Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Smartphone apps are a promising tool for delivering accessible and appealing physical activity interventions. Objective: This systematic review and meta-analysis aimed to determine the effectiveness of smartphone apps for increasing objectively measured physical activity in adults. Methods: Seven electronic databases (Embase, Emcare, Medline, Scopus, Sport Discus, The Cochrane Library and Web of Science) were searched from 2007 to January 2018. Following the PICOS format, studies were eligible if they were randomised-controlled trials involving adults, used a smartphone app as the primary or stand-alone component of the physical activity intervention, used a no or minimal intervention control condition, and measured objective physical activity either in the form of minutes of moderate to vigorous physical activity (MVPA) or steps. Study quality was assessed using a 25-item tool based on the CONSORT 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 behaviour (physical activity alone, vs physical activity in combination with other health behaviours) or target population (general adult population vs specific health populations). Results: Following the removal of duplicates, a total of 6170 studies were identified from the original database search. Nine studies, involving a total of 1740 participants, were identified as meeting eligibility criteria for inclusion in this review. Of these, six studies could be included in a meta-analysis of the effects of physical activity apps on steps/day. In comparison to the control conditions, smartphone apps produced a non-significant (P = .19) increase in participants’ average steps per day, with mean difference between groups of 476.75 steps/day (95% CI = -229.57 to 1183.07). Sensitivity analyses suggested that physical activity programs with a duration < 3 months were more effective than apps evaluated across > 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 date, apps have been most effective in the short term (e.g. up to 3 months). Future research is needed to understand the time course of intervention effects and to investigate strategies to sustain intervention effects over time.

Engagement 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?’ Eight databases (Web of Science, PsycINFO, Medline, INSPEC, ERIC, Cochrane Library, Business Source Complete and ACM Digital Library) were searched from 2010 to the 28^th 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. 1017 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. Gamification 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.

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

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. 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. 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. 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.

The market for wearable activity trackers has grown prolifically in recent years, with increasing numbers of consumers using them to track, measure, and ideally improve their health and wellbeing. Empirical evidence tends to support wearables as valid, reliable, and effective health behaviour change tools, however little research has been conducted to understand experiential aspects of the devices, particularly thier effects on users’ psychological wellbeing and affect. This study addresses this literature gap by exploring wearable users’ affective responses to their devices and how these relate to personality traits and individual differences. Data were collected from adult wearable users (N = 237) via an online survey that assessed participant demographic characteristics, personality trait profiles, and experiences of negative (guilt, self-consciousness, & anxiety) and positive affect (empowerment, motivation, & accountability) related to their wearable both during wear, and when unable to wear (e.g. if the battery ran flat). Outcomes were analysed descriptively and general linear models used to examine associations between affect scores with personality traits and individual differences. Both current and previous wearable users experience more positive than negative affect related to their device whilst they were wearing it (p = <.001). When prevented from wearing their device, however, this pattern was reversed with most participants reporting stronger negative than positive affect (p = <.001). These patterns were generally consistent across demographic sub-groups and personality trait profiles, although conscientiousness and openness to experience were independently and positively associated with affect during wear (p = .001). Results suggest that using a wearable is a positive experience for users with little risk of negative psychological consequences. Whilst experiences of negative affect were uncommon, individuals low in conscientiousness or openness to experience are at greater risk of negative affect and all users may experience negative affect such as anxiety or frustration when prevented from wearing their device. Findings contribute to mounting evidence of wearables’ safety and appeal as health behaviour tools and highlight the importance of examining psychological and experiential aspects of activity tracking.