A cross-sectional study of the individual, social, and built environmental correlates of pedometer based physical activity among elementary school children

Background: Children who participate in regular physical activity obtain health benefits. Preliminary pedometerbased cut-points representing sufficient levels of physical activity among youth have been established; however limited evidence regarding correlates of achieving these cut-points exists. The purpose of this study was to identify correlates of pedometer-based cut-points among elementary school-aged children.
Method: A cross-section of children in grades 5-7 (10-12 years of age) were randomly selected from the most (n = 13) and least (n = 12) ‘walkable’ public elementary schools (Perth, Western Australia), stratified by socioeconomic status. Children (n = 1480; response rate = 56.6%) and parents (n = 1332; response rate = 88.8%) completed a survey, and steps were collected from children using pedometers. Pedometer data were categorized to reflect the sex-specific pedometer-based cut-points of ≥15000 steps/day for boys and ≥12000 steps/day for girls. Associations between socio-demographic characteristics, sedentary and active leisure-time behavior, independent mobility, active transportation and built environmental variables - collected from the child and parent surveys - and meeting pedometer-based cut-points were estimated (odds ratios: OR) using generalized estimating equations.
Results: Overall 927 children participated in all components of the study and provided complete data. On average, children took 11407 ± 3136 steps/day (boys: 12270 ± 3350 vs. girls: 10681 ± 2745 steps/day; p < 0.001) and 25.9% (boys: 19.1 vs. girls: 31.6%; p < 0.001) achieved the pedometer-based cut-points. After adjusting for all other variables and school clustering, meeting the pedometer-based cut-points was negatively associated (p < 0.05) with being male (OR = 0.42), parent self-reported number of different destinations in the neighborhood (OR 0.93), and a friend’s (OR 0.62) or relative’s (OR 0.44, boys only) house being at least a 10-minute walk from home. Achieving the pedometer-based cut-points was positively associated with participating in screen-time < 2 hours/day (OR 1.88), not being driven to school (OR 1.48), attending a school located in a high SES neighborhood (OR 1.33), the average number of steps among children within the respondent’s grade (for each 500 step/day increase: OR 1.29), and living further than a 10-minute walk from a relative’s house (OR 1.69, girls only).
Conclusions: Comprehensive multi-level interventions that reduce screen-time, encourage active travel to/from school and foster a physically active classroom culture might encourage more physical activity among children.

Acceptability of a theory of planned behaviour email-based nutrition intervention

This study investigated feasibility and acceptability of a new email-delivered intervention promoting fruit and vegetable consumption in a university-based population of Australian young adults. The study explored whether there are differences in the reported feasibility and acceptability between demographic groups within the population of interest and at three levels of intervention intensity. The email-delivered intervention program consists of an implementation intention ‘planning task’ and between 3 and 15 short email messages over a 15-day study period. The intervention program was developed using the Theory of Planned Behaviour and was designed to modify perceived behavioural control. One hundred and ten participants (mean age = 19.21 years, 25.6% male) completed the feasibility and acceptability questionnaire at Day 15. This questionnaire contained items about all intervention components. High acceptability and feasibility scores were found for all intervention parts and at all levels of intervention intensity. There were few significant differences in the reported acceptability of items between key demographic sub-groups, and no differences in reported acceptability at different levels of intervention intensity. These results suggest that this email-delivered intervention is an acceptable and feasible tool for promoting fruit and vegetable consumption for participants in the target population.

Acceptability of a theory of planned behaviour email-based nutrition intervention

This study investigated feasibility and acceptability of a new email-delivered intervention promoting fruit and vegetable consumption in a university-based population of Australian young adults. The study explored whether there are differences in the reported feasibility and acceptability between demographic groups within the population of interest and at three levels of intervention intensity. The email-delivered intervention program consists of an implementation intention ‘planning task’ and between 3 and 15 short email messages over a 15-day study period. The intervention program was developed using the Theory of Planned Behaviour and was designed to modify perceived behavioural control. One hundred and ten participants (mean age = 19.21 years, 25.6% male) completed the feasibility and acceptability questionnaire at Day 15. This questionnaire contained items about all intervention components. High acceptability and feasibility scores were found for all intervention parts and at all levels of intervention intensity. There were few significant differences in the reported acceptability of items between key demographic sub-groups, and no differences in reported acceptability at different levels of intervention intensity. These results suggest that this email-delivered intervention is an acceptable and feasible tool for promoting fruit and vegetable consumption for participants in the target population.

Contextually Learnt Detection of Unusual Motion-Based Behaviour in Crowded Public Spaces

In this paper we are interested in analyzing behaviour in crowded publicplaces at the level of holistic motion. Our aim is to learn, without user input, strong scene priors or labelled data, the scope of ‘‘normal behaviour’’ for a particular scene and thus alert to novelty in unseen footage. The first contribution is a low-level motion model based on what we term tracklet primitives, which are scenespecific elementary motions. We propose a clustering-based algorithm for tracklet estimation from local approximations to tracks of appearance features. This is followed by two methods for motion novelty inference from tracklet primitives: (a) an approach based on a non-hierarchial ensemble of Markov chains as a means of capturing behavioural characteristics at different scales, and (b) a more flexible alternative which exhibits a higher generalizing power by accounting for constraints introduced by intentionality and goal-oriented planning of human motion in a particular scene. Evaluated on a 2 h long video of a busy city marketplace, both algorithms are shown to be successful at inferring unusual behaviour, the latter model achieving better performance for novelties at a larger spatial scale.

Effect of a school-based active play intervention on sedentary time and physical activity in preschool children

Early childhood is a critical time for promoting physical activity. Few studies have investigated the effect of interventions in this population. The aim of this study was to investigate the effect of a school-based active play intervention on preschool children’s sedentary time and physical activity. Preschool children were recruited from randomly selected preschools. Schools were randomly assigned to an intervention or comparison group. One teacher per intervention school received training from active play professionals in the delivery of a 6-week active play programme. Comparison schools continued their usual practice. Children wore a uni-axial accelerometer for 7 days at baseline, immediately after and at 6-month post-intervention. No significant intervention effects were observed for sedentary time or physical activity. However, sex and hours spent at school were significant predictors of physical activity. Children who spent fewer hours (half-day children) at school were significantly more active than their full-day counterparts. Physical activity during the intervention classes was high even though neither daily physical activity nor sedentary time changed. Notably children who spent more time at preschool were less active suggesting that preschool was not as conducive to physical activity engagement as other environments.

Sitting behaviour-based pattern recognition for predicting driver fatigue

The proposed approach based on physiological characteristics of sitting behaviours and sophisticated machine learning techniques would enable an effective and practical solution to driver fatigue prognosis since it is insensitive to the illumination of driving environment, non-obtrusive to driver, without violating driver’s privacy, more acceptable by drivers.

Do physical activity and dietary smartphone applications incorporate evidence-based behaviour change techniques?

BACKGROUND: There has been a recent proliferation in the development of smartphone applications (apps) aimed at modifying various health behaviours. While interventions that incorporate behaviour change techniques (BCTs) have been associated with greater effectiveness, it is not clear to what extent smartphone apps incorporate such techniques. The purpose of this study was to investigate the presence of BCTs in physical activity and dietary apps and determine how reliably the taxonomy checklist can be used to identify BCTs in smartphone apps.

METHODS: The top-20 paid and top-20 free physical activity and/or dietary behaviour apps from the New Zealand Apple App Store Health & Fitness category were downloaded to an iPhone. Four independent raters user-tested and coded each app for the presence/absence of BCTs using the taxonomy of behaviour change techniques (26 BCTs in total). The number of BCTs included in the 40 apps was calculated. Krippendorff's alpha was used to evaluate interrater reliability for each of the 26 BCTs.

RESULTS: Apps included an average of 8.1 (range 2-18) techniques, the number being slightly higher for paid (M = 9.7, range 2-18) than free apps (M = 6.6, range 3-14). The most frequently included BCTs were "provide instruction" (83% of the apps), "set graded tasks" (70%), and "prompt self-monitoring" (60%). Techniques such as "teach to use prompts/cues", "agree on behavioural contract", "relapse prevention" and "time management" were not present in the apps reviewed. Interrater reliability coefficients ranged from 0.1 to 0.9 (Mean 0.6, SD = 0.2).

CONCLUSIONS: Presence of BCTs varied by app type and price; however, BCTs associated with increased intervention effectiveness were in general more common in paid apps. The taxonomy checklist can be used by independent raters to reliably identify BCTs in physical activity and dietary behaviour smartphone apps.