Measuring and influencing physical activity with Smartphone technology : a systematic review

Background Rapid developments in technology have encouraged the use of smartphones in physical activity research, although little is known regarding their effectiveness as measurement and intervention tools. Objective This study systematically reviewed evidence on smartphones and their viability for measuring and influencing physical activity. Data Sources Research articles were identified in September 2013 by literature searches in Web of Knowledge, PubMed, PsycINFO, EBSCO, and ScienceDirect. Study Selection The search was restricted using the terms (physical activity OR exercise OR fitness) AND (smartphone* OR mobile phone* OR cell phone*) AND (measurement OR intervention). Reviewed articles were required to be published in international academic peer-reviewed journals, or in full text from international scientific conferences, and focused on measuring physical activity through smartphone processing data and influencing people to be more active through smartphone applications. Study Appraisal and Synthesis Methods Two reviewers independently performed the selection of articles and examined titles and abstracts to exclude those out of scope. Data on study characteristics, technologies used to objectively measure physical activity, strategies applied to influence activity; and the main study findings were extracted and reported. Results A total of 26 articles (with the first published in 2007) met inclusion criteria. All studies were conducted in highly economically advantaged countries; 12 articles focused on special populations (e.g. obese patients). Studies measured physical activity using native mobile features, and/or an external device linked to an application. Measurement accuracy ranged from 52 to 100 % (n = 10 studies). A total of 17 articles implemented and evaluated an intervention. Smartphone strategies to influence physical activity tended to be ad hoc, rather than theory-based approaches; physical activity profiles, goal setting, real-time feedback, social support networking, and online expert consultation were identified as the most useful strategies to encourage physical activity change. Only five studies assessed physical activity intervention effects; all used step counts as the outcome measure. Four studies (three pre–post and one comparative) reported physical activity increases (12–42 participants, 800–1,104 steps/day, 2 weeks–6 months), and one case-control study reported physical activity maintenance (n = 200 participants; >10,000 steps/day) over 3 months. Limitations Smartphone use is a relatively new field of study in physical activity research, and consequently the evidence base is emerging. Conclusions Few studies identified in this review considered the validity of phone-based assessment of physical activity. Those that did report on measurement properties found average-to-excellent levels of accuracy for different behaviors. The range of novel and engaging intervention strategies used by smartphones, and user perceptions on their usefulness and viability, highlights the potential such technology has for physical activity promotion. However, intervention effects reported in the extant literature are modest at best, and future studies need to utilize randomized controlled trial research designs, larger sample sizes, and longer study periods to better explore the physical activity measurement and intervention capabilities of smartphones.

Effects of a pediatric weight management program with and without active video games

Importance Active video games may offer an effective strategy to increase physical activity in overweight and obese children. However, the specific effects of active gaming when delivered within the context of a pediatric weight management program are unknown. Objective To evaluate the effects of active video gaming on physical activity and weight loss in children participating in an evidence-based weight management program delivered in the community. Design, Setting, and Participants Group-randomized clinical trial conducted during a 16-week period in YMCAs and schools located in Massachusetts, Rhode Island, and Texas. Seventy-five overweight or obese children (41 girls [55%], 34 whites [45%], 20 Hispanics [27%], and 17 blacks [23%]) enrolled in a community-based pediatric weight management program. Mean (SD) age of the participants was 10.0 (1.7) years; body mass index (BMI) z score, 2.15 (0.40); and percentage overweight from the median BMI for age and sex, 64.3% (19.9%). Interventions All participants received a comprehensive family-based pediatric weight management program (JOIN for ME). Participants in the program and active gaming group received hardware consisting of a game console and motion capture device and 1 active game at their second treatment session and a second game in week 9 of the program. Participants in the program-only group were given the hardware and 2 games at the completion of the 16-week program. Main Outcomes and Measures Objectively measured daily moderate-to-vigorous and vigorous physical activity, percentage overweight, and BMI z score. Results Participants in the program and active gaming group exhibited significant increases in moderate-to-vigorous (mean [SD], 7.4 [2.7] min/d) and vigorous (2.8 [0.9] min/d) physical activity at week 16 (P < .05). In the program-only group, a decline or no change was observed in the moderate-to-vigorous (mean [SD] net difference, 8.0 [3.8] min/d; P = .04) and vigorous (3.1 [1.3] min/d; P = .02) physical activity. Participants in both groups exhibited significant reductions in percentage overweight and BMI z scores at week 16. However, the program and active gaming group exhibited significantly greater reductions in percentage overweight (mean [SD], −10.9% [1.6%] vs −5.5% [1.5%]; P = .02) and BMI z score (−0.25 [0.03] vs −0.11 [0.03]; P < .001). Conclusions and Relevance Incorporating active video gaming into an evidence-based pediatric weight management program has positive effects on physical activity and relative weight.

