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BACKGROUND: Technological advances have seen a burgeoning industry for accelerometer-based wearable activity monitors targeted at the consumer market. The purpose of this study was to determine the convergent validity of a selection of consumer-level accelerometer-based activity monitors. METHODS: 21 healthy adults wore seven consumer-level activity monitors (Fitbit One, Fitbit Zip, Jawbone UP, Misfit Shine, Nike Fuelband, Striiv Smart Pedometer and Withings Pulse) and two research-grade accelerometers/multi-sensor devices (BodyMedia SenseWear, and ActiGraph GT3X+) for 48-hours. Participants went about their daily life in free-living conditions during data collection. The validity of the consumer-level activity monitors relative to the research devices for step count, moderate to vigorous physical activity (MVPA), sleep and total daily energy expenditure (TDEE) was quantified using Bland-Altman analysis, median absolute difference and Pearson’s correlation. RESULTS: All consumer-level activity monitors correlated strongly (r > 0.8) with research-grade devices for step count and sleep time, but only moderately-to-strongly for TDEE (r = 0.74-0.81) and MVPA (r = 0.52-0.91). Median absolute differences were generally modest for sleep and steps (<10% of research device mean values for the majority of devices) moderate for TDEE (<30% of research device mean values), and large for MVPA (26-298%). Across the constructs examined, the Fitbit One, Fitbit Zip and Withings Pulse performed most strongly. CONCLUSIONS: In free-living conditions, the consumer-level activity monitors showed strong validity for the measurement of steps and sleep duration, and moderate valid for measurement of TDEE and MVPA. Validity for each construct ranged widely between devices, with the Fitbit One, Fitbit Zip and Withings Pulse being the strongest performers.

Estimates of adults’ moderate-to-vigorous physical activity (MVPA) based on self-report are generally higher than estimates derived from criterion measures. This study examines a possible explanation for part of this discrepancy: the cutpoint bias hypothesis. This hypothesis proposes that inter- and intra-individual variability in energy expenditure, combined with the fact that adults perform a high proportion of daily activities at or just above the traditional 3 MET cutpoint, result in systematic over-estimates of MVPA. Cross-sectional. Time-use recalls (n = 6862) were collected using the Multimedia Activity Recall for Children and Adults from 2210 adults (1215 female, age 16–93 years) from 16 studies conducted in Australia and New Zealand between 2008-2017. Minutes spent in MVPA were estimated using models with varying levels of intra- and inter-individual (total variability) Unadjusted (0% total variability), Low (11.9%), Best Guess (20.7%), and High (30.0%). In the Unadjusted model, participants accumulated an average of 129 (standard deviation 127) min/day of MVPA. Estimated MVPA was 98 (110), 99 (107) and 108 (107) min/day in the Low, Best Guess and High variability models, respectively, with intra-class correlation coefficients with the Unadjusted model ranging from 0.78 to 0.83. These findings support the hypothesis of a cutpoint bias, which probably contributes to the large disparities seen between self-reported and criterion measures of MVPA. Future studies are needed to confirm these findings using other self-report instruments and in other populations.

This 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. Australian 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. Results 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. Findings 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.

Background Recently, a small number of studies have suggested that gains in fitness and reductions in body fat achieved during the school term are reversed or stagnate during the holiday period. This may be associated with changed activity patterns. The aim of this study was to compare 24-h activity compositions between school and holiday periods in Australian children. Methods The participants in this study were 366 children (53% female, 13.4 ± 2.3 years) who were a subgroup of the 2007 Australian National Children’s Nutrition and Physical Activity Survey. Each child recalled use of time on at least one school day, one weekend day and one holiday using the Multimedia Activity Recall for Children and Adults. Composite “in-term” and “holiday” use-of-time profiles were generated by weighting school days by 5, and weekends by 2 where data were available. Difference between holiday and in-term time use was assessed using a compositional multivariate linear model for repeated measures. Subsequent models tested for interaction between time of measurement and socio-economic status or body mass index. Results Time use was significantly different between holidays and in-term days (F = 103, p  < 0.0001). On holidays, children accumulated 140 min less School-related time, compensated by sleeping 40 min longer, 58 min more Screen Time, and 35 min more Domestic/Social time. Children spent 10 min less in vigorous physical activity, and although sitting time was 33 min/day less during holidays, estimated total daily energy expenditure (TDEE) was 5.4% lower. Differences between holiday and in-term activity compositions did not vary by parental education (F = 1.2, p  = 0.25), postcode-level socio-economic status (F = 0.9, p  = 0.56) or weight status (F = 1.7, p  = 0.07). Conclusions In this subsample of a nationally representative survey of Australian children, holidays were characterised by longer sleep and higher TV and videogame time, lower vigorous activity and lower TDEE. Uncompensated by dietary adjustments, these differences would result in an accumulation of about 650 g of fat over a six-week holiday period. Holiday activity patterns may be a promising focus for obesity prevention efforts.

