BEAM – Bettering Education by Advancing Mental Health Literacy

BEAM contributes to efforts aimed at improving mental health literacy among teachers and students. The project is a collaboration between TIDE Research Group and FubIntLab, BEAM and involves multidisciplinary collaborations among researchers (education technology, HCI, neuroscience, bioengineering), medical professionals (child and adolescent psychologists), and educators. The project builds off of work done in the Erasmus+ Spotlighters Project which focused on student self-management and self-care by analysing data collected from classroom interventions and by running exploratory studies aimed at advancing the ClassMood App – to strengthen its scientific grounding and identify opportunities to better serve disadvantaged students.

 

Why BEAM?

Social-emotional learning (SEL) programs can be a foundation for a public health approach to education (Greenberg et al., 2017). SEL programs can lead to improvements in both student well-being and academic outcomes (MacCann et al, 2020; Mahoney et al, 2018). The previously mentioned Spotlighters’ project strived to improve student knowledge of the science of stress, mindfulness, and cognitive appraisal. Preliminary results of the lesson intervention were presented at CIDUI 2021 (Beardsley, Vujovic & Portero Tresserra, 2021). Previous studies have also found that the combination of mindful breathing practices and cognitive reappraisal seems to be an effective approach for promoting self-regulation skills among university students (Galante et al, 2018). Additional data from the Spotlighters’ project has been collected, BEAM will provide support to analyze such data.

Additionally, there is growing interest toward integrating multiple behavioral modalities to enhance insights on behavioral characteristics and states such as anxiety. For example, researchers using machine learning techniques have been able to accurately classify anxiety using different physiological modalities together, including ECG, EDA, EMG, blood volume pulse (BVP), temperature, bio impedance, and heart sound (Liu et al, 2008). The ECG signal represents the fluctuations of cardiac potential and it is the most widely used approach to detect the variations between consecutive heartbeats, known as HRV. Measures of HRV such as vagal tone and respiratory sinus arrhythmia (RSA) are valuable indicators for understanding PNS responses to stress (i.e. activation) (Porges et al, 1994)) and has been used to study self-regulatory practices such as Mindfulness (Kirk & Axelsen, 2020)]. Polyvagal theory suggests that greater PNS activity of the vagal tone is associated with better social interaction and emotion regulation (Porges, 2008). BEAM looks to complement such work while assessing self-regulatory activities and further the use of affective computing in educational settings (Yadegaridehkordi et al, 2019). The project will develop a protocol for assessing self-regulatory activities for classroom use.

 

Relevance of the project for the area of planetary wellbeing

In relation to the UN Sustainable Development Goals, mental health is included in goal 3. Specifically, Target 3.4 related to reducing premature mortality from noncommunicable diseases through the prevention, treatment, and promotion of mental health and well-being; and Target 3.5 related to strengthening the prevention and treatment of substance abuse. 

The need to support mental health is detailed in the The WHO Special Initiative for Mental Health (2019-2023) which writes that: Mental health conditions cause 1 in 5 years lived with disability; 800 000/year deaths from suicide, which is a leading cause of death in young people; Depression and anxiety disorders cost the global economy US$1 trillion per year; People with mental health conditions often experience severe human rights violations, discrimination, stigma. Thus, “mental health conditions contribute to poor health outcomes, premature death, human rights violations, and global and national economic loss.” There is a pressing need to improve mental health support and literacy in students and formal education offers a scalable pathway for doing so.

 

References

  • World Health Organization. (2016, January 14). Mental health included in the UN Sustainable Development Goals. 
  • World Health Organization. (2019). The WHO special initiative for mental health (‎‎‎ 2019-2023)‎‎‎‎: universal health coverage for mental health (No. WHO/MSD/19.1). World Health Organization.
  • Colao, A., Piscitelli, P., Pulimeno, M., Colazzo, S., Miani, A., & Giannini, S. (2020). Rethinking the role of the school after COVID-19. The Lancet Public Health, 5(7), e370.
  • Greenberg, M. T., Domitrovich, C. E., Weissberg, R. P., & Durlak, J. A. (2017). Social and emotional learning as a public health approach to education. The Future of Children, 13-32.
  • Mahoney, J. L., Durlak, J. A., & Weissberg, R. P. (2018). An update on social and emotional learning outcome research. Phi Delta Kappan, 100(4), 18-23.
  • MacCann, C., Jiang, Y., Brown, L. E. R., Double, K. S., Bucich, M., & Minbashian, A. (2020). Emotional intelligence predicts academic performance: A meta-analysis. Psychological Bulletin, 146(2), 150–186. https://doi.org/10.1037/bul0000219
  • Galante, J., Dufour, G., Vainre, M., Wagner, A.P., Stochl, J., Benton, A., Lathia, N., Howarth, E., & Jones, P.B. (2018). A mindfulness-based intervention to increase resilience to stress in university students (the Mindful Student Study): a pragmatic randomised controlled trial. The Lancet Public Health, 3(2), pp.e72-e81.
  • Beardsley, M., Vujovic, M., & Portero Tresserra, M. Evaluating an intervention to improve university student stress mindsets and self-management skills. Paper accepted at: XI Congrés CIDUI 2021; 30 Jun-2 Jul; Hospitalet de Llobregat, Spain
  • Liu, C., Conn, K., Sarkar, N., and Stone, W. (2008).  Physiology-based affect recognition for computer-assisted intervention of children with Autism SpectrumDisorder.International journal of human-computer studies, 66(9):662–677
  • Porges, S. W., Doussard-Roosevelt, J. A., and Maiti, A. K. (1994).Vagal tone and the physiological regulation of emotion.Monographs of the society for research in child development, 59(2-3):167–186.
  • Kirk, U., & Axelsen, J. L. (2020). Heart rate variability is enhanced during mindfulness practice: A randomized controlled trial involving a 10-day online-based mindfulness intervention. PloS one, 15(12), e0243488.
  • Porges, S. W. (2007).  The polyvagal perspective. Biological Psychology, 74(2): 116–143
  • Yadegaridehkordi, E., Noor, N. F. B. M., Ayub, M. N. B., Affal, H. B., & Hussin, N. B. (2019). Affective computing in education: A systematic review and future research. Computers & Education, 142, 103649.