A systematic review of community-based interventions for emerging zoonotic diseases in Southeast Asia

Background Southeast Asia has been at the epicentre of recent epidemics of emerging and re-emerging zoonotic diseases. Community-based surveillance and control interventions have been heavily promoted but the most effective interventions have not been identified. Objectives This review evaluated evidence for the effectiveness of community-based surveillance interventions at monitoring and identifying emerging infectious disease; the effectiveness of community-based control interventions at reducing rates of emerging infectious disease; and contextual factors that influence intervention effectiveness. Inclusion criteria Participants Communities in Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand and Viet Nam. Types of intervention(s) Non-pharmaceutical, non-vaccine, and community-based surveillance or prevention and control interventions targeting rabies, Nipah virus , dengue, SARS or avian influenza. Types of outcomes Primary outcomes: measures: of infection or disease; secondary outcomes: measures of intervention function. Types of studies Original quantitative studies published in English. Search strategy Databases searched (1980 to 2011): PubMed, CINAHL, ProQuest, EBSCOhost, Web of Science, Science Direct, Cochrane database of systematic reviews, WHOLIS, British Development Library, LILACS, World Bank (East Asia), Asian Development Bank. Methodological quality Two independent reviewers critically appraised studies using standard Joanna Briggs Institute instruments. Disagreements were resolved through discussion. Data extraction A customised tool was used to extract quantitative data on intervention(s), populations, study methods, and primary and secondary outcomes; and qualitative contextual information or narrative evidence about interventions. Data synthesis Data was synthesised in a narrative summary with the aid of tables. Meta-analysis was used to statistically pool quantitative results. Results Fifty-seven studies were included. Vector control interventions using copepods, environmental cleanup and education are effective and sustainable at reducing dengue in rural and urban communities, whilst insecticide spraying is effective in urban outbreak situations. Community-based surveillance interventions can effectively identify avian influenza in backyard flocks, but have not been broadly applied. Outbreak control interventions for Nipah virus and SARS are effective but may not be suitable for ongoing control. Canine vaccination and education is more acceptable than culling, but still fails to reach coverage levels required to effectively control rabies. Contextual factors were identified that influence community engagement with, and ultimately effectiveness of, interventions. Conclusion Despite investment in community-based disease control and surveillance in Southeast Asia, published evidence evaluating interventions is limited in quantity and quality. Nonetheless this review identified a number of effective interventions, and several contextual factors influencing effectiveness. Identification of the best programs will require comparative evidence of effectiveness acceptability, cost-effectiveness and sustainability.

Life transitions and changing physical activity patterns in young women

Background Physical activity (PA) patterns are likely to change in young adulthood in line with changes in lifestyle that occur in the transition from adolescence to adulthood. The aim of this study was to ascertain whether key life events experienced by young women in their early twenties are associated with increasing levels of inactivity. Methods This was a 4-year follow-up of 7281 participants (aged 18 to 23 years at baseline) in the Australian Longitudinal Study of Women’s Health, with self-reported measures of PA, life events, body mass index (BMI), and sociodemographic variables. Results The cross-sectional data indicated no change in PA between baseline (57% “active”) and follow-up (56% “active”). However, for almost 40% of the sample, PA category changed between baseline and follow-up, with approximately 20% of the women changing from being “active” to “inactive,” and another 20% changing from being “inactive” to “active.” After adjustment for age, other sociodemographic variables, BMI, and PA at baseline, women who reported getting married, having a first or subsequent child, or beginning paid work were more likely to be inactive at follow-up than those who did not report these events. Conclusions The results suggest that life events such as getting married, having children, and starting work are associated with decreased levels of PA in young adult women. Strategies are needed to promote maintenance of activity at the time when most women experience these key life-stage transitions.

