Related Experiment Video
Updated: Feb 20, 2026

Physical Activity Measurement in Children Accepting Table Tennis Training
Published on: July 27, 2022
In Search of Consistent Predictors of Children's Physical Activity
Keren Best1, Kylie Ball2, Dorota Zarnowiecki3
1Institute for Physical Activity and Nutrition, Deakin University, Burwood, VIC 3125, Australia. keren.best@deakin.edu.au.
Abstract:
Physical activity is pivotal for children's health and well-being, yet participation declines across teenage years. Efforts to increase physical activity need to be strengthened to combat this, however, evidence for the design and planning of physical activity promotion in children is lacking. The aim was to identify predictors of physical activity that were relatively consistent across three different measures of physical activity, in pre- and early adolescent South Australians. This is the first study to compare correlates of physical activity across three measures of physical activity in a single sample, in this age group. Children (n = 324) aged 9-13 years and their parents were surveyed on personal, interpersonal and environmental correlates of physical activity. Child physical activity was objectively measured using pedometers (7 days). Self-reported physical activity was determined from organised sport participation and the Physical Activity Questionnaire for Adolescents. Regression models were used to identify consistent predictors of three physical activity measures. Consistent predictors across multiple physical activity measures were: parent support for physical activity, having appropriate clothing for sport, enjoyment of physical activity and perceived availability of sporting clubs. These predictors identify potential avenues for directing intervention efforts to increase physical activity in early adolescents.
Related Concept Videos
Factors Influencing Attraction II: Physical Attraction
Factors Affecting Activity Coefficient
The activity coefficient value for an ion is close to one when the solution has almost zero ionic strength, i.e., when the solution shows close to ideal behavior. As the ionic strength of the solution increases from 0 to 0.1 mol/L, a...
Nature and Nurture
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...

