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Background : According to the Elaboration Likelihood Model, persuasion can occur via two different routes (the central route and peripheral route), with the route utilized dependent on factors associated with motivation and ability. This study aimed to explore the moderating role of need for cognition (NFC) and perceived relevance on the processing of physical activity messages designed to persuade via either the central route or the peripheral route. Method: Participants (N = 50) were randomized to receive messages optimized for central route processing or messages optimized for peripheral route processing. Eye-tracking devices were used to assess attention, which was the primary outcome. Message perceptions and the extent of persuasion (changes in physical activity determinants) were also assessed via self-report as secondary outcomes. Moderator effects were examined using interaction terms within mixed effects models and linear regression models. Results: There were no detected interactions between condition and NFC for any of the study outcomes (all ps >.05). Main effects of personal relevance were observed for some self-report outcomes, with increased relevance associated with better processing outcomes. An interaction between need for cognition and personal relevance was observed for perceived behavioral control (p = 0.002); greater relevance was associated with greater perceived behavioral control for those with a higher need for cognition. Conclusion: Matching physical activity messages based on NFC may not increase intervention efficacy. Relevance of materials is associated with greater change in physical activity determinants and may be more so among those with a higher NFC. [ABSTRACT FROM AUTHOR]

• Acceptability of the TaylorActive intervention website was rated mostly high in the video-tailored and text-tailored intervention groups. • Usability was rated high across the 3 groups with no significant between-group differences. • Usage of the TaylorActive website was modest in both video-tailored and text-tailored intervention groups. • Perceived usefulness of the TaylorActive website for increasing physical activity was rated low in both intervention groups, albeit significantly higher compared to the control group. • Satisfaction with the TaylorActive website was mixed. Intervention participants liked its ease of use, personalized feedback, and tracking of progress; however, they found completing action plans and survey questions each week repetitive and tedious. 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. 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. 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. 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. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: Online risk assessment tools for type 2 diabetes communicate risk information to motivate individuals to take actions and reduce their risk if needed. The impact of these tools on follow-up behaviours (e.g., General Practitioner (GP) visits, improvement in health behaviours) is unknown. This study examined effectiveness of a personalised video story and text-based message on GP and health professional visitations and health behaviours, of individuals assessed as 'high risk' following completion of the online Australian Type 2 Diabetes Risk Assessment Tool (AUSDRISK). Methods: A Randomised Controlled Trial (conducted between October 2018 and April 2019) included 477 participants with a high score (≥12). The control group received a text-based message (TM) and the intervention group received both the text-based message and a personalised video story (TM+VS) encouraging them to take follow-up action. Participants reported follow-up actions (one- and three months), and physical activity (PA), dietary behaviours and body weight (baseline, one and three months). Generalized Linear Mixed Models and chi-squared tests were used to test differences in outcomes between groups over time. Results: The intervention was not more effective for the TM+VS group compared to the TM only group (p-values>0.05 for all outcomes). More participants in the TM only group (49.8% compared to 40.0% in the VS+TM group) visited either a GP or health professional (p = 0.18). During the 3-month follow-up: 44.9% of all participants visited a GP (36.7%) and/or other health professional (31.0%). Significant improvements were found between baseline and three months, in both groups for weekly physical activity, daily fruit and vegetable intake and weight status. Conclusions: Messages provided with online diabetes risk assessment tools to those with high-risk, positively influence GP and health professional visitations and promote short-term improvements in health behaviours that may contribute to an overall reduction in the development of type 2 diabetes. Trial registration: Australia New Zealand Clinical Trials Registry; ACTRN12619000809134. [ABSTRACT FROM AUTHOR]

Background: To examine if a composite activity-sleep behaviour index (ASI) mediates the effects of a combined physical activity and sleep intervention on symptoms of depression, anxiety, or stress, quality of life (QOL), energy and fatigue in adults. Methods: This analysis used data pooled from two studies: Synergy and Refresh. Synergy: Physically inactive adults (18–65 years) who reported poor sleep quality were recruited for a two-arm Randomised Controlled Trial (RCT) (Physical Activity and Sleep Health (PAS; n = 80), or Wait-list Control (CON; n = 80) groups). Refresh: Physically inactive adults (40–65 years) who reported poor sleep quality were recruited for a three-arm RCT (PAS (n = 110), Sleep Health-Only (SO; n = 110) or CON (n = 55) groups). The SO group was omitted from this study. The PAS groups received a pedometer, and accessed a smartphone/tablet "app" using behaviour change strategies (e.g., self-monitoring, goal setting, action planning), with additional email/SMS support. The ASI score comprised self-reported moderate-to-vigorous-intensity physical activity, resistance training, sitting time, sleep duration, efficiency, quality and timing. Outcomes were assessed using DASS-21 (depression, anxiety, stress), SF-12 (QOL-physical, QOL-mental) and SF-36 (Energy & Fatigue). Assessments were conducted at baseline, 3 months (primary time-point), and 6 months. Mediation effects were examined using Structural Equation Modelling and the product of coefficients approach (AB), with significance set at 0.05. Results: At 3 months there were no direct intervention effects on mental health, QOL or energy and fatigue (all p > 0.05), and the intervention significantly improved the ASI (all p < 0.05). A more favourable ASI score was associated with improved symptoms of depression, anxiety, stress, QOL-mental and of energy and fatigue (all p < 0.05). The intervention effects on symptoms of depression ([AB; 95%CI] -0.31; − 0.60,-0.11), anxiety (− 0.11; − 0.27,-0.01), stress (− 0.37; − 0.65,-0.174), QOL-mental (0.53; 0.22, 1.01) and ratings of energy and fatigue (0.85; 0.33, 1.63) were mediated by ASI. At 6 months the magnitude of association was larger although the overall pattern of results remained similar. Conclusions: Improvements in the overall physical activity and sleep behaviours of adults partially mediated the intervention effects on mental health and quality of life outcomes. This highlights the potential benefit of improving the overall pattern of physical activity and sleep on these outcomes. Trial registration: Australian New Zealand Clinical Trial Registry: ACTRN12617000680369; ACTRN12617000376347. Universal Trial number: U1111–1194-2680; U1111–1186-6588. Human Research Ethics Committee Approval: H-2016-0267; H-2016–0181. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objectives: Examining mediators of intervention efficacy in an m-health intervention targeting physical activity and sleep in 160 Australian adults. Design: Nationwide randomised controlled trial. Main outcome measures: Moderate- and vigorous-intensity physical activity (MVPA), assessed using the Active Australia Questionnaire; sleep quality (Pittsburgh Sleep Quality Index); and sleep hygiene practices (Sleep Hygiene Index). Hypothesised psychosocial (e.g. self-efficacy) and behavioural (i.e. MVPA, sleep quality, sleep hygiene) mediators were tested on primary endpoint data at 3 months using bias-corrected bootstrapping (PROCESS 2 for SPSS). All outcomes and mediators were assessed using self-report. Results: At three months, the intervention had significantly improved sleep quality (d = 0.48, 95% CI: −2.26, −0.33, p = 0.009) and sleep hygiene (d = 0.40, 95% CI: −3.10, −0.19, p = 0.027). Differences in MVPA were not significant (d = 0.24, 95% CI: −35.53, 254.67, p = 0.139). Changes in MVPA were mediated by self-efficacy, perceived capability, environment, social support, intentions and planning, some of which showed inconsistent mediation (suppression). None of the hypothesised psychosocial factors mediated sleep outcomes. Changes in sleep hygiene mediated changes in sleep quality. Conclusions: Several psychosocial factors mediated changes in physical activity but not in sleep outcomes. Mediation effects of sleep hygiene on sleep quality highlight the importance of providing evidence-based strategies to improve sleep quality. [ABSTRACT FROM AUTHOR]

