Background Smartphone apps are a promising tool for delivering accessible and appealing physical activity interventions. Given the large growth of research in this field, there are now enough studies using the “gold standard” of experimental design—the randomized controlled trial design—and employing objective measurements of physical activity, to support a meta-analysis of these scientifically rigorous studies. Objective This systematic review and meta-analysis aimed to determine the effectiveness of smartphone apps for increasing objectively measured physical activity in adults. Methods A total of 7 electronic databases (EMBASE, EmCare, MEDLINE, Scopus, Sport Discus, The Cochrane Library, and Web of Science) were searched from 2007 to January 2018. Following the Population, Intervention, Comparator, Outcome and Study Design format, studies were eligible if they were randomized controlled trials involving adults, used a smartphone app as the primary or sole component of the physical activity intervention, used a no- or minimal-intervention control condition, and measured objective physical activity either in the form of moderate-to-vigorous physical activity minutes or steps. Study quality was assessed using a 25-item tool based on the Consolidated Standards of Reporting Trials checklist. A meta-analysis of study effects was conducted using a random effects model approach. Sensitivity analyses were conducted to examine whether intervention effectiveness differed on the basis of intervention length, target behavior (physical activity alone vs physical activity in combination with other health behaviors), or target population (general adult population vs specific health populations). Results Following removal of duplicates, a total of 6170 studies were identified from the original database searches. Of these, 9 studies, involving a total of 1740 participants, met eligibility criteria. Of these, 6 studies could be included in a meta-analysis of the effects of physical activity apps on steps per day. In comparison with the control conditions, smartphone apps produced a nonsignificant ( P =.19) increase in participants’ average steps per day, with a mean difference of 476.75 steps per day (95% CI −229.57 to 1183.07) between groups. Sensitivity analyses suggested that physical activity programs with a duration of less than 3 months were more effective than apps evaluated across more than 3 months ( P =.01), and that physical activity apps that targeted physical activity in isolation were more effective than apps that targeted physical activity in combination with diet ( P =.04). Physical activity app effectiveness did not appear to differ on the basis of target population. Conclusions This meta-analysis provides modest evidence supporting the effectiveness of smartphone apps to increase physical activity. To...

BackgroundEngagement in online programs is difficult to maintain. Gamification is the recent trend that offers to increase engagement through the inclusion of game-like features like points and badges, in non-game contexts. This review will answer the following question, ‘Are gamification strategies effective in increasing engagement in online programs?’MethodEight databases (Web of Science, PsycINFO, Medline, INSPEC, ERIC, Cochrane Library, Business Source Complete and ACM Digital Library) were searched from 2010 to the 28th of October 2015 using a comprehensive search strategy. Eligibility criteria was based on the PICOS format, where “population” included adults, “intervention” involved an online program or smart phone application that included at least one gamification feature. “Comparator” was a control group, “outcomes” included engagement and “downstream” outcomes which occurred as a result of engagement; and “study design” included experimental studies from peer-reviewed sources. Effect sizes (Cohens d and 95% confidence intervals) were also calculated.Results1017 studies were identified from database searches following the removal of duplicates, of which 15 met the inclusion criteria. The studies involved a total of 10,499 participants, and were commonly undertaken in tertiary education contexts. Engagement metrics included time spent (n = 5), volume of contributions (n = 11) and occasions visited to the software (n = 4); as well as downstream behaviours such as performance (n = 4) and healthy behaviours (n = 1). Effect sizes typically ranged from medium to large in direct engagement and downstream behaviours, with 12 out of 15 studies finding positive significant effects in favour of gamification.ConclusionGamification is effective in increasing engagement in online programs. Key recommendations for future research into gamification are provided. In particular, rigorous study designs are required to fully examine gamification’s effects and determine how to best achieve sustained engagement.

