Journal
PERSONAL AND UBIQUITOUS COMPUTING
Volume 22, Issue 4, Pages 839-866Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00779-018-1166-x
Keywords
Brain-computer interfaces; Neurofeedback; Self-regulation; Children; Games for learning; Developing countries; Field evaluation
Funding
- Natural Science and Engineering Research Council of Canada (NSERC)
- Social Science and Humanities Research Council (SSHRC)
- GRAND Network Centre of Excellence (Canada)
- Microsoft Research
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Children living in poverty often suffer multiple forms of trauma, which impedes their ability to effectively self-regulate negative emotions, such as anxiety, and to focus their attention. As a result, many of these children struggle at school. Our work explores the effectiveness of using a mindfulness-oriented, neurofeedback-based, brain-computer system to help teach children living in poverty to self-regulate anxiety and attention. Our system, called Mind-Full, was specifically designed for illiterate girls who attend an NGO-funded school in Pokhara, Nepal. In this paper, we present the results of a waitlist control field experiment with 21 girls who completed an intervention using the Mind-Full system. Our results indicated that a 6-week Mind-Full intervention was viable and that children were able to transfer self-regulation skills learned using our system into real-world settings and continue to self-regulate successfully after 2 months. We present our findings as a validation of the effectiveness of mobile neurofeedback-based interventions to help young children living in poverty develop self-regulation skills. We conclude with a discussion of the results, methodological challenges of working in the developing world, and advice for future investigations of the effectiveness of neurofeedback applications for children.
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