Background: Although gender is an important determinant of health behaviour with males less likely to perform health-protective behaviours, samples in health behaviour research are heavily biased towards females. This study investigated the use of online social network, Facebook, to reach and recruit inactive males to a team-based, social, and gamified physical activity randomised controlled trial.Methods: Methodological techniques included a narrative literature review, survey of inactive males (n = 34) who rated advertisement images and text captions on scales of 1-10, and trial Facebook-delivered recruitment campaigns. Advertisement effectiveness was measured by cost-per-click to the study website, number of expressions of interest, and study enrolments from males.Results: Survey results showed that vibrant images of men exercising accompanied by concise captions (< 35 words) were most effective. An advertising campaign incorporating these components achieved a cost-per-click of $0.60, with 80% of n = 50 expressions of interest being from men, a marked improvement from baseline campaigns in which only 11% of expressions of interest were from men. Despite this, men who were recruited through the targeted campaign failed to enrol into the study, primarily due to reluctance to invite friends to join their team. An alternative strategy of encouraging females to invite men boosted male participation from 18% of the sample at baseline to 29% in the targeted recruitment phase.Conclusions: Evidence-based approaches can improve Facebook recruitment outcomes, however, there are complex barriers hindering male recruitment to health behaviour studies that may necessitate multi-faceted strategies including involvement of family and friends. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Physical inactivity is a leading preventable cause of chronic disease and premature death globally, yet over half of the adult Australian population is inactive. To address this, web-based physical activity interventions, which have the potential to reach large numbers of users at low costs, have received considerable attention. To fully realise the potential of such interventions, there is a need to further increase their appeal to boost engagement and retention, and sustain intervention effects over longer periods of time. This randomised controlled trial aims to evaluate the efficacy of a gamified physical activity intervention that connects users to each other via Facebook and is delivered via a mobile app.Methods: The study is a three-group, cluster-RCT. Four hundred and forty (440) inactive Australian adults who use Facebook at least weekly will be recruited in clusters of three to eight existing Facebook friends. Participant clusters will be randomly allocated to one of three conditions: (1) waitlist control condition, (2) basic experimental condition (pedometer plus basic app with no social and gamification features), or (3) socially-enhanced experimental condition (pedometer plus app with social and gamification features). Participants will undertake assessments at baseline, three and nine months. The primary outcome is change in total daily minutes of moderate-to-vigorous physical activity at three months measured objectively using GENEActive accelerometers [Activeinsights Ltd., UK]. Secondary outcomes include self-reported physical activity, depression and anxiety, wellbeing, quality of life, social-cognitive theory constructs and app usage and engagement.Discussion: The current study will incorporate novel social and gamification elements in order to examine whether the inclusion of these components increases the efficacy of app-based physical activity interventions. The findings will be used to guide the development and increase the effectiveness of future health behaviour interventions.Trial Registration: This trial was registered with the Australian and New Zealand Clinical Trial Registry ( ACTRN12617000113358 , date of registration 23 January, 2017). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Most people do not engage in sufficient physical activity to confer health benefits and to reduce risk of chronic disease. Healthcare professionals frequently provide guidance on physical activity, but often do not meet guideline levels of physical activity themselves. The main objective of this study is to develop and test the efficacy of a tailored intervention to increase healthcare professionals' physical activity participation and quality of life, and to reduce work-related stress and absenteeism. This is the first study to compare the additive effects of three forms of a tailored intervention using different techniques from behavioural theory, which differ according to their focus on motivational, self-regulatory and/or habitual processes.Methods/design: Healthcare professionals (N = 192) will be recruited from four hospitals in Perth, Western Australia, via email lists, leaflets, and posters to participate in the four group randomised controlled trial. Participants will be randomised to one of four conditions: (1) education only (non-tailored information only), (2) education plus intervention components to enhance motivation, (3) education plus components to enhance motivation and self-regulation, and (4) education plus components to enhance motivation, self-regulation and habit formation. All intervention groups will receive a computer-tailored intervention administered via a web-based platform and will receive supporting text-messages containing tailored information, prompts and feedback relevant to each condition. All outcomes will be assessed at baseline, and at 3-month follow-up. The primary outcome assessed in this study is physical activity measured using activity monitors. Secondary outcomes include: quality of life, stress, anxiety, sleep, and absenteeism. Website engagement, retention, preferences and intervention fidelity will also be evaluated as well as potential mediators and moderators of intervention effect.Discussion: This is the first study to examine a tailored, technology-supported intervention aiming to increase physical activity in healthcare professionals. The study will evaluate whether including additional theory-based behaviour change techniques aimed at promoting motivation, self-regulation and habit will lead to increased physical activity participation relative to information alone. The online platform developed in this study has potential to deliver efficient, scalable and personally-relevant intervention that can be translated to other occupational settings.Trial Registration: Australian New-Zealand Clinical Trial Registry: ACTRN12616000462482, submitted 29/03/2016, prospectively registered 8/04/2016. [ABSTRACT FROM AUTHOR]

