Stephanie Schoeppe

Associations of children's independent mobility and active travel with physical activity, sedentary behaviour and weight status: A systematic review

UNLABELLED Health benefits from childrens independent mobility and active travel beyond school travel are largely unexplored. OBJECTIVES This review synthesized the evidence for associations of independent mobility and active travel to various destinations with physical activity, sedentary behaviour and weight status. DESIGN Systematic review. METHODS A systematic search in six databases (PubMed, Scopus, CINAHL, SportDiscus, PsychInfo, TRIS) for papers published between January 1990 and March 2012 was undertaken, focussing on children aged 3-18 years. Study inclusion and methodological quality were independently assessed by two reviewers. RESULTS 52 studies were included. Most studies focussed solely on active travel to and/or from school, and showed significant positive associations with physical activity. The same relationship was detected for active travel to leisure-related places and independent mobility with physical activity. An inverse relationship between active travel to school and weight status was evident but findings were inconsistent. Few studies examined correlations between active travel to school and self-reported screen-time or objectively measured sedentary behaviour, and findings were unclear. CONCLUSIONS Studies on independent mobility suggested that children who have the freedom to play outdoors and travel actively without adult supervision accumulate more physical activity than those who do not. Further investigation of childrens active travel to leisure-related destinations, measurement of diverse sedentary behaviour beyond simply screen-based activities, and consistent thresholds for objectively measured sedentary behaviour in children will clarify the inconsistent evidence base on associations of active travel with sedentary behaviour and weight status.

Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review

BackgroundHealth and fitness applications (apps) have gained popularity in interventions to improve diet, physical activity and sedentary behaviours but their efficacy is unclear. This systematic review examined the efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour in children and adults.MethodsSystematic literature searches were conducted in five databases to identify papers published between 2006 and 2016. Studies were included if they used a smartphone app in an intervention to improve diet, physical activity and/or sedentary behaviour for prevention. Interventions could be stand-alone interventions using an app only, or multi-component interventions including an app as one of several intervention components. Outcomes measured were changes in the health behaviours and related health outcomes (i.e., fitness, body weight, blood pressure, glucose, cholesterol, quality of life). Study inclusion and methodological quality were independently assessed by two reviewers.ResultsTwenty-seven studies were included, most were randomised controlled trials (n = 19; 70%). Twenty-three studies targeted adults (17 showed significant health improvements) and four studies targeted children (two demonstrated significant health improvements). Twenty-one studies targeted physical activity (14 showed significant health improvements), 13 studies targeted diet (seven showed significant health improvements) and five studies targeted sedentary behaviour (two showed significant health improvements). More studies (n = 12; 63%) of those reporting significant effects detected between-group improvements in the health behaviour or related health outcomes, whilst fewer studies (n = 8; 42%) reported significant within-group improvements. A larger proportion of multi-component interventions (8 out of 13; 62%) showed significant between-group improvements compared to stand-alone app interventions (5 out of 14; 36%). Eleven studies reported app usage statistics, and three of them demonstrated that higher app usage was associated with improved health outcomes.ConclusionsThis review provided modest evidence that app-based interventions to improve diet, physical activity and sedentary behaviours can be effective. Multi-component interventions appear to be more effective than stand-alone app interventions, however, this remains to be confirmed in controlled trials. Future research is needed on the optimal number and combination of app features, behaviour change techniques, and level of participant contact needed to maximise user engagement and intervention efficacy.

Examining the use of evidence-based and social media supported tools in freely accessible physical activity intervention websites

BackgroundIt has been shown that physical activity is more likely to increase if web-based interventions apply evidence-based components (e.g. self-monitoring) and incorporate interactive social media applications (e.g. social networking), but it is unclear to what extent these are being utilized in the publicly available web-based physical activity interventions. The purpose of this study was to evaluate whether freely accessible websites delivering physical activity interventions use evidence-based behavior change techniques and provide social media applications.MethodsIn 2013, a systematic search strategy examined 750 websites. Data was extracted on a wide range of variables (e.g. self-monitoring, goal setting, and social media applications). To evaluate website quality a new tool, comprising three sub-scores (Behavioral Components, Interactivity and User Generated Content), was developed to assess implementation of behavior change techniques and social media applications. An overall website quality scored was obtained by summing the three sub-scores.ResultsForty-six publicly available websites were included in the study. The use of self-monitoring (54.3%), goal setting (41.3%) and provision of feedback (46%) was relatively low given the amount of evidence supporting these features. Whereas the presence of features allowing users to generate content (73.9%), and social media components (Facebook (65.2%), Twitter (47.8%), YouTube (48.7%), smartphone applications (34.8%)) was relatively high considering their innovative and untested nature. Nearly all websites applied some behavioral and social media applications. The average Behavioral Components score was 3.45 (±2.53) out of 10. The average Interactivity score was 3.57 (±2.16) out of 10. The average User Generated Content Score was 4.02 (±2.77) out of 10. The average overall website quality score was 11.04 (±6.92) out of 30. Four websites (8.7%) were classified as high quality, 12 websites (26.1%) were classified as moderate quality, and 30 websites (65.2%) were classified as low quality.ConclusionsDespite large developments in Internet technology and growth in the knowledge of how to develop more effective web-based interventions, overall website quality was low and the majority of freely available physical activity websites lack the components associated with behavior change. However, the results show that website quality can be improved by taking a number of simple steps, and the presence of social media applications in most websites is encouraging.