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.

Background Overweight and obese children and adolescents face many physical and psychosocial hardships. Resistance training is a modality of exercise which allows this at-risk group to excel and therefore has the potential to positively affect not only their physical but also psychosocial health. Objective To systematically review and meta-analyse the peer-reviewed literature to determine the effect of resistance training on the strength, body composition and psychosocial status of overweight and/or obese children and/or adolescents. Data Sources Relevant databases (MEDLINE, Embase, Scopus, Web of Science, SPORTDiscus, CINAHL, PsycINFO, Cochrane library, ProQuest) were searched up to and including 30 January 2013. Study Selection Included studies ( n  = 40, from the 2,247 identified) were randomised controlled trials (RCTs), non-randomised controlled trials (NRCTs) and uncontrolled trials (UCTs) which had run an exercise intervention, with a resistance training component, for overweight and/or obese children and/or adolescents, and which had examined the effect of resistance training on either strength, body composition or psychosocial outcomes. Study Appraisal and Synthesis Methods Studies were initially critically appraised for risk of bias by the lead author, following which both co-authors critically appraised five randomly selected studies to assess reliability. Results Randomised controlled trials and NRCTs were analysed separately from UCTs. To determine the overall intervention effect for each outcome variable for each study design group, standardised mean differences were calculated with each individual study/data set weighted by the inverse of the pooled variance. The overall intervention effect reported for RCTs and NRCTs was relative to the control group whereas the effect reported for UCTs shows an overall post-intervention effect. Subgroup analyses, which determined whether the overall intervention effect was influenced by intervention type, training volume, age, sex, risk of bias or study design (for RCT/NRCT group only), were run using the same summary measure. Typically, resistance training had very small to small effects on body composition and moderate to large effects on strength in favour of the intervention. However, the magnitude and direction of the effect of resistance training on psychological outcomes are still unclear given the limited number of studies which looked at psychosocial outcomes and the inconclusive results shown by this review. Uncontrolled trials typically showed larger intervention effects than RCTs and NRCTs; however, these results may be greatly influenced by maturational changes rather than the intervention itself. Limitations The included studies employed a number of different exercise intervention types (e.g. resistance training, resistance plus aerobic training etc.) that ranged from 6 to 52 weeks in duration. Studies also employed a number of different methodologies to assess similar outcome measures (e.g. dual energy X-ray absorptiometry versus skinfolds to assess body composition; one-repetition maximum testing versus hand grip strength to assess strength). However, by completing subgroup analyses and using a standardised summary measure these limitations have been accounted for. Conclusion While the effect of resistance training on the body composition and strength of overweight and obese children and adolescents is clear, given the paucity of conclusive data more studies are needed to fully understand the effect of resistance training on the psychosocial status of this population.

Background How time is allocated influences health. However, any increase in time allocated to one behaviour must be offset by a decrease in others. Recently, studies have used compositional data analysis (CoDA) to estimate the associations with health when reallocating time between different behaviours. The aim of this scoping review was to provide an overview of studies that have used CoDA to model how reallocating time between different time-use components is associated with health. Methods A systematic search of four electronic databases (MEDLINE, Embase, Scopus, SPORTDiscus) was conducted in October 2022. Studies were eligible if they used CoDA to examine the associations of time reallocations and health. Reallocations were considered between movement behaviours (sedentary behaviour (SB), light physical activity (LPA), moderate-to-vigorous physical activity (MVPA)) or various activities of daily living (screen time, work, household chores etc.). The review considered all populations, including clinical populations, as well as all health-related outcomes. Results One hundred and three studies were included. Adiposity was the most commonly studied health outcome (n = 41). Most studies (n = 75) reported reallocations amongst daily sleep, SB, LPA and MVPA. While other studies reported reallocations amongst sub-compositions of these (work MVPA vs. leisure MVPA), activity types determined by recall (screen time, household chores, passive transport etc.) or bouted behaviours (short vs. long bouts of SB). In general, when considering cross-sectional results, reallocating time to MVPA from any behaviour(s) was favourably associated with health and reallocating time away from MVPA to any behaviour(s) was unfavourably associated with health. Some beneficial associations were seen when reallocating time from SB to both LPA and sleep; however, the strength of the association was much lower than for any reallocations involving MVPA. However, there were many null findings. Notably, most of the longitudinal studies found no associations between reallocations of time and health. Some evidence also suggested the context of behaviours was important, with reallocations of leisure time toward MVPA having a stronger favourable association for health than reallocating work time towards MVPA. Conclusions Evidence suggests that reallocating time towards MVPA from any behaviour(s) has the strongest favourable association with health, and reallocating time away from MVPA toward any behaviour(s) has the strongest unfavourable association with health. Future studies should use longitudinal and experimental study designs, and for a wider range of outcomes.