BackgroundThe success of a mobile phone app in changing health behavior is thought to be contingent on engagement, commonly operationalized as frequency of use.ObjectiveThis 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.MethodsEngagement 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.ResultsEngagement 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).ConclusionsTotal 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 RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12617000113358; https://www.anzctr.org.au/ACTRN12617000113358.aspx

BackgroundWearable activity trackers offer considerable promise for helping users to adopt healthier lifestyles. This study aimed to explore users’ experience of activity trackers, including usage patterns, sharing of data to social media, perceived behaviour change (physical activity, diet and sleep), and technical issues/barriers to use.MethodsA cross-sectional online survey was developed and administered to Australian adults who were current or former activity tracker users. Results were analysed descriptively, with differences between current and former users and wearable brands explored using independent samples t-tests, Mann-Whitney, and chi square tests.ResultsParticipants included 200 current and 37 former activity tracker users (total N = 237) with a mean age of 33.1 years (SD 12.4, range 18–74 years). Fitbit (67.5%) and Garmin devices (16.5%) were most commonly reported. Participants typically used their trackers for sustained periods (5–7 months) and most intended to continue usage. Participants reported they had improved their physical activity (51–81%) more commonly than they had their diet (14–40%) or sleep (11–24%), and slightly more participants reported to value the real time feedback (89%) compared to the long-term monitoring (78%). Most users (70%) reported they had experienced functionality issues with their devices, most commonly related to battery life and technical difficulties.ConclusionsResults suggest users find activity trackers appealing and useful tools for increasing perceived physical activity levels over a sustained period.Electronic supplementary materialThe online version of this article (10.1186/s12889-017-4888-1) contains supplementary material, which is available to authorized users.

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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. Electronic supplementary material The online version of this article (10.1186/s12889-019-7087-4) contains supplementary material, which is available to authorized users.

Background: Immobility is major contributor to poor outcomes for older people during hospitalisation with an acute medical illness. Yet currently there is no specific mobility guidance for this population, to facilitate sustainable changes in practice. This study aimed to generate draft physical activity (PA) and sedentary behaviour (SB) recommendations for older adults' during hospitalisation for an acute medical illness. Methods: A 4-Round online Delphi consensus survey was conducted. International researchers, medical/ nursing/physiotherapy clinicians, academics from national PA/SB guideline development teams, and patients were invited to participate. Round 1 sought responses to open-ended questions. In Rounds 2-3, participants rated the importance of items using a Likert scale (1-9); consensus was defined a priori as: ≥70% of respondents rating an item as "critical" (score ≥ 7) and ≤ 15% of respondents rating an item as "not important" (score ≤ 3). Round 4 invited participants to comment on draft statements derived from responses to Rounds 1-3; Round 4 responses subsequently informed final drafting of recommendations. Results: Forty-nine people from nine countries were invited to each Round; response rates were 94, 90, 85 and 81% from Rounds 1-4 respectively. 43 concepts (items) from Rounds 2 and 3 were incorporated into 29 statements under themes of PA, SB, people and organisational factors in Round 4. Examples of the final draft recommendations (being the revised version of statements with highest participant endorsement under each theme) were: "some PA is better than none", "older adults should aim to minimise long periods of uninterrupted SB during waking hours while hospitalised", "when encouraging PA and minimising SB, people should be culturally responsive and mindful of older adults' physical and mental capabilities" and "opportunities for PA and minimising SB should be incorporated into the daily care of older adults with a focus on function, independence and activities of daily living".

IntroductionThis study evaluated the psychometric properties of the PERMA Profiler, a 15-item self-report measurement tool designed to measure Seligman’s five pillars of wellbeing: Positive emotions, Relationships, Engagement, Meaning, and Accomplishment.MethodsAustralian adults (N = 439) completed the PERMA Profiler and measures of physical and mental health (SF-12), depression, anxiety, stress (DASS 21), subjective physical activity (Active Australia Survey), and objective activity and sleep (GENEActiv accelerometer). Internal consistency was examined using Cronbach’s alpha and associations between theoretically related constructs examined using Pearson’s correlation. Model fit in comparison with theorised models was examined via Confirmatory Factor Analysis.ResultsResults indicated acceptable internal consistency for overall PERMA Profiler scores and all subscales (α range = 0.80–0.93) except Engagement (α = 0.66). Moderate associations were found between PERMA Profiler wellbeing scores with subjective constructs (e.g. depression, anxiety, stress; r = -0.374 - -0.645, p = <0.001) but not objective physical activity or sleep. Data failed to meet model fit criteria for neither the theorised five-factor nor an alternative single-factor structure.ConclusionsFindings were mixed, providing strong support for the scale’s internal consistency and moderate support for congervent and divergent validity, albeit not in comparison to objectively captured activity outcomes. We could not replicate the theorised data structure nor an alternative, single factor structure. Results indicate insufficient psychometric properties of the PERMA Profiler.