Automatic Evaluation Stimuli – The Most Frequently Used Words to Describe Physical Activity and the Pleasantness of Physical Activity

Physical activity is partially regulated by non-conscious processes including automatic evaluations – the spontaneous affective reactions we have to physical activity that lead us to approach or avoid physical activity opportunities. A sound understanding of which words best represent the concepts of physical activity and pleasantness (as associated with physical activity) is needed to improve the measurement of automatic evaluations and related constructs (e.g., automatic self-schemas, attentional biases). The first aim of this study was to establish population-level evidence of the most common word stimuli for physical activity and pleasantness. Given that response latency measures have been applied to assess automatic evaluations of physical activity and exercise, the second aim was to determine whether people use the same behavior and pleasant descriptors for physical activity and exercise. Australian adults (N = 1,318; 54.3% women; 48.9% aged 55 years or older) were randomly assigned to one of two groups, through a computer-generated 1:1 ratio allocation, to be asked to list either five behaviors and pleasant descriptors of physical activity (n = 686) or of exercise (n = 632). The words were independently coded twice as to whether they were novel words or the same as another (i.e., same stem or same meaning). Intercoder reliability varied between moderate and strong (agreement = 50.1 to 97.8%; κ = 0.48 to 0.82). A list of the 20 most common behavior and pleasantness words were established based on how many people reported them, weighted by the ranking (1–5) people gave them. The words people described as physical activity were mostly the same as those people used to describe exercise. The most common behavior words were ‘walking,’ ‘running,’ ‘swimming,’ ‘bike riding,’ and ‘gardening’; and the most common pleasant descriptor words were ‘relaxing,’ ‘happiness,’ ‘enjoyment,’ ‘exhilarating,’ ‘exhausting,’ and ‘good.’ These sets of stimuli can be utilized as resources for response latency measurement tasks of automatic evaluations and for tools to enhance automatic evaluations of physical activity in evaluative conditioning tasks.

Australian children's independent mobility levels: Secondary analyses of cross-sectional data between 1991 and 2012

This study investigated changes in Australian childrens independent mobility levels between1991 and 2012. Data from five cross-sectional studies conducted in 1991, 1993, 2010, 2011 and 2012 were analysed. Parent and child surveys were used to assess parental licences for independent mobility and actual independent mobility behaviour in children aged 8–13 years. Findings show declines in the proportion of young children (≤10 years of age) being allowed to travel home from school alone (1991: 68%, 1993: 50%, 2010: 43%, 2011: 45%, 2012: 31%) and travel on buses alone (1991: 31%, 1993: 15%, 2010: 8%, 2011: 6%, 2012: 9%). Furthermore, the proportion of children travelling independently to school decreased (1991: 61%, 1993: 42%, 2010: 31%, 2011: 32%, 2012: 32%). Significantly fewer girls than boys travelled independently to school at each time point (p ≤ .001). Overall, the findings suggest that Australian childrens independent mobility levels declined between 1991 and 2012.

The association between physical activity, sitting time, sleep duration, and sleep quality as correlates of presenteeism

Objective: This study aims to examine the relationship of lifestyle behaviors (physical activity, work and non-work sitting time, sleep quality, and sleep duration) with presenteeism while controlling for sociodemographics, work- and health-related variables. Methods: Data were collected from 710 workers (aged 20 to 76 years; 47.9% women) from randomly selected Australian adults who completed an online survey. Linear regression was used to examine the relationship between lifestyle behaviors and presenteeism. Results: Poorer sleep quality (standardized regression coefficients [B] = 0.112; P < 0.05), suboptimal duration (B = 0.081; P < 0.05), and lower work sitting time (B = −0.086; P < 0.05) were significantly associated with higher presenteeism when controlling for all lifestyle behaviors. Engaging in three risky lifestyle behaviors was associated with higher presenteeism (B = 0.150; P < 0.01) compared with engaging in none or one. Conclusions: The results of this study highlight the importance of sleep behaviors for presenteeism and call for behavioral interventions that simultaneously address sleep in conjunction with other activity-related behaviors.

