Measuring Child and Adolescent Behavior in Outdoor Play Environments: A Survey Among Researchers Exploring Quantitative Research Methods

Abstract

Background Outdoor play environments are essential for children’s and adolescents’ development, making it crucial to understand how to measure their use effectively. This study focuses on quantitative methods, which are well suited to capturing the frequency, intensity, and volume of play, as well as supporting large‑scale behavioral and environmental analyses. We synthesized researchers’ experiences to identify the strengths, limitations, and appropriate applications of commonly used quantitative methods, and highlight needs for methodological development.

Method Data were collected via a survey of researchers with experience studying children’s and adolescents’ behavior in outdoor play spaces using quantitative methods. Responses were analyzed using descriptive statistics (close-ended questions) and directed content analysis (open-ended questions) to identify perceived benefits, challenges, recommended contexts of use, and priorities for methodological development.

Results Thirty-one researchers completed the survey, reporting on 62 methods. Researchers reported trade‑offs across methods. Wearables provided high‑quality, validated, and continuous data but were limited by recruitment challenges and time‑intensive processing. Systematic observations imposed minimal participant burden and offered rich contextual detail but lacked scalability due to labor demands and limited temporal coverage. Surveys were highly scalable and complementary but raised concerns regarding child usability and data quality. Methods were most strongly recommended for children aged 6–12 years and in structured settings (schools, early childhood education and care, public open spaces), with gaps identified for younger children and less structured contexts. Key development needs included more scalable observational approaches, user‑friendly wearables, improved survey tools, and integrated solutions such as 24‑h wearables, automated space monitoring, and multi‑source data collection.

Conclusion No single method is without limitations, and selection involves tradeoffs between resources, data quality, and scalability. Wearables dominate individual‑level measurement but require further development to capture activity type, context, and social interaction. Systematic observations remain central for assessing space use, though automated monitoring offers promising scalability. Future method development should focus on being feasible in unscheduled settings and for younger children, while minimizing participant burden.