Mediators of physical activity behavior change among women with young children

Background Women with children are less likely to engage in adequate physical activity (PA) than women without children. This study aimed to evaluate the efficacy of two strategies for promoting increased PA among mothers of preschool-aged children, and to explore the mediators of any resulting change in PA behavior. Design Controlled intervention trial incorporating repeated data collection from 554 women, randomized to one of three experimental conditions. Intervention Group 1 served as a control, while women in Groups 2 and 3 were given print information about overcoming PA barriers. Women in Group 3 were also invited to discuss the development of local strategies for the promotion of PA among mothers of young children. The primary strategies included increasing partner support, social advocacy, and capacity building, and were implemented through collaboration among participants, researchers, and community organizations. Main Outcome Measures Adequate physical activity (PA), self-efficacy (SE) and partner support (PS). Results: Following the intervention, women in Group 3 were significantly more likely to meet guidelines for PA than controls (odds ratio [OR]=1.71, confidence interval [CI]=1.05–2.77)] after controlling for age and PA at baseline. After controlling for baseline PA, residualized change in SE (OR=1.86, CI=1.17–2.94) and PS (OR=2.29, CI=1.46–3.58) significantly predicted meeting guidelines. After controlling for residual change in PS and SE, the significant intervention effect was attenuated (Group 3 OR=1.40, CI=0.76–2.36), indicating that partner support and self-efficacy may be mediators of physical activity behavior change. Conclusions The findings indicate that community participation approaches that facilitate increased self-efficacy and partner support can be effective in increasing PA among mothers of young children.

Promoting physical activity to older adults : a preliminary evaluation of three general practice-based strategies

The aim of this study was to explore the feasibility of an exercise scientist (ES) working in general practice to promote physical activity (PA) to 55 to 70 year old adults. Participants were randomised into one of three groups: either brief verbal and written advice from a general practitioner (GP) (G1, N=9); or individualised counselling and follow-up telephone calls from an ES, either with (G3, N=8) or without a pedometer (G2, N=11). PA levels were assessed at week 1, after the 12-wk intervention and again at 24 weeks. After the 12-wk intervention, the average increase in PA was 116 (SD=237) min/wk; N=28, p < 0.001. Although there were no statistically significant between-group differences, the average increases in PA among G2 and G3 participants were 195 (SD=207) and 138 (SD=315) min/wk respectively, compared with no change (0.36, SD=157) in G1. After 24 weeks, average PA levels remained 56 (SD=129) min/wk higher than in week 1. The small numbers of participants in this feasibility study limit the power to detect significant differences between groups, but it would appear that individualised counselling and follow-up contact from an ES, with or without a pedometer, can result in substantial changes in PA levels. A larger study is now planned to confirm these findings.

Physical activity and population health outcomes

SMA members Neville Owen, Adrian Bauman, Wendy Brown and Stewart Trost have recently been awarded two NHMRC grants for research which will focus on understanding and influencing physical activity to improve population health outcomes. They were awarded under the Capital Building for Population Health scheme and the Program Grants scheme. The total value of the grants is 86.5 million over five years. The new grants will allow the researchers to conduct rigorous behavioural and epidemiological research which will inform the development of innovative primary and secondary prevention initiatives and determine their effectiveness. This is important, because physical activity is significantly implicated in the prevention and management of established chronic health problems such as cardiovascular disease, type 2 diabetes, osteoporosis and some forms of cancer. It also has a key role to play in addressing the growing epidemic of childhood and adult obesity, and in the maintenance of functional well-being with age. However, in recent years, physical activity levels in Australia have declined, indicating that the net sum of all our efforts to encourage physical activity participation require renewed and innovative efforts. The proposed research programs will be based on the researchers' cross-disciplinary backgrounds in exercise physiology, psychology, health promotion and epidemiology, and will be integrated across four main domains:..

Validation of a 24-h physical activity recall in indigenous and non-indigenous Australian adolescents

The purpose of this study was to evaluate the concurrent validity of a modified version of the widely used previous day physical activity recall (PDPAR24) self-report instrument in a diverse sample of Australian adolescents comprising Aboriginal and Torres Strait Islanders (A&TSI) and non-indigenous high school students. A sample of 63 A&TSI and 59 non-indigenous high school students (N = 122) from five public secondary schools participated in the study. Participants completed the PDPAR-24 after wearing a seated electronic pedometer on the previous day. Significant positive correlations were observed between the self-reported physical activity variables (mean MET level, blocks of vigorous activity, and blocks of moderate-to-vigorous physical activity) and 24-h step counts. Validity coefficients (rho) ranged from 0.29 to 0.34 (p<0.05). A significant inverse correlation was observed for self-reported screen time and 24-h step count (rho = -0.19, p<0.05). Correlations for A&TSI students were equal to or greater than those observed for non-indigenous students. The PDPAR-24 instrument is a quick, unobtrusive, and cost-effective assessment tool. that would be useful for evaluating physical activity and sedentary behaviour in population-based studies. (C) 2006 Sports Medicine Australia.

