Exploring the Potential of Game-based Biofeedback for Anxiety Regulation

Project Lead Category Project status
Joanneke Weerdmeester Anxiety | Depression Completed

This project explored the potential of using game-based biofeedback interventions for anxiety regulation. Specifically, the project had the following aims: 1) Creating a new integrative theoretical model featuring traditional as well as newly proposed mechanisms of change in biofeedback interventions for anxiety regulation. 2) Further developing and validating the efficacy of the biofeedback video game DEEP as an anxiety regulation tool. 3) Formulating guidelines for future research and development of biofeedback interventions for anxiety regulation.

Project team

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07-12-2022

What is biofeedback? 

Biofeedback is the process of measuring an individual’s physiological states and feeding information about these changes back to them so that they can learn how to regulate their physiological activity to improve their wellbeing (Gilbert & Moss, 2003). In biofeedback training, participants are given insight into changes in their physiology such as heart rate, breathing or even brain activity by showing them visualisations (e.g., moving graphs of changes in heart rate) of these changes (Schwartz & Andrasik, 2017). These visualisations contribute to participants’ awareness of internal body signals, also known as interoceptive awareness, which is an important part of effective emotion regulation (Gross, 2002; Kever et al., 2015). In addition operant learning principles such as conditioning and reinforcement are used to teach participants to effectively regulate their physiology. For example, a pleasant tone can indicate when someone has reached an optimal heart- or breathing rate (Hammond, 2005, 2007; Lehrer et al., 2000; Peper et al., 2009; Schwartz & Andrasik, 2017).
Biofeedback is effective in regulating stress and anxiety (Goessl et al., 2017; Hammond, 2005; Richardson & Rothstein, 2008; Schoenberg & David, 2014; Schwartz & Andrasik, 2017; Tolin et al., 2020; Yucha & Montgomery, 2008), however, various practical issues such as specific hardware requirements and high costs prevented a wide adaptation. Furthermore, biofeedback training involves many repetitive trials which makes it difficult for participants to stay motivated, particularly young participants (e.g. Parnandi & Gutierrez-Osuna, 2017). In addition, for treatments to be strengthened and tailored, it is crucial to know what factors contribute to successful change (and which ones do not) (Kazdin, 2014), however, there is a limited understanding of underlying mechanisms of change in biofeedback interventions (Weerdmeester, Van Rooij, Engels, & Granic, 2020; Wheat & Larkin, 2010). 

Project Aims 

The current project explored the potential of using game-based biofeedback interventions for anxiety regulation and had the following aims: 

1) Creating a new integrative theoretical model. This model included factors that have been traditionally linked to the efficacy of biofeedback (e.g., interoceptive awareness) but also identified several cognitive appraisal factors which were posited as possible determinants of the effectiveness of biofeedback training for anxiety regulation. 

2) Further developing and validating the efficacy of the biofeedback video game DEEP as an anxiety regulation tool. In our studies we specifically assessed a) anxiety outcomes, b) the role of cognitive appraisal factors, as well as the influence of c) specific mechanics in the game DEEP based on evidence-based techniques from biofeedback (e.g., visualisation of physiological change) and clinical practice (e.g., exposure).

3) Formulating guidelines for future research and development of biofeedback interventions for anxiety regulation.


The Research

We have conducted multiple studies including pilot studies, an implementation trial in a special eduction school, and most recently a Randomized Controlled Trial with anxious youth to assess whether a training with DEEP could help alleviate anxiety symptoms. In addition we wrote an extensive review regarding biofeedback interventions for anxiety regulation. In this review we identified several psychological mechanisms of change that may be tied to adaptive outcomes of biofeedback interventions and we included a set of guidelines to for a new phase of biofeedback therapy, inspired by game design and the potential of wearable biosensors. All of these studies (and more) are summarized in Joanneke Weerdmeester's doctoral thesis entitled  "Take a DEEP Breath: Exploring the Potential of Game-based Biofeedback Interventions for Anxiety Regulation" which you can download via the link below. 

Download Doctoral Thesis Here

The Findings

Our results demonstrate the ability of game-based biofeedback interventions like DEEP to help youth regulate momentary bouts of anxiety and to diminish their anxiety symptoms over a longer time period with repeated practice. Game-based biofeedback interventions like DEEP may be particularly useful to facilitate relaxation exercises, exposure treatment, and at-home practice. Our findings also highlight the importance of measuring and targeting cognitive appraisals in the context of biofeedback interventions. Self-efficacy and threat-challenge appraisals in particular may serve as important mechanisms of change. Still, more ideographic methods are needed to assess and establish the causal relationships between individual changes in physiology, cognitive appraisals, and anxiety in biofeedback interventions. Moreover, we recommend using study designs and methods with multiple baselines or randomizations to test the unique effect of specific evidence-based techniques and biofeedback mechanics. We also argue that during the entire testing and development phase of new digital interventions it is vital to share acquired knowledge in various fields of expertise to gather valuable feedback and engage with potential end-users. Sharing knowledge can also strengthen the communication within multidisciplinary teams as team members can learn more about each other’s field of expertise. Moreover, digital interventions designed by multi-disciplinary teams, particularly those with a strong art and design foundation can reach a bigger audience and impact people’s wellbeing in new and creative ways (e.g., by showcasing them in public places). Taken together, the current dissertation demonstrates the strength of collaborations between artists and scientists to develop innovative, playful, and meaningful digital interventions which can motivate and help people feel empowered to improve their wellbeing.


Where are we now?

Following our research, the DEEP team now aim to bring DEEP to the masses. In addition, in collaboration with health care partners we are finding new ways in which DEEP could contribute to people's well-being. For example, we are exploring whether DEEP could be used to help youth who have experienced trauma. Furthermore, we are exploring ways in which DEEP can be used in the current Covid-19 pandemic to relieve the stress of front-line medical workers or support people's recovery from the virus. Check out the DEEP website for updates.

Publications

  • An Integrative Model for the Effectiveness of Biofeedback Interventions for Anxiety Regulation: Viewpoint

    Weerdmeester, J., van Rooij, M. M., Engels, R. C., & Granic, I. (2020). Journal of Medical Internet Research, 22(7), e14958.

    Author: Joanneke Weerdmeester

    Upload date: 07-23-2020

  • Efficacy of a Virtual Reality Biofeedback Game (DEEP) to Reduce Anxiety and Disruptive Classroom Behavior: Single-Case Study

    Bossenbroek, R., Wols, A., Weerdmeester, J., Lichtwarck-Aschoff, A., Granic, I., & van Rooij, M. (2020). JMIR Mental Health, 7(3), e16066. http://dx.doi.org/10.2196/16066

    Author: Aniek Wols

    Upload date: 03-24-2020

  • Exploring the Role of Self-efficacy in Biofeedback Video Games

    Weerdmeester, J., van Rooij, M., Harris, O., Smit, N., