Purpose:
Around the world, millions of children attend Outside School Hours Childcare (OSHC) (for example, up to 80% of Norwegian children, and 10% of Australian children). Yet, there is a lack of evidence-based guidance on appropriate physical activity and screen-time practices in OSHC. This study aimed to engage multidisciplinary stakeholders to formulate physical activity and screen-time guidelines for Australian OSHC.

Methods:
A 4-round online Delphi survey was conducted. Australian and international stakeholders were invited, representing academia, the education sector, government, health professionals, OSHC staff and parents (n=110).  Round one comprised open-ended items exploring physical activity, screen-time and sedentary behaviour in before and after school care, and vacation care settings. Subsequent rounds were based on stakeholder comments from previous rounds and sought consensus for inclusion in national guidelines. Consensus was set at 80% agreement. Statements reaching consensus were combined with evidence from two systematic/scoping reviews to develop the guidelines following the GRADE process.

Results/findings: Sixty-seven stakeholders participated representing all target stakeholder groups. 48 statements achieved consensus for inclusion. These statements related to offering a variety of physical activities (free play, playground, sports equipment and facilitated games) and limiting screen-time availability. Consensus was reached on the need to restrict recreational screen-time. Some participants believed screen time should not be routinely offered in OSHC, however this did not reach consensus. The resulting guidelines were framed at the OSHC service-level, rather than child-level, in order to provide OHSC services with clear guidance for scheduling of physical activity and screen-time. The physical activity guidelines assumed a 3:1 ratio, i.e. that children will be physically active for approximately one third of scheduled physical activity opportunity. The final guidelines recommend: before school: > 45 minutes of scheduled physical activity and <30 minutes screen-time; after school >90 minutes of scheduled physical activity and <60 minutes of screen-time; vacation care >180 minutes of scheduled physical activity and <120 minutes of screen-time.

Conclusions: This novel research used expert and stakeholder consultation to underpin the development of the Australian physical activity and screen-time guidelines for OSHC. Future research will seek OSHC sector feedback on the guidelines, and identify translation pathways.

Purpose: The nature of children’s journeys to and from school has public health relevance for physical activity and healthy eating. By passively capturing images of children’s surroundings, wearable cameras have the potential to not only identify travel modes, but also environmental factors that influence health e.g. food marketing. We aimed to determine the nature of children’s journeys to and from school, including time spent in active and motorized travel, destinations visited and food purchase/consumption, using data from the Kids’Cam wearable camera project.

Methods: The sample for this cross-sectional observational study included 153 Year 8 children aged 11-13 years in the Wellington region of New Zealand. Each child wore a wearable camera around their neck for two school days, capturing images of their surroundings every 7 seconds. Following piloting and reliability testing, images were coded for active and motorised travel time, destinations visited on-route (e.g food outlets, recreation/sport) and food purchase/consumption. Mean active and passive travel time were calculated using negative binomial regression.

Results: Children’s journeys, on average, took 19.4 minutes (active travel: 6.8 minutes; passive travel: 7.8 minutes; time spent ‘stopped’: 4.3 minutes. Journeys were variable, containing an average of 2.8 legs (e.g. walk-bus-walk). The most common destinations at which children stopped were unhealthy food outlets (e.g. convenience stores) (40.7% of total). Children with higher active travel time visited more food outlets and purchased more food/beverages than those using motorised transport.

Conclusions: Wearable cameras are a promising tool for contextualising children’s journeys to and from school.  Our findings highlight the complexity of school journeys, many of which do not fit a simple classification as ‘active’ or ‘passive’. The link between active travel and unhealthy food exposure emphasizes the need to limit food marketing and unhealthy food availability near schools, as a means to create environments that support both active travel and healthy eating.

Background: The application of machine-learning to classify activity behaviours is becoming more prominent. The ability to distinguish sitting in a car vs. other forms of sitting is important to better understand travel behaviours and evaluate active transport-focused interventions. This study examined if a dual accelerometer system and machine learning methods can differentiate sedentary behaviours during travel and non-travel time in children.  

Methods: 13 children wore two Axivity AX3 accelerometers (set to record at 100 HZ, with ±8G of bandwidth); one to their thigh, and one to their lower back; alongside an automated clip camera (clipped to the lapel) that captures video of their free-living environment (criterion measure of sedentary activity). Participants were then taken on a car drive for 10 to 15 mins and were also encouraged to complete sedentary activities (e.g., sitting on a chair) at their private residence within a timeframe of 2 hours. Various signal features were extracted from raw accelerometer data, which were used to train a random forest machine learning classifier. The model was evaluated using leave-one-out cross-validation.

Results: In total, 9.1 hours of sitting were recorded, of which 2.1 hours were ‘sitting in a car’. The random forest model achieved a sensitivity of 57%, specificity of 83.4% (Kappa = 0.3213), and a precision of 35.3% in distinguishing ‘sitting in a car’ from other forms of sitting.

Conclusions: This study demonstrated that a dual accelerometer system cannot effectively distinguish sedentary behaviours accumulated during travel and non-travel time. Future studies may have to rely on an additional GPS device to provide contextual information for sedentary behaviors.

Purpose: Most studies about parental support behaviors for physical activity (PA) on children’s moderate-to-vigorous intensity physical activity (MVPA) were conducted in developed countries, and most  focused on mother’s or parent’s (with no differentiation between father’s or mother’s) support behaviors. Besides, children’s MVPA time interval was not differentiated adequately. This paper aimed at investigating the associations between paternal and maternal support behaviors for PA, and children’s MVPA on weekdays, weekends and the whole week in China.

Methods: Cross-sectional data of 517 father-child dyads and 1,422 mother-child dyads were analyzed. Children’s MVPA time was recorded using consecutive 7-day PA diary. MVPA time on weekdays, weekends and the whole week were further calculated, respectively. Father or mother completed a questionnaire on their support behaviors for children’s PA. Multivariate logistic regression was conducted to investigate the independent effect of paternal and maternal support behaviors for PA on children’s meeting MVPA recommendation on weekdays, weekends and the whole week, respectively.

Results: The proportion of children’s meeting MVPA recommendation on weekends (37.8%) was significantly lower than that on weekdays (62.8%). Higher paternal (OR[95%CI]:1.098[1.009,1.195]) and maternal (OR[95%CI]:1.076[1.021,1.134]) total scores of support behaviors for PA were associated with children’s higher odds of meeting MVPA recommendation on weekends, after controlling for covariates. Paternal sharing PA knowledge with child was significantly associated with children’s meeting MVPA recommendation on weekends (OR[95%CI]:1.319[1.055,1.649]), and marginally associated with children’s meeting MVPA recommendation on weekdays (OR[95%CI]:1.220[0.974,1.528], P=0.084) and on the whole week (OR[95%CI]:1.218[0.977,1.519], P=0.080). Maternal reserving PA time for child was associated with children’s higher likelihood of meeting MVPA recommendation on weekdays (OR[95%CI]:1.160[1.025,1.313]), weekends (OR[95%CI]:1.241[1.097,1.403]) and the whole week (OR[95%CI]:1.214[1.076,1.369]), respectively.

Conclusions: On weekends, paternal and maternal total support behaviors for PA deserves more practices for promoting children’s MVPA. To promote children’s MVPA on weekdays, weekends and the whole week, father’s sharing PA knowledge with child and mother’s reserving PA time for child are recommended. Longitudinal researches are needed to verify the findings.

Purpose: Socio-behavioural adaptations during the COVID-19 pandemic may have significantly affected young people’s lifestyle. Investigations on the reasons for changes in adolescents’ physical activity and sedentary behaviour during the pandemic are not yet available. This study aimed to explore underlying reasons affecting changes in physical activity and sedentary behaviour in Indonesian adolescents during the COVID-19 pandemic based on parents’ perspectives.

Methods: This qualitative study employed a reflexive thematic analysis approach. We recruited participants from the Yogyakarta region of Indonesia by using purposive and snowball sampling. Twenty mothers agreed to participate in the study. We collected data by using interviews and an online sociodemographic questionnaire. Semi-structured one-on-one interviews were conducted by the lead author primarily by mobile phone (n=17). Three participants asked to do face-to-face interviews due to problems with telephone connections and convenience reasons. Interviews were audio-recorded, transcribed verbatim and anonymised. All data were imported into NVivo software for analysis.

Results: The interviews lasted between 38 and 113 minutes (M duration = 65 min). Participants’ age ranged between 36-54 years (M = 42.6 years). Participants’ children ranged in age from 12 to 15 years (M=13.7 years, female: 9, male: 11). From the data analysis, we generated two themes related to changes in physical activity during the COVID-19 pandemic: 1) self-determination to do physical activity, and 2) the presence of supports from others. Meanwhile, three inter-related themes related to changes in sedentary behaviour: 1) increased demands for using screen-based devices, 2) increased reliance on screen-based devices, and 3) support system in the family.

Conclusions: This study provides new insights on underlying factors affecting changes in adolescents’ physical activity and sedentary behaviour during the COVID-19 pandemic. Overall, adolescents became less active and more reliant on screen-based devices, either for educational or recreational purposes. Self-determination seems to be the most significant factor for adolescents to keep doing physical activity during the pandemic. WhatsApp, Instagram, and YouTube were the most popular social media among adolescents, suggesting future studies and policymakers to take into account these findings when designing interventions and policies.

Keywords: pandemic, health, youth, young people, exercise, screen time