Parents face complex challenges managing children’s digital privacy, navigating their own practices and multi-stakeholder family dynamics. This study develops a psychologically grounded model of parental privacy management to identify modifiable cognitive and emotional antecedents. Surveying 1,000 German parents and using structural equation modeling techniques, we examined how privacy concern and self-efficacy predict three key behaviors: child mediation, parental child data disclosure regulation, and regulation of others. Results show that privacy concern robustly predicts all three behaviors, challenging the traditional privacy paradox in parental contexts. More importantly, self-efficacy emerges as a substantially stronger predictor of privacy behaviors than concern. Among its antecedents, technical skills are most influential. Our findings suggest a paradigm shift toward peer-to-peer interventions that prioritize confidence and skill-building over fear-based approaches that emphasize privacy threats. By focusing on modifiable antecedents, this work provides practical guidance for designing interventions and platforms that empower parents to effectively protect children’s privacy.
ACM CHI Conference on Human Factors in Computing Systems