Comparison of three generations of ActiGraph (TM) activity monitors in children and adolescents

In this study, we evaluated agreement among three generations of ActiGraph (TM) accelerometers in children and adolescents. Twenty-nine participants (mean age = 14.2 +/- 3.0 years) completed two laboratory-based activity sessions, each lasting 60 min. During each session, participants concurrently wore three different models of the ActiGraph (TM) accelerometers (GT1M, GT3X, GT3X+). Agreement among the three models for vertical axis counts, vector magnitude counts, and time spent in moderate-to-vigorous physical exercise (MVPA) was evaluated by calculating intraclass correlation coefficients and Bland-Altman plots. The intraclass correlation coefficient for total vertical axis counts, total vector magnitude counts, and estimated MVPA was 0.994 (95% CI = 0.989-0.996), 0.981 (95% CI = 0.969-0.989), and 0.996 (95% CI = 0.989-0.998), respectively. Inter-monitor differences for total vertical axis and vector magnitude counts ranged from 0.3% to 1.5%, while inter-monitor differences for estimated MVPA were equal to or close to zero. On the basis of these findings, we conclude that there is strong agreement between the GT1M, GT3X, and GT3X+ activity monitors, thus making it acceptable for researchers and practitioners to use different ActiGraph (TM) models within a given study.

Tracking of physical activity in young children

The purpose of this study was to determine whether physical activity behavior tracks during early childhood. Forty-seven children (22 males, 25 females) aged 3-4 yr at the beginning of the study were followed over a 3-yr period. Heart rates were measured at least 2 and up to 4 d . yr(-1) with a Quantum XL Telemetry heart rate monitor. Physical activity was quantified as the percentage of observed minutes between 3:00 and 6:00 p.m. during which heart rate was 50% or more above individual resting heart rate (PAHR-50 Index). Tracking of physical activity was analyzed using Pearson and Spearman correlations. Yearly PAHR-50 index tertiles were created and examined for percent agreement and Cohen's kappa. Repeated measures ANOVA was used to calculate the intraclass correlation coefficient across the 3 yr of the study. Spearman rank order correlations ranged from 0.57 to 0.66 (P < 0.0001). Percent agreement ranged from 49% to 62%. The intraclass R for the 3 yr was 0.81. It was concluded that physical activity behavior tends to track during early childhood.

Comparison of accelerometer cut points for predicting activity intensity in youth

The absence of comparative validity studies has prevented researchers from reaching consensus regarding the application of intensity-related accelerometer cut points for children and adolescents. PURPOSE This study aimed to evaluate the classification accuracy of five sets of independently developed ActiGraph cut points using energy expenditure, measured by indirect calorimetry, as a criterion reference standard. METHODS A total of 206 participants between the ages of 5 and 15 yr completed 12 standardized activity trials. Trials consisted of sedentary activities (lying down, writing, computer game), lifestyle activities (sweeping, laundry, throw and catch, aerobics, basketball), and ambulatory activities (comfortable walk, brisk walk, brisk treadmill walk, running). During each trial, participants wore an ActiGraph GT1M, and VO 2 was measured breath-by-breath using the Oxycon Mobile portable metabolic system. Physical activity intensity was estimated using five independently developed cut points: Freedson/Trost (FT), Puyau (PU), Treuth (TR), Mattocks (MT), and Evenson (EV). Classification accuracy was evaluated via weighted κ statistics and area under the receiver operating characteristic curve (ROC-AUC). RESULTS Across all four intensity levels, the EV (κ = 0.68) and FT (κ = 0.66) cut points exhibited significantly better agreement than TR (κ = 0.62), MT (κ = 0.54), and PU (κ = 0.36). The EV and FT cut points exhibited significantly better classification accuracy for moderate-to vigorous-intensity physical activity (ROC-AUC = 0.90) than TR, PU, or MT cut points (ROC-AUC = 0.77-0.85). Only the EV cut points provided acceptable classification accuracy for all four levels of physical activity intensity and performed well among children of all ages. The widely applied sedentary cut point of 100 counts per minute exhibited excellent classification accuracy (ROC-AUC = 0.90). CONCLUSIONS On the basis of these findings, we recommend that researchers use the EV ActiGraph cut points to estimate time spent in sedentary, light-, moderate-, and vigorous-intensity activity in children and adolescents. Copyright © 2011 by the American College of Sports Medicine.

