ESRA 2027 sessions by theme

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Session Details

Children’s subjective experiences of daily life, leisure, and health are often underrepresented in public health data, despite Article 12 of the UN Convention on the Rights of the Child guaranteeing their right to express views on matters affecting them. This study pilots a mixed-methods approach to analyze open-ended responses from three pilot surveys targeting children aged 8–16 in Sweden’s Hälsorapport. Using AI-assisted thematic analysis (Vibe), fritext responses were processed to identify preliminary themes, which were then refined iteratively by researchers to ensure depth and accuracy.
The surveys explored daily routines (e.g., sleep, physical activity, diet), leisure activities (e.g., preferences, barriers, time allocation), and health perceptions (e.g., definitions of well-being, barriers to feeling good). The COM-B framework (Capability, Opportunity, Motivation) structured the analysis, revealing patterns in children’s behaviors, barriers (e.g., time pressure, limited access to nature), and motivations (e.g., social engagement, personal interests).
Preliminary findings highlight nuanced perspectives on well-being, such as the importance of autonomy in daily habits and the role of outdoor activities in mental health. Results directly inform Folkhälsomyndigheten’s methodological development, ensuring children’s voices systematically shape future data collection—aligning with the agency’s commitment to child rights and inclusive research. By demonstrating how AI can enhance traditional qualitative analysis for a vulnerable group, this study aligns with ESRA 2027’s theme of integrating AI with survey methods to produce inclusive, actionable social data.