Background: Office workers demonstrate high levels of sitting on workdays. As sitting is positively associated with adverse health risks in adults, a theory-driven web-based computer-tailored intervention to influence workplace sitting, named 'Start to Stand,' was developed. The intervention was found to be effective in reducing self-reported workplace sitting among Flemish employees. The aim of this study was to investigate through which mechanisms the web-based computer-tailored intervention influenced self-reported workplace sitting.Methods: Employees (n = 155) participated in a clustered randomised controlled trial and reported socio-demographics (age, gender, education), work-related (hours at work, employment duration), health-related (weight and height, workplace sitting and physical activity) and psychosocial (knowledge, attitudes, self-efficacy, social support, intention regarding (changing) sitting behaviours) variables at baseline and 1-month follow-up. The product-of-coefficients test of MacKinnon based on multiple linear regression analyses was conducted to examine the mediating role of five psychosocial factors (knowledge, attitudes, self-efficacy, social support, intention). The influence of one self-regulation skill (action planning) in the association between the intervention and self-reported workplace sitting time was investigated via moderation analyses.Results: The intervention had a positive influence on knowledge (p = 0.040), but none of the psychosocial variables did mediate the intervention effect on self-reported workplace sitting. Action planning was found to be a significant moderator (p < 0.001) as the decrease in self-reported workplace sitting only occurred in the group completing an action plan.Conclusions: Future interventions aimed at reducing employees' workplace sitting are suggested to focus on self-regulatory skills and promote action planning when using web-based computer-tailored advice.Trial Registration: Clinicaltrials.gov NCT02672215 ; (Archived by WebCite at https://clinicaltrials.gov/ct2/show/NCT02672215 ). [ABSTRACT FROM AUTHOR]

Background: Physical activity (PA) during pregnancy is associated with a variety of health benefits including a reduced risk of pregnancy related conditions such as pre-eclampsia and pregnancy-induced hypertension and leads to greater control over gestational weight gain. Despite these associated health benefits, very few pregnant women are sufficiently active. In an attempt to increase health outcomes, it is important to explore innovative ways to increase PA among pregnant women. Therefore, the aim of this study was to assess the feasibility, acceptability and efficacy of a four week web-based computer-tailored PA intervention among pregnant women.Methods: Seventy-seven participants were randomised into either: (1) an intervention group that received tailored PA advice and access to a resource library of articles relating to PA during pregnancy; or (2) a standard information group that only received access to the resources library. Objective moderate-to-vigorous physical activity (MVPA) was assessed at baseline and immediately post-intervention. Recruitment, attrition, intervention adherence, and website engagement were assessed. Questions on usability and satisfaction were administered post-intervention.Results: Feasibility was demonstrated through acceptable recruitment (8.5 participants recruited and randomised/month), and attrition (25%). Acceptability among intervention group participants was positive with high intervention adherence (96% of 4 modules completed). High website engagement (participants logged in 1.6 times/week although only required to log in once per week), usability (75/100), and satisfaction outcomes were reported in both groups. However, participants in the intervention group viewed significantly more pages on the website (p < 0.05), reported that the website felt more personally relevant (p < 0.05), and significantly increased their MVPA from baseline to post-intervention (mean difference = 35.87 min), compared to the control group (mean difference = 9.83 min) (p < 0.05), suggesting efficacy.Conclusions: The delivery of a computer-tailored web-based intervention designed to increase PA in pregnant women is feasible, well accepted and associated with increases in short-term MVPA. Findings suggest the use of computer-tailored information leads to greater website engagement, satisfaction and greater PA levels among pregnant women compared to a generic information only website.Trial Registration: The trial was 'retrospectively registered' with the Australian New Zealand Clinical Trials Registry ( ACTRN12614001105639 ) on 17th October, 2014. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Web-based physical activity interventions that apply computer tailoring have shown to improve engagement and behavioral outcomes but provide limited accountability and social support for participants. It is unknown how video calls with a behavioral expert in a Web-based intervention will be received and whether they improve the effectiveness of computer-tailored advice.Objective: The purpose of this study was to determine the feasibility and effectiveness of brief video-based coaching in addition to fully automated computer-tailored advice in a Web-based physical activity intervention for inactive adults.Methods: Participants were assigned to one of the three groups: (1) tailoring + video-coaching where participants received an 8-week computer-tailored Web-based physical activity intervention ("My Activity Coach") including 4 10-minute coaching sessions with a behavioral expert using a Web-based video-calling program (eg, Skype; n=52); (2) tailoring-only where participants received the same intervention without the coaching sessions (n=54); and (3) a waitlist control group (n=45). Demographics were measured at baseline, intervention satisfaction at week 9, and physical activity at baseline, week 9, and 6 months by Web-based self-report surveys. Feasibility was analyzed by comparing intervention groups on retention, adherence, engagement, and satisfaction using t tests and chi-square tests. Effectiveness was assessed using linear mixed models to compare physical activity changes between groups.Results: A total of 23 tailoring + video-coaching participants, 30 tailoring-only participants, and 30 control participants completed the postintervention survey (83/151, 55.0% retention). A low percentage of tailoring + video-coaching completers participated in the coaching calls (11/23, 48%). However, the majority of those who participated in the video calls were satisfied with them (5/8, 71%) and had improved intervention adherence (9/11, 82% completed 3 or 4 modules vs 18/42, 43%, P=.01) and engagement (110 minutes spent on the website vs 78 minutes, P=.02) compared with other participants. There were no overall retention, adherence, engagement, and satisfaction differences between tailoring + video-coaching and tailoring-only participants. At 9 weeks, physical activity increased from baseline to postintervention in all groups (tailoring + video-coaching: +150 minutes/week; tailoring only: +123 minutes/week; waitlist control: +34 minutes/week). The increase was significantly higher in the tailoring + video-coaching group compared with the control group (P=.01). No significant difference was found between intervention groups and no significant between-group differences were found for physical activity change at 6 months.Conclusions: Only small improvements were observed when video-coaching was added to computer-tailored advice in a Web-based physical activity intervention. However, combined Web-based video-coaching and computer-tailored advice was effective in comparison with a control group. More research is needed to determine whether Web-based coaching is more effective than stand-alone computer-tailored advice.Trial Registration: Australian New Zealand Clinical Trials Registry (ACTRN): 12614000339651; http://www.anzctr.org.au/TrialSearch.aspx?searchTxt=ACTRN12614000339651+&isBasic=True (Archived by WebCite at http://www.webcitation.org/6jTnOv0Ld). [ABSTRACT FROM AUTHOR]