Background The ActivityStat hypothesis suggests that when physical activity is increased or decreased in one domain, there will be a compensatory change in another domain, in order to maintain an overall stable level of physical activity or energy expenditure over time. The ActivityStat debate is gaining momentum in the literature and most of the research to date is based on observational studies. Objective The objective of this paper is to conceptually clarify the ActivityStat hypothesis and to examine the experimental research aiming to demonstrate or refute compensation using a systematic review process. Methods A systematic review was conducted using electronic database searches with the aim of detecting studies experimentally investigating the ActivityStat hypothesis or compensation in physical activity or energy expenditure. Included studies were critically appraised using a specifically designed tool to address the conceptual considerations of the ActivityStat hypothesis. Results Searches identified 28 studies that met the inclusion criteria. Publications spanned 26 years and had multiple methodological approaches, including randomized and non-randomized controlled trials, crossover designs, cluster randomized controlled trials and pre-post trials. Populations of the included studies ranged from children, to adults and the elderly, across a range of weight statuses and used both aerobic, resistance and mixed-exercise interventions. The timeframe of interventions ranged from 1 day to 4 years and outcomes were measured using doubly labelled water, accelerometry, heart rate monitoring, resting metabolic rate, indirect calorimetry, pedometry, subjective recall questionnaire and the activity-related time index. Fifteen of 28 included studies provided evidence of compensation, while 13 did not. Subgroup analyses by population, type and duration of intervention, weight status and study quality also showed mixed findings. Conclusion There is a substantial body of experimental literature investigating compensation that has largely been overlooked in the ActivityStat debate. However, this evidence is currently inconclusive and lacks a cohesive approach to the question of an ActivityStat. Recommendations for the design of future experimental research investigating the ActivityStat hypothesis are presented.

The success of a mobile phone app in changing health behavior is thought to be contingent on engagement, commonly operationalized as frequency of use. 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. 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. 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; F =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; F =6.385; P=.01) than younger users (mean 155.6, 95% CI 128.5-182.6). Super users were 4.6 years older (t =3.6; P<.001) and less likely to have a BMI in the obese range (χ =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 (F =4.76; P=.03). 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. Australian New Zealand Clinical Trials Registry ACTRN12617000113358; https://www.anzctr.org.au/ACTRN12617000113358.aspx.

To determine the reliability and validity of the Multimedia Activity Recall for Children and Adults (MARCA) in people with chronic obstructive pulmonary disease (COPD). People with COPD and their carers completed the Multimedia Activity Recall for Children and Adults (MARCA) for four, 24-hour periods (including test-retest of 2 days) while wearing a triaxial accelerometer (Actigraph GT3X+®), a multi-sensor armband (Sensewear Pro3®) and a pedometer (New Lifestyles 1000®). Self reported activity recalls (MARCA) and objective activity monitoring (Accelerometry) were recorded under free-living conditions. 24 couples were included in the analysis (COPD; age 74.4 ± 7.9 yrs, FEV1 54 ± 13% Carer; age 69.6 ± 10.9 yrs, FEV1 99 ± 24%). Not applicable. Test-retest reliability was compared for MARCA activity domains and different energy expenditure zones. Validity was assessed between MARCA-derived physical activity level (in metabolic equivalent of task (MET) per minute), duration of moderate to vigorous physical activity (min) and related data from the objective measurement devices. Analysis included intra-class correlation coefficients (ICC), Bland-Altman analyses, paired t-tests (p) and Spearman's rank correlation coefficients (rs). Reliability between occasions of recall for all activity domains was uniformly high, with test-retest correlations consistently >0.9. Validity correlations were moderate to strong (rs = 0.43-0.80) across all comparisons. The MARCA yields comparable PAL estimates and slightly higher moderate to vigorous physical activity (MVPA) estimates. In older adults with chronic illness, the MARCA is a valid and reliable tool for capturing not only the time and energy expenditure associated with physical and sedentary activities but also information on the types of activities.