups significantly increased self-reported MVPA more than the control group at 3 months only, but there were no differences between video-tailored and text-tailored groups. The video-tailored group spent significantly more time on the website compared with text-tailored participants (90 vs 77 min, p=0.02). CONCLUSIONS: The personally tailored videos were not more effective than personally tailored text in increasing MVPA. The findings from this study conflict with pilot study outcomes and previous literature. Process evaluation and mediation analyses will provide further insights. TRIAL REGISTRATION NUMBER: ACTRN12615000057583.

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.

Validity and responsiveness to change of the Active Australia Survey according to gender, age, BMI, education, and physical activity level and awareness.

BACKGROUND: This study aimed to investigate the validity of the Active Australia Survey across different subgroups and its responsiveness to change, as few previous studies have examined this. METHODS: The Active Australia Survey was validated against the ActiGraph as an objective measure of physical activity. Participants (n = 465) wore the ActiGraph for 7 days and subsequently completed the Active Australia Survey. Moderate activity, vigorous activity and total moderate and vigorous physical activity were compared using Spearman rank-order correlations. Changes in physical activity between baseline and 3-month assessments were correlated to examine responsiveness to change. The data were stratified to assess outcomes according to different subgroups (e.g., gender, age, weight, activity levels). RESULTS: With regards to the validity, a significant correlation of ρ = 0.19 was found for moderate physical activity, ρ = 0.33 for vigorous physical activity and ρ = 0.23 for moderate and vigorous physical activity combined. For vigorous physical activity correlations were higher than 0.3 for most subgroups, whereas they were only higher than 0.3 in those with a healthy weight for the other activity outcomes. With regards to responsiveness to change, a correlation of ρ = 0.32 was found for moderate physical activity, ρ = 0.19 for vigorous physical activity and ρ = 0.35 for moderate and vigorous physical activity combined. For moderate and vigorous activity combined correlations were higher than 0.4 for several subgroups, but never for vigorous physical activity. CONCLUSIONS: Little evidence for the validity of Active Australia Survey was found, although the responsiveness to change was acceptable for several subgroups. Findings from studies using the Active Australia Survey should be interpreted with caution. TRIAL REGISTRATION: World Health Organisation Universal Trial Number: U111-1119-1755. Australian New Zealand Clinical Trials Registry, ACTRN12611000157976 . Registration date: 8 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.

UWALK: the development of a multi-strategy, community-wide physical activity program.

UWALK is a multi-strategy, multi-sector, theory-informed, community-wide approach using e and mHealth to promote physical activity in Alberta, Canada. The aim of UWALK is to promote physical activity, primarily via the accumulation of steps and flights of stairs, through a single over-arching brand. This paper describes the development of the UWALK program. A social ecological model and the social cognitive theory guided the development of key strategies, including the marketing and communication activities, establishing partnerships with key stakeholders, and e and mHealth programs. The program promotes the use of physical activity monitoring devices to self-monitor physical activity. This includes pedometers, electronic devices, and smartphone applications. In addition to entering physical activity data manually, the e and mHealth program provides the function for objective data to be automatically uploaded from select electronic devices (Fitbit®, Garmin and the smartphone application Moves) The RE-AIM framework is used to guide the evaluation of UWALK. Funding for the program commenced in February 2013. The UWALK brand was introduced on April 12, 2013 with the official launch, including the UWALK website on September 20, 2013. This paper describes the development and evaluation framework of a physical activity promotion program. This program has the potential for population level dissemination and uptake of an ecologically valid physical activity promotion program that is evidence-based and theoretically framed.

A pilot study on the motivational effects of an internet-delivered physical activity behaviour change programme in Nova Scotian cancer survivors.

OBJECTIVE: To examine the effects of an internet-delivered, distance-based physical activity (PA) behaviour change programme on motivation to perform PA in cancer survivors. DESIGN: Breast, prostate and colorectal cancer survivors (N = 95) were randomized to either an online Theory of Planned Behaviour (TPB)-based PA behaviour change programme (UCAN) or usual care. MAIN OUTCOME MEASURES: Motivational variables from the TPB including intention, planning, attitude, subjective norm, perceived behavioural control and underlying beliefs. RESULTS: UCAN had significant negative effects on self-efficacy (-.7; 95% CI = -1.2 to -.1; d = -.53, p = .019), affective attitude (-.4; 95% CI = -.8 to -.0; d = -.45, p = .044), instrumental attitude (-.5; 95% CI = -.9 to -.1; d = -.43, p = .026) and confidence to perform PA in bad weather (-.8; 95% CI = -1.6 to -.1; d = -.49, p = .030), despite health issues (-.7; 95% CI = -1.3 to -.1; d = -.48, p = .031), despite pain/soreness (-.7; 95% CI = -1.4 to -.1; d = -.52, p = .020), despite family responsibilities (-1.0; 95% CI = -1.7 to -.3; d = -.62, p = .005) and when PA is boring (-.8; 95% CI = -1.4 to -.1; d = -.54, p = .016). CONCLUSION: UCAN had negative effects on motivational variables in cancer survivors. These findings may be explained by methodological issues related to measuring motivation and/or the absence of post-intentional constructs.

A Systematic Review of Interventions to Increase Stair Use.

CONTEXT: Stair climbing is an accessible activity that can be incorporated into one's daily lifestyle to increase physical activity levels and provide health benefits. This review summarizes the effectiveness of stair interventions and explores key differences that may influence intervention effectiveness. EVIDENCE ACQUISITION: Interventions to increase stair use published from January 1990 to July 2015 were identified in PubMed, Sport Discus, Web of Science, Environment Complete, CINAHL, Trial Register of Promoting Health Interventions, Embase, Scopus, and PsycINFO. Eligibility criteria included original studies, published in peer-reviewed journals, targeting adult samples, and clearly describing intervention design and results. Studies were also required to measure the use of stairs compared with an elevator, escalator, or moving stairway at baseline and during at least one timepoint when the intervention was in effect. Studies were required to provide data to determine if the intervention resulted in significant changes in stair use/climbing. EVIDENCE SYNTHESIS: The search results yielded 2,136 articles in total; 54 articles met the criteria, which resulted in a final sample of 67 studies included in the analyses. Interventions settings included public sites (75%), worksites (21%), or a combination of both (4%). For Phase 1 results, 72% of studies reported significant improvements in stair use (n=10 of 14) and stair climbing (n=38 of 53). CONCLUSIONS: Evidence from the review demonstrates support for the effectiveness of interventions to increase stair use and stair climbing. Although evidence supports the effectiveness of stair interventions in public settings, less support is provided for worksites.

Dog ownership and physical activity among breast, prostate, and colorectal cancer survivors.

BACKGROUND: Dog ownership has been associated with higher rates of physical activity (PA) in several populations but no study to date has focused on cancer survivors. The purpose of this study was to examine the associations between dog ownership and PA among cancer survivors and to examine correlates of dog ownership. METHODS: A stratified random sample of 2062 breast cancer survivors, prostate cancer survivors, and colorectal cancer survivors was mailed a questionnaire assessing PA, social cognitive, dog ownership, demographic, and medical variables. RESULTS: Overall, 25% of the sample was dog owners (DOs). There were no significant differences in moderate, vigorous, or total PA minutes between DOs and non-dog owners. There was a significant difference in light PA minutes in favor of DOs (153 vs 112 minutes; 95% CI = 4 to 77; P = .030), however, this was largely restricted to breast cancer survivors (143 vs 79 minutes; 95% CI = 25 to 102; P = .001) who also reported fewer vigorous PA minutes (18 vs 39 minutes; 95% CI = -42 to -1; P = .042). Survivors were more likely to be DOs if they had breast cancer (P = .054), a higher income (P = .021), radiation therapy (P = .029), chemotherapy (P = .010), were younger (P < .001), employed (P < .001), and a current smoker (P = .015). Few social cognitive variables were associated with DO. CONCLUSIONS: Dog ownership among cancer survivors was not associated with moderate-to-vigorous PA but was associated with light PA. Further research is necessary to determine if promoting dog ownership and dog walking among cancer survivors may increase PA and possibly improve health outcomes.

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.

Examining an Australian physical activity and nutrition intervention using RE-AIM.

Translating evidence-based interventions into community practice is vital to health promotion. This study used the RE-AIM framework to evaluate the larger dissemination of the ManUp intervention, an intervention which utilized interactive web-based technologies to improve the physical activity and nutrition behaviors of residents in Central Queensland, Australia. Data were collected for each RE-AIM measure (Reach, Effectiveness, Adoption, Implementation, Maintenance) using (i) computer-assisted telephone interview survey (N = 312) with adults (18 years and over) from Central Queensland, (ii) interviews with key stakeholders from local organizations (n = 12) and (iii) examination of project-related statistics and findings. In terms of Reach, 47% of participants were aware of the intervention; Effectiveness, there were no significant differences between physical activity and healthy nutrition levels in those aware and unaware; Adoption, 73 participants registered for the intervention and 25% of organizations adopted some part of the intervention; Implementation, 26% of participants initially logged onto the website, 29 and 17% started the web-based physical activity and nutrition challenges, 33% of organizations implemented the intervention, 42% considered implementation and 25% reported difficulties; Maintenance, an average of 0.57 logins and 1.35 entries per week during the 12 week dissemination and 0.27 logins and 0.63 entries per week during the 9-month follow-up were achieved, 22 and 0% of participants completed the web-based physical activity and nutrition challenges and 33.3% of organizations intended to continue utilizing components of the intervention. While this intervention demonstrated good reach, effectiveness, adoption and implementation warrant further investigation.

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.