Background: Many adults are insufficiently physically active, have prolonged sedentary behaviour and report poor sleep. These behaviours can be improved by interventions that include education, goal setting, self-monitoring, and feedback strategies. Few interventions have explicitly targeted these behaviours simultaneously or examined the relative efficacy of different self-monitoring methods.Methods/design: This study aims to compare the efficacy of two self-monitoring methods in an app-based multi-behaviour intervention to improve objectively measured physical activity, sedentary, and sleep behaviours, in a 9 week 2-arm randomised trial. Participants will be adults (n = 64) who report being physically inactive, sitting >8 h/day and frequent insufficient sleep (≥14 days out of last 30). The "Balanced" intervention is delivered via a smartphone 'app', and includes education materials (guidelines, strategies to promote change in behaviour), goal setting, self-monitoring and feedback support. Participants will be randomly allocated to either a device-entered or user-entered self-monitoring method. The device-entered group will be provided with a activity tracker to self-monitor behaviours. The user-entered group will recall and manually record behaviours. Assessments will be conducted at 0, 3, 6, and 9 weeks. Physical activity, sedentary behaviour and sleep-wake behaviours will be measured using the wrist worn Geneactiv accelerometer. Linear mixed models will be used to examine differences between groups and over time using an alpha of 0.01.Discussion: This study will evaluate an app-based multi-behavioural intervention to improve physical activity, sedentary behaviour and sleep; and the relative efficacy of two different approaches to self-monitoring these behaviours. Outcomes will provide information to inform future interventions and self-monitoring targeting these behaviours.Trial Registration: ACTRN12615000182594 (Australian New Zealand Clinical Trials Registry. Registry URL: www.anzctr.org.au ; registered prospectively on 25 February 2015). [ABSTRACT FROM AUTHOR]

Background: Effective interventions to influence workplace sitting are needed, as office-based workers demonstrate high levels of continued sitting, and sitting too much is associated with adverse health effects. Therefore, we developed a theory-driven, Web-based, interactive, computer-tailored intervention aimed at reducing and interrupting sitting at work.Objective: The objective of our study was to investigate the effects of this intervention on objectively measured sitting time, standing time, and breaks from sitting, as well as self-reported context-specific sitting among Flemish employees in a field-based approach.Methods: Employees (n=213) participated in a 3-group randomized controlled trial that assessed outcomes at baseline, 1-month follow-up, and 3-month follow-up through self-reports. A subsample (n=122) were willing to wear an activity monitor (activPAL) from Monday to Friday. The tailored group received an automated Web-based, computer-tailored intervention including personalized feedback and tips on how to reduce or interrupt workplace sitting. The generic group received an automated Web-based generic advice with tips. The control group was a wait-list control condition, initially receiving no intervention. Intervention effects were tested with repeated-measures multivariate analysis of variance.Results: The tailored intervention was successful in decreasing self-reported total workday sitting (time × group: P<.001), sitting at work (time × group: P<.001), and leisure time sitting (time × group: P=.03), and in increasing objectively measured breaks at work (time × group: P=.07); this was not the case in the other conditions. The changes in self-reported total nonworkday sitting, sitting during transport, television viewing, and personal computer use, objectively measured total sitting time, and sitting and standing time at work did not differ between conditions.Conclusions: Our results point out the significance of computer tailoring for sedentary behavior and its potential use in public health promotion, as the effects of the tailored condition were superior to the generic and control conditions.Trial Registration: Clinicaltrials.gov NCT02672215; http://clinicaltrials.gov/ct2/show/NCT02672215 (Archived by WebCite at http://www.webcitation.org/6glPFBLWv). [ABSTRACT FROM AUTHOR]

Background: Physical activity (PA) offers numerous benefits to health and well-being, but most adults are not sufficiently physically active to afford such benefits. The 10,000 steps campaign has been a popular and effective approach to promote PA. The Transtheoretical Model posits that individuals have varying levels of readiness for health behavior change, known as Stages of Change (Precontemplation, Contemplation, Preparation, Action, and Maintenance). Few validated assessment instruments are available for determining Stages of Change in relation to the PA goal of 10,000 steps per day. The purpose of this study was to assess the criterion-related validity of the SoC-Step, a brief 10,000 steps per day Stages of Change instrument.Methods: Participants were 504 Australian adults (176 males, 328 females, mean age = 50.8 ± 13.0 years) from the baseline sample of the Walk 2.0 randomized controlled trial. Measures included 7-day accelerometry (Actigraph GT3X), height, weight, and self-reported intention, self-efficacy, and SoC-Step: Stages of Change relative to achieving 10,000 steps per day. Kruskal-Wallis H tests with pairwise comparisons were used to determine whether participants differed by stage, according to steps per day, general health, body mass index, intention, and self-efficacy to achieve 10,000 steps per day. Binary logistic regression was used to test the hypothesis that participants in Maintenance or Action stages would have greater likelihood of meeting the 10,000 steps goal, in comparison to participants in the other three stages.Results: Consistent with study hypotheses, participants in Precontemplation had significantly lower intention scores than those in Contemplation (p = 0.003) or Preparation (p < 0.001). Participants in Action or Maintenance stages were more likely to achieve ≥10,000 steps per day (OR = 3.11; 95 % CI = 1.66,5.83) compared to those in Precontemplation, Contemplation, or Preparation. Intention (p < 0.001) and self-efficacy (p < 0.001) to achieve 10,000 steps daily differed by stage, and participants in the Maintenance stage had higher general health status and lower body mass index than those in Precontemplation, Contemplation and Preparation stages (p < 0.05).Conclusions: This brief SoC-Step instrument appears to have good criterion-related validity for determining Stages of Change related to the public health goal of 10,000 steps per day.Trial Registration: Australian New Zealand Clinical Trials Registry reference: ACTRN12611000157976 World Health Organization Universal Trial Number: U111-1119-1755. [ABSTRACT FROM AUTHOR]

