Integrating AI in Cross-Cultural Questionnaire Design on Parents’ Perceptions of Children’s Risky Play

Purpose
This study presents the iterative, international development of a photo-based questionnaire designed to explore parents’ perceptions of children’s risky play across diverse cultural contexts. Building on a validated Belgian version (Jidovtseff et al., 2022), the project engages 30 researchers from 16 countries in co-constructing a culturally adaptable tool that captures differences in how adults perceive benefits, dangers, and permissions associated with children’s outdoor play.
Methods/Approach/Framework
The development followed a participatory and iterative approach inspired by Delphi principles. Through multiple feedback rounds, partners reached consensus on: (1) the selection of play situations and target age groups, (2) the wording and response options, and (3) the creation of representative imagery. Artificial Intelligence (AI) played a dual role in this process. First, it supported the generation of realistic, culturally diverse images illustrating eight categories of risky play (Sandseter, 2009), ensuring gender and ethnic balance through controlled prompts and “seed” parameters. Second, AI-assisted translation tools will be used to support multilingual adaptation into different languages, facilitating semantic consistency and accessibility while maintaining human final validation through back-translation and expert review.
Results
The project produced a harmonized set of 10 photo-based scenarios and standardized question items, validated for content and cultural relevance. The integration of AI-driven image generation and translation substantially reduced time and logistical constraints, allowing efficient coordination across continents while preserving methodological rigor. Pilot testing and preliminary data collection are planned for early 2026.
Conclusion
This project illustrates how iterative collaboration, AI technologies, and expert validation can jointly advance cross-cultural research. Beyond its focus on risky play, it demonstrates how combining human expertise with machine assistance enhances inclusivity, transparency, and feasibility in international research.