Using objective physical activity measures with youth : How many days of monitoring are needed?

Purpose The purpose of this study was to establish the minimal number of days of monitoring required for accelerometers to assess usual physical activity in children. Methods A total of 381 students (189 M, 192 F) wore a CSA 7164 uniaxial accelerometer for seven consecutive days. To examine age-related trends students were grouped as follows: Group I: grades 1-3 (N = 92); Group II: grades 4-6 (N = 98); Group III: grades 7-9 (N = 97); Group IV: grades 10-12 (N = 94). Average daily time spent in moderate-to-vigorous physical activity (MVPA) was calculated from minute-by-minute activity counts using the regression equation developed by Freedson et al. (1997). Results Compared with adolescents in grades 7 to 12, children in grades 1 to 6 exhibited less day-to-day variability in MVPA behavior. Spearman-Brown analysts indicated that between 4 and 5 d of monitoring would be necessary to a achieve a reliability of 0.80 in children, and between 8 and 9 d of monitoring would be necessary to achieve a reliability of 0.80 in adolescents. Within all grade levels, the 7-d monitoring protocol produced acceptable estimates of daily participation in MVPA (R = 0.76 (0.71-0.81) to 0.87 (0.84-0.90)). Compared with weekdays, children exhibited significantly higher levels of MVPA on weekends, whereas adolescents exhibited significantly lower levels of MVPA on weekends. Principal components analysis revealed two distinct time components for MVPA during the day for children (early morning, rest of the day), and three distinct time components for MVPA during the day for adolescents (morning, afternoon, early evening). Conclusions These results indicate that a 7-d monitoring protocol provides reliable estimates of usual physical activity behavior in children and adolescents and accounts for potentially important differences in weekend versus weekday activity behavior as well as differences in activity patterns within a given day.

Validity of the computer science and applications (CSA) activity monitor in children

Purpose The purpose of this study was to evaluate the validity of the CSA activity monitor as a measure of children's physical activity using energy expenditure (EE) as a criterion measure. Methods Thirty subjects aged 10 to 14 performed three 5-min treadmill bouts at 3, 4, and 6 mph, respectively. While on the treadmill, subjects wore CSA (WAM 7164) activity monitors on the right and left hips. (V) over dot O-2 was monitored continuously by an automated system. EE was determined by multiplying the average (V) over dot O-2 by the caloric equivalent of the mean respiratory exchange ratio. Results Repeated measures ANOVA indicated that both CSA monitors were sensitive to changes in treadmill speed. Mean activity counts from each CSA unit were not significantly different and the intraclass reliability coefficient for the two CSA units across all speeds was 0.87. Activity counts from both CSA units were strongly correlated with EE (r = 0.86 and 0.87, P < 0.001). An EE prediction equation was developed from 20 randomly selected subjects and cross-validated on the remaining 10. The equation predicted mean EE within 0.01 kcal.min(-1). The correlation between actual and predicted values was 0.93 (P < 0.01) and the SEE was 0.93 kcal.min(-1). Conclusion These data indicate that the CSA monitor is a valid and reliable tool for quantifying treadmill walking and running in children.

Effects of child care policy and environment on physical activity

Child care centers differ systematically with respect to the quality and quantity of physical activity they provide, suggesting that center-level policies and practices, as well as the center's physical environment, are important influences on children's physical activity behavior. Purpose To summarize and critically evaluate the extant peer-reviewed literature on the influence of child care policy and environment on physical activity in preschool-aged children. Methods A computer database search identified seven relevant studies that were categorized into three broad areas: cross-sectional studies investigating the impact of selected center-level policies and practices on moderate-to-vigorous physical activity (MVPA), studies correlating specific attributes of the outdoor play environment with the level and intensity of MVPA, and studies in which a specific center-level policy or environmental attribute was experimentally manipulated and evaluated for changes in MVPA. Results Staff education and training, as well as staff behavior on the playground, seem to be salient influences on MVPA in preschoolers. Lower playground density (less children per square meter) and the presence of vegetation and open play areas also seem to be positive influences on MVPA. However, not all studies found these attributes to be significant. The availability and quality of portable play equipment, not the amount or type of fixed play equipment, significantly influenced MVPA levels. Conclusions Emerging evidence suggests that several policy and environmental factors contribute to the marked between-center variability in physical activity and sedentary behavior. Intervention studies targeting these factors are thus warranted.