Maternal and paternal support for physical activity and healthy eating in preschool children: a cross-sectional study

BackgroundParental support is a key influence on children’s health behaviours; however, no previous investigation has simultaneously explored the influence of mothers’ and fathers’ social support on eating and physical activity in preschool-aged children. This study evaluated the singular and combined effects of maternal and paternal support for physical activity (PA) and fruit and vegetable consumption (FV) on preschoolers’ PA and FV.MethodsA random sample comprising 173 parent–child dyads completed validated scales assessing maternal and paternal instrumental support and child PA and FV behaviour. Pearson correlations, controlling for child age, parental age, and parental education, were used to evaluate relationships between maternal and paternal support and child PA and FV. K-means cluster analysis was used to identify families with distinct patterns of maternal and paternal support for PA and FV, and one-way ANOVA examined the impact of cluster membership on child PA and FV.ResultsMaternal and paternal support for PA were positively associated with child PA (r = 0.37 and r = 0.36, respectively; P < 0.001). Maternal but not paternal support for FV was positively associated with child FV (r = 0.35; P < 0.001). Five clusters characterised groups of families with distinct configurations of maternal and paternal support for PA and FV: 1) above average maternal and paternal support for PA and FV, 2) below average maternal and paternal support for PA and FV, 3) above average maternal and paternal support for PA but below average maternal and paternal support for FV, 4) above average maternal and paternal support for FV but below average maternal and paternal support for PA, and 5) above average maternal support but below average paternal support for PA and FV. Children from families with above average maternal and paternal support for both health behaviours had higher PA and FV levels than children from families with above average support for just one health behaviour, or below average support for both behaviours.ConclusionsThe level and consistency of instrumental support from mothers and fathers for PA and FV may be an important target for obesity prevention in preschool-aged children.

Activity Trackers Implement Different Behavior Change Techniques for Activity, Sleep, and Sedentary Behaviors

Background Several studies have examined how the implementation of behavior change techniques (BCTs) varies between different activity trackers. However, activity trackers frequently allow tracking of activity, sleep, and sedentary behaviors; yet, it is unknown how the implementation of BCTs differs between these behaviors. Objective The aim of this study was to assess the number and type of BCTs that are implemented by wearable activity trackers (self-monitoring systems) in relation to activity, sleep, and sedentary behaviors and to determine whether the number and type of BCTs differ between behaviors. Methods Three self-monitoring systems (Fitbit [Charge HR], Garmin [Vivosmart], and Jawbone [UP3]) were each used for a 1-week period in August 2015. Each self-monitoring system was used by two of the authors (MJD and BM) concurrently. The Coventry, Aberdeen, and London-Refined (CALO-RE) taxonomy was used to assess the implementation of 40 BCTs in relation to activity, sleep, and sedentary behaviors. Discrepancies in ratings were resolved by discussion, and interrater agreement in the number of BCTs implemented was assessed using kappa statistics. Results Interrater agreement ranged from 0.64 to 1.00. From a possible range of 40 BCTs, the number of BCTs present for activity ranged from 19 (Garmin) to 33 (Jawbone), from 4 (Garmin) to 29 (Jawbone) for sleep, and 0 (Fitbit) to 10 (Garmin) for sedentary behavior. The average number of BCTs implemented was greatest for activity (n=26) and smaller for sleep (n=14) and sedentary behavior (n=6). Conclusions The number and type of BCTs implemented varied between each of the systems and between activity, sleep, and sedentary behaviors. This provides an indication of the potential of these systems to change these behaviors, but the long-term effectiveness of these systems to change activity, sleep, and sedentary behaviors remains unknown.

Examining the Correlates of Online Health Information–Seeking Behavior Among Men Compared With Women:

This study aimed to identify and compare the demographic, health behavior, health status, and social media use correlates of online health-seeking behaviors among men and women. Cross-sectional self-report data were collected from 1,289 Australian adults participating in the Queensland Social Survey. Logistic regression analyses were used to identify the correlates of online health information seeking for men and women. Differences in the strength of the relation of these correlates were tested using equality of regression coefficient tests. For both genders, the two strongest correlates were social media use (men: odds ratio [OR] = 2.57, 95% confidence interval [CI: 1.78, 3.71]; women: OR = 2.93, 95% CI [1.92, 4.45]) and having a university education (men: OR = 3.63, 95% CI [2.37, 5.56]; women: OR = 2.74, 95% CI [1.66, 4.51]). Not being a smoker and being of younger age were also associated with online health information seeking for both men and women. Reporting poor health and the presence of two chronic diseases were positively associated with online health seeking for women only. Correlates of help seeking online among men and women were generally similar, with exception of health status. Results suggest that similar groups of men and women are likely to access health information online for primary prevention purposes, and additionally that women experiencing poor health are more likely to seek health information online than women who are relatively well. These findings are useful for analyzing the potential reach of online health initiatives targeting both men and women.

Too far from home? Adult attitudes on children's independent mobility range

The purpose of this study was to investigate adult attitudes on distances children should be allowed to travel to places and play in outdoor areas without adult supervision, with consideration of differences in adult attitudes by socio-demographics and urbanisation. In 2013, Australian adults (N = 1293) were asked what distances children aged 8–12 years should be allowed to walk/cycle to places, and play outdoors without adults. Descriptive analyses and chi-square tests were conducted to assess adult attitudes on childrens independent mobility range. Overall, 62% of adults would restrict childrens independent travel to places <500 m from home, and 74% would restrict independent outdoor play <500 m from home. Women and adults with lower education were more likely to report restrictive attitudes than men and adults with higher education, respectively. The promotion of active travel and outdoor play in children may require increasing adults’ acceptance of greater independent mobility range.