Background Effective strategies to address risk factors of non-communicable diseases are required to curtail the expanding costs of health care. This trial tested the effectiveness over one year of a minimal intervention targeting multiple health behaviours (diet, physical activity, alcohol and smoking) in a general practice setting, through the provision of personalised, computer-tailored feedback. Methods Patients who had attended a general practice in the previous 6 months were recruited from 21 general practitioners in Brisbane, Australia. Baseline data were collected using self-reports on adherence to ten health behaviours and summarised into a health score from 0 to 10. This randomised controlled trial used a 2x2 factorial design, with one arm randomising subjects to the intervention or control group. The other arm was either feedback at baseline (single contact) or an additional assessment with feedback at 3 months (dual contact). As such, 4 study groups created were, to which participants were randomised blindly: A. Intervention with single contact; B. Intervention with dual contact; C. Control with single contact and D. Control with dual contact. All participants were assessed again at 12 months. Results Of the 4676 participants randomised, 3065 completed questionnaires at 12 months. Both single and dual contact groups improved their 10 item health scores (+0.31 and +0.49 respectively) relative to control group outcomes (+0.02; p < 0.01). Improvement in adherence to guidelines for fish intake, type of milk consumed, vegetable and fruit intake, and alcohol intake were observed in single and dual contact intervention groups (p < 0.01). Both intervention groups showed greater improvement than controls for individual health behaviours, apart from red meat intake, smoking behaviour, physical activity and body weight. Interestingly, there was an improvement in reported non-smoking rates in both intervention and control groups (3% single contact; 4.5% dual contact). Conclusions Small but meaningful long-term changes in health behaviours can be achieved with a low-intensity intervention, which may reduce health care costs if implemented on a large scale. Further research is needed to better understand the mechanism by which maintenance of behaviour change can be achieved. Trial Registration The Australian New Zealand Clinical Trials Registry: ACTRN12611001213932. [ABSTRACT FROM AUTHOR]

Abstract: Objective: This study examined the effectiveness of a fully automated web-based programme to increase physical activity in adults with Type 2 diabetes. Methods: Between May and July 2010, participants were randomly allocated into either a 12-week intervention (n =195) or a control (n =202) group. Participants were adults diagnosed with Type 2 diabetes, residing in Australia. Participants were assessed at baseline, 12 and 36weeks. The primary physical activity outcome was self-reported minutes of total physical activity. Secondary physical activity outcomes included minutes spent walking, and engaged in moderate, and vigorous physical activity. Additional measures included website satisfaction and website usage. The intervention consisted of a 12-week web-based physical activity intervention developed based on the Theory of Planned Behavior and self-management framework. Data were analysed from 2011 to 2012. Results: There was a significant group-by-time interaction (X 2 (df =1)=6.37, p <.05) for total physical activity favouring the intervention group d =0.11, for those who completed the intervention, however this was not significant in the intention-to-treat analysis d =0.01. The intervention yielded high website satisfaction and usage. Conclusions: In general, there is some evidence for the effectiveness of web-based interventions for improving physical activity levels; however it is clear that maintaining improvements remains an issue. [Copyright &y& Elsevier]

Background: Physical inactivity is one of the leading modifiable causes of death and disease in Australia. National surveys indicate less than half of the Australian adult population are sufficiently active to obtain health benefits. The Internet is a potentially important medium for successfully communicating health messages to the general population and enabling individual behaviour change. Internet-based interventions have proven efficacy; however, intervention studies describing website usage objectively have reported a strong decline in usage, and high attrition rate, over the course of the interventions. Web 2.0 applications give users control over web content generated and present innovative possibilities to improve user engagement. There is, however, a need to assess the effectiveness of these applications in the general population. The Walk 2.0 project is a 3-arm randomised controlled trial investigating the effects of "next generation" web-based applications on engagement, retention, and subsequent physical activity behaviour change. Methods/design: 504 individuals will be recruited from two sites in Australia, randomly allocated to one of two web-based interventions (Web 1.0 or Web 2.0) or a control group, and provided with a pedometer to monitor physical activity. The Web 1.0 intervention will provide participants with access to an existing physical activity website with limited interactivity. The Web 2.0 intervention will provide access to a website featuring Web 2.0 content, including social networking, blogs, and virtual walking groups. Control participants will receive a logbook to record their steps. All groups will receive similar educational material on setting goals and increasing physical activity. The primary outcomes are objectively measured physical activity and website engagement and retention. Other outcomes measured include quality of life, psychosocial correlates, and anthropometric measurements. Outcomes will be measured at baseline, 3, 12 and 18 months. Discussion: The findings of this study will provide increased understanding of the benefit of new web-based technologies and applications in engaging and retaining participants on web-based intervention sites, with the aim of improved health behaviour change outcomes. [ABSTRACT FROM AUTHOR]

Background: The adoption and maintenance of healthy behaviours is essential in the primary prevention of chronic non-communicable diseases. This study evaluated the effectiveness of a minimal intervention on multiple lifestyle factors such as diet, physical activity, smoking and alcohol, delivered through general practice, using computer-tailored feedback. Methods: Adult patients visiting 21 general practitioners in Brisbane, Australia, were surveyed about ten health behaviours that are risk factors for chronic, non-communicable diseases. Those who completed the self-administered baseline questionnaire entered a randomised controlled trial, with the intervention group receiving computer-tailored printed advice, targeting those health behaviours for which respondents were not meeting current recommendations. The primary outcome was change in summary lifestyle score (Prudence Score) and individual health behaviours at three months. A repeated measures analysis compared change in these outcomes in intervention and control groups after adjusting for age and education. Results: 2306 patients were randomised into the trial. 1711 (76%) returned the follow-up questionnaire at 3 months. The Prudence Score (10 items) in the intervention group at baseline was 5.88, improving to 6.25 at 3 months (improvement = 0.37), compared with 5.84 to 5.96 (improvement = 0.12) in the control group (F = 13.3, p = 0.01). The intervention group showed improvement in meeting recommendations for all individual health behaviours compared with the control group. However, these differences were significant only for fish intake (OR 1.37, 95% CI 1.11-1.68), salt intake (OR 1.19, 95% CI 1.05-1.38), and type of spread used (OR 1.28, 95% CI 1.06-1.51). Conclusion: A minimal intervention using computer-tailored feedback to address multiple lifestyle behaviours can facilitate change and improve unhealthy behaviours. Although individual behaviour changes were modest, when implemented on a large scale through general practice, this intervention appears to be an effective and practical tool for population-wide primary prevention. Trial Registration: The Australian New Zealand Clinical Trials Registry: ACTRN12611001213932 [ABSTRACT FROM AUTHOR]

Synopsis: Despite their popularity and potential to promote health in large populations, the effectiveness of online social networks (e.g., Facebook) to improve health behaviors has been somewhat disappointing. Most of the research examining the effectiveness of such interventions has used randomized controlled trials (RCTs). It is asserted that the modest outcomes may be due to characteristics specific to both online social networks and RCTs. The highly controlled nature of RCTs stifles the dynamic nature of online social networks. Alternative and ecologically valid research designs that evaluate online social networks in real-life conditions are needed to advance the science in this area. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Simple Summary: Previous research supports the participation in supervised exercise among individuals with metastatic prostate cancer to help lessen the physical and psychological disease burden. However, many individuals experience considerable barriers to attending face-to-face exercise services. To overcome some of these limitations, digital interventions that can be delivered remotely have been proposed. Our pilot study investigated the acceptability, safety and preliminary efficacy of an 8-week computer-tailored web-based exercise intervention. We demonstrated that a web-based exercise program with telehealth support was acceptable and could be implemented safely. Participants in the intervention group increased their participation in moderate to vigorous physical activity compared to the control group. This study provides insight into the prospect of web-based exercise prescription for individuals with metastatic prostate cancer as an alternative for individuals who cannot access supervised exercise interventions. Preliminary research has shown the effectiveness of supervised exercise-based interventions in alleviating sequela resulting from metastatic prostate cancer. However, many individuals encounter barriers that limit the uptake of face-to-face exercise. Technology-enabled interventions offer a distance-based alternative. This pilot study aimed to explore the acceptability, safety and preliminary efficacy of a web-based exercise intervention (ExerciseGuide) in individuals with metastatic prostate cancer. Forty participants (70.2 ± 8.5 years) with metastatic prostate cancer were randomised into the 8-week intervention (N = 20) or a wait-list control (N = 20). The intervention arm had access to a computer-tailored website, personalised exercise prescription and remote supervision. ExerciseGuide was deemed acceptable with a score ≥20 on the client satisfaction questionnaire; however, the usability score was just below the pre-specified score of ≥68 on the software usability scale. There were no serious adverse events reported. Moderate-to-vigorous physical activity levels between baseline and follow-ups were significantly higher (10.0 min per day; 95% CI = (1.3–18.6); p = 0.01) in the intervention group compared to wait-list control. There were also greater improvements in step count (1332; 95% CI = (159–2505); p = 0.02) and identified motivation (0.4, 95% CI = (0.0, 0.7); p = 0.04). Our findings provide preliminary evidence that ExerciseGuide is acceptable, safe and efficacious among individuals with metastatic prostate cancer. [ABSTRACT FROM AUTHOR]

Background: The success of a mobile phone app in changing health behavior is thought to be contingent on engagement, commonly operationalized as frequency of use.Objective: This subgroup analysis of the 2 intervention arms from a 3-group randomized controlled trial aimed to examine user engagement with a 100-day physical activity intervention delivered via an app. Rates of engagement, associations between user characteristics and engagement, and whether engagement was related to intervention efficacy were examined.Methods: Engagement was captured in a real-time log of interactions by users randomized to either a gamified (n=141) or nongamified version of the same app (n=160). Physical activity was assessed via accelerometry and self-report at baseline and 3-month follow-up. Survival analysis was used to assess time to nonuse attrition. Mixed models examined associations between user characteristics and engagement (total app use). Characteristics of super users (top quartile of users) and regular users (lowest 3 quartiles) were compared using t tests and a chi-square analysis. Linear mixed models were used to assess whether being a super user was related to change in physical activity over time.Results: Engagement was high. Attrition (30 days of nonuse) occurred in 32% and 39% of the gamified and basic groups, respectively, with no significant between-group differences in time to attrition (P=.17). Users with a body mass index (BMI) in the healthy range had higher total app use (mean 230.5, 95% CI 190.6-270.5; F2=8.67; P<.001), compared with users whose BMI was overweight or obese (mean 170.6, 95% CI 139.5-201.6; mean 132.9, 95% CI 104.8-161.0). Older users had higher total app use (mean 200.4, 95% CI 171.9-228.9; F1=6.385; P=.01) than younger users (mean 155.6, 95% CI 128.5-182.6). Super users were 4.6 years older (t297=3.6; P<.001) and less likely to have a BMI in the obese range (χ22=15.1; P<.001). At the 3-month follow-up, super users were completing 28.2 (95% CI 9.4-46.9) more minutes of objectively measured physical activity than regular users (F1,272=4.76; P=.03).Conclusions: Total app use was high across the 100-day intervention period, and the inclusion of gamified features enhanced engagement. Participants who engaged the most saw significantly greater increases to their objectively measured physical activity over time, supporting the theory that intervention exposure is linked to efficacy. Further research is needed to determine whether these findings are replicated in other app-based interventions, including those experimentally evaluating engagement and those conducted in real-world settings.Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12617000113358; https://www.anzctr.org.au/ACTRN12617000113358.aspx. [ABSTRACT FROM AUTHOR]

Background: Mobile technologies have great potential to promote an active lifestyle in lower educated working young adults, an underresearched target group at a high risk of low activity levels. Objective: The objective of our study was to examine the effect and process evaluation of the newly developed evidence- and theory-based smartphone app "Active Coach" on the objectively measured total daily physical activity; self-reported, context-specific physical activity; and self-reported psychosocial variables among lower educated working young adults. Methods: We recruited 130 lower educated working young adults in this 2-group cluster randomized controlled trial and assessed outcomes at baseline, posttest (baseline+9 weeks), and follow-up (posttest+3 months). Intervention participants (n=60) used the Active Coach app (for 9 weeks) combined with a Fitbit activity tracker. Personal goals, practical tips, and educational facts were provided to encourage physical activity. The control group received print-based generic physical activity information. Both groups wore accelerometers for objective measurement of physical activity, and individual interviews were conducted to assess the psychosocial variables and context-specific physical activity. Furthermore, intervention participants were asked process evaluation questions and generalized linear mixed models and descriptive statistics were applied. Results: No significant intervention effects were found for objectively measured physical activity, self-reported physical activity, and self-reported psychosocial variables (all P>.05). Intervention participants evaluated the Active Coach app and the combined use with the Fitbit wearable as self-explanatory (36/51, 70.6%), user friendly (40/51, 78.4%), and interesting (34/51, 66.7%). Throughout the intervention, we observed a decrease in the frequency of viewing graphical displays in the app (P<.001); reading the tips, facts, and goals (P<.05); and wearing the Fitbit wearable (P<.001). Few intervention participants found the tips and facts motivating (10/41, 24.4%), used them to be physically active (8/41, 19.6%), and thought they were tailored to their lifestyle (7/41, 17.1%). Conclusions: The lack of significant intervention effects might be due to low continuous user engagement. Advice or feedback that was not perceived as adequately tailored and the difficulty to compete with many popular commercial apps on young people's smartphones may be responsible for a decrease in the engagement. A stand-alone app does not seem sufficient to promote an active lifestyle among lower educated working young adults; therefore, multicomponent interventions (using both technological and human support), as well as context-specific sensing to provide tailored advice, might be needed in this population. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

Background: Online social networks offer considerable potential for delivery of socially influential health behavior change interventions.Objective: To determine the efficacy, engagement, and feasibility of an online social networking physical activity intervention with pedometers delivered via Facebook app.Methods: A total of 110 adults with a mean age of 35.6 years (SD 12.4) were recruited online in teams of 3 to 8 friends. Teams were randomly allocated to receive access to a 50-day online social networking physical activity intervention which included self-monitoring, social elements, and pedometers ("Active Team" Facebook app; n=51 individuals, 12 teams) or a wait-listed control condition (n=59 individuals, 13 teams). Assessments were undertaken online at baseline, 8 weeks, and 20 weeks. The primary outcome measure was self-reported weekly moderate-to-vigorous physical activity (MVPA). Secondary outcomes were weekly walking, vigorous physical activity time, moderate physical activity time, overall quality of life, and mental health quality of life. Analyses were undertaken using random-effects mixed modeling, accounting for potential clustering at the team level. Usage statistics were reported descriptively to determine engagement and feasibility.Results: At the 8-week follow-up, the intervention participants had significantly increased their total weekly MVPA by 135 minutes relative to the control group (P=.03), due primarily to increases in walking time (155 min/week increase relative to controls, P<.001). However, statistical differences between groups for total weekly MVPA and walking time were lost at the 20-week follow-up. There were no significant changes in vigorous physical activity, nor overall quality of life or mental health quality of life at either time point. High levels of engagement with the intervention, and particularly the self-monitoring features, were observed.Conclusions: An online, social networking physical activity intervention with pedometers can produce sizable short-term physical activity changes. Future work is needed to determine how to maintain behavior change in the longer term, how to reach at-need populations, and how to disseminate such interventions on a mass scale.Trial Registration: Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12614000488606; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366239 (Archived by WebCite at http://www.webcitation.org/6ZVtu6TMz). [ABSTRACT FROM AUTHOR]

Background: The high number of adult males engaging in low levels of physical activity and poor dietary practices, and the health risks posed by these behaviors, necessitate broad-reaching intervention strategies. Information technology (IT)-based (Web and mobile phone) interventions can be accessed by large numbers of people, yet there are few reported IT-based interventions targeting males' physical activity and dietary practices. Objective: This study examines the effectiveness of a 9-month IT-based intervention (ManUp) to improve the physical activity, dietary behaviors, and health literacy in middle-aged males compared to a print-based intervention. Methods: Participants, recruited offline (eg, newspaper ads), were randomized into either an IT-based or print-based intervention arm on a 2:1 basis in favor of the fully automated IT-based arm. Participants were adult males aged 35-54 years living in 2 regional cities in Queensland, Australia, who could access the Internet, owned a mobile phone, and were able to increase their activity level. The intervention, ManUp, was based on social cognitive and self-regulation theories and specifically designed to target males. Educational materials were provided and self-monitoring of physical activity and nutrition behaviors was promoted. Intervention content was the same in both intervention arms; only the delivery mode differed. Content could be accessed throughout the 9-month study period. Participants' physical activity, dietary behaviors, and health literacy were measured using online surveys at baseline, 3 months, and 9 months. Results: A total of 301 participants completed baseline assessments, 205 in the IT-based arm and 96 in the print-based arm. A total of 124 participants completed all 3 assessments. There were no significant between-group differences in physical activity and dietary behaviors (P≥.05). Participants reported an increased number of minutes and sessions of physical activity at 3 months (exp(β)=1.45, 95% CI 1.09-1.95; exp(β)=1.61, 95% CI 1.17-2.22) and 9 months (exp(β)=1.55, 95% CI 1.14-2.10; exp(β)=1.51, 95% CI 1.15-2.00). Overall dietary behaviors improved at 3 months (exp(β)=1.07, 95% CI 1.03-1.11) and 9 months (exp(β)=1.10, 95% CI 1.05-1.13). The proportion of participants in both groups eating higher-fiber bread and low-fat milk increased at 3 months (exp(β)=2.25, 95% CI 1.29-3.92; exp(β)=1.65, 95% CI 1.07-2.55). Participants in the IT-based arm were less likely to report that 30 minutes of physical activity per day improves health (exp(β)=0.48, 95% CI 0.26-0.90) and more likely to report that vigorous intensity physical activity 3 times per week is essential (exp(β)=1.70, 95% CI 1.02-2.82). The average number of log-ins to the IT platform at 3 and 9 months was 6.99 (SE 0.86) and 9.22 (SE 1.47), respectively. The average number of self-monitoring entries at 3 and 9 months was 16.69 (SE 2.38) and 22.51 (SE 3.79), respectively. Conclusions: The ManUp intervention was effective in improving physical activity and dietary behaviors in middle-aged males with no significant differences between IT- and print-based delivery modes. [ABSTRACT FROM AUTHOR]

Background: Persistently poor glycemic control in adult type 1 diabetes patients is a common, complex, and serious problem initiating significant damage to the cardiovascular, renal, neural, and visual systems. Currently, there is a plethora of low-cost and free diabetes self-management smartphone applications available in online stores. Objective: The aim of this study was to examine the effectiveness of a freely available smartphone application combined with text-message feedback from a certified diabetes educator to improve glycemic control and other diabetes-related outcomes in adult patients with type 1 diabetes in a two-group randomized controlled trial. Methods: Patients were recruited through an online type 1 diabetes support group and letters mailed to adults with type 1 diabetes throughout Australia. In a 6-month intervention, followed by a three-month follow-up, patients (n=72) were randomized to usual care (control group) or usual care and the use of a smartphone application (Glucose Buddy) with weekly text-message feedback from a Certified Diabetes Educator (intervention group). All outcome measures were collected at baseline and every three months over the study period. Patients' glycosylated hemoglobin levels (HbA1c) were measured with a blood test and diabetes-related self-efficacy, self-care activities, and quality of life were measured with online questionnaires. Results: The mean age of patients was 35.20 years (SD 10.43) (28 male, 44 female), 39% (28/72) were male, and patients had been diagnosed with type 1 diabetes for a mean of 18.94 years (SD 9.66). Of the initial 72 patients, 53 completed the study (25 intervention, 28 control group). The intervention group significantly improved glycemic control (HbA1c) from baseline (mean 9.08%, SD 1.18) to 9-month follow-up (mean 7.80%, SD 0.75), compared to the control group (baseline: mean 8.47%, SD 0.86, follow-up: mean 8.58%, SD 1.16). No significant change over time was found in either group in relation to self-efficacy, self-care activities, and quality of life. Conclusions: In adjunct to usual care, the use of a diabetes-related smartphone application combined with weekly text-message support from a health care professional can significantly improve glycemic control in adults with type 1 diabetes. [ABSTRACT FROM AUTHOR]

Background: In randomized controlled trials, participants cannot choose their preferred intervention delivery mode and thus might refuse to participate or not engage fully if assigned to a nonpreferred group. This might underestimate the true effectiveness of behavior-change interventions. Objective: To examine whether receiving interventions either matched or mismatched with participants' preferred delivery mode would influence effectiveness of a Web-based physical activity intervention. Methods: Adults (n = 863), recruited via email, were randomly assigned to one of three intervention delivery modes (text based, video based, or combined) and received fully automated, Internet-delivered personal advice about physical activity. Personalized intervention content, based on the theory of planned behavior and stages of change concept, was identical across groups. Online, self-assessed questionnaires measuring physical activity were completed at baseline, 1 week, and 1 month. Physical activity advice acceptability and website usability were assessed at 1 week. Before randomization, participants were asked which delivery mode they preferred, to categorize them as matched or mismatched. Time spent on the website was measured throughout the intervention. We applied intention-to-treat, repeated-measures analyses of covariance to assess group differences. Results: Attrition was high (575/863, 66.6%), though equal between groups (t[sub 863] =1.31, P =.19). At 1-month follow-up, 93 participants were categorized as matched and 195 as mismatched. They preferred text mode (493/803, 61.4%) over combined (216/803, 26.9%) and video modes (94/803, 11.7%). After the intervention, 20% (26/132) of matched-group participants and 34% (96/282) in the mismatched group changed their delivery mode preference. Time effects were significant for all physical activity outcomes (total physical activity: F[sub 2,801] = 5.07, P = .009; number of activity sessions: F[sub 2,801] = 7.52, P < .001; walking: F[sub 2,801] = 8.32, P < .001; moderate physical activity: F[sub 2,801] = 9.53, P < .001; and vigorous physical activity: F[sub 2,801] = 6.04, P = .002), indicating that physical activity increased over time for both matched and mismatched groups. Matched-group participants improved physical activity outcomes slightly more than those in the mismatched group, but interaction effects were not significant. Physical activity advice acceptability (content scale: t[sub 368] = .10, P = .92; layout scale: t[sub 368] = 1.53, P = .12) and website usability (layout scale: t[sub 426] = .05, P = .96; ease of use scale: t[sub 426] = .21, P = .83) were generally high and did not differ between the matched and mismatched groups. The only significant difference (t[sub 621] = 2.16, P = .03) was in relation to total time spent on the website: the mismatched group spent significantly more time on the website (14.4 minutes) than the matched group (12.1 minutes). Conclusion: Participants' preference regarding delivery mode may not significantly influence intervention outcomes. Consequently, allowing participants to choose their preferred delivery mode may not increase effectiveness of Web-based interventions. [ABSTRACT FROM AUTHOR]

Introduction: Appealing approaches to increasing physical activity levels are needed. This study evaluated whether a social and gamified smartphone app (Active Team) could be one such approach.Study Design: A 3-group cluster RCT compared the efficacy of Active Team with a basic self-monitoring app and waitlist control group.Setting/participants: Australian adults (N=444, mean age of 41 years, 74% female) were recruited in teams (n=121) and randomly assigned (1:1:1) to the Active Team (n=141, 39 teams), self-monitoring app (n=160, 42 teams), or waitlist group (n=143, 40 teams). Data were collected in 2016-2017, and analysis was conducted in 2018-2019.Intervention: Active Team is a 100-day app-based, gamified, online social networking physical activity intervention.Main Outcome Measures: The primary outcome was change in objective physical activity from baseline to 3-month follow-up. Secondary outcomes included objective physical activity at 9 months and self-reported physical activity, quality of life, depression, anxiety and stress, well-being, and engagement.Results: Mixed models indicated no significant differences in objective physical activity between groups at 3 (F=0.17, p=0.84; Cohen's d=0.03, 95% CI= -0.21, 0.26) or 9 months (F=0.23, p=0.92; d=0.06, 95% CI= -0.17, 0.29) and no significant differences for secondary outcomes of quality of life, depression, anxiety and stress, or well-being. Self-reported moderate-to-vigorous physical activity was significantly higher in the Active Team group at the 9-month follow-up (F=3.05, p=0.02; d=0.50, 95% CI=0.26, 0.73). Engagement was high; the Active Team group logged steps on an average of 72 (SD=35) days and used the social and gamified features an average of 89 (SD=118) times.Conclusions: A gamified, online social networking physical activity intervention did not change objective moderate-to-vigorous physical activity, though it did increase self-reported moderate-to-vigorous physical activity and achieve high levels of engagement. Future work is needed to understand if gamification, online social networks, and app-based approaches can be leveraged to achieve positive behavior change.Trial Registration: This study is registered at Australian and New Zealand Clinical Trial Registry (protocol: ANZCTR12617000113358). [ABSTRACT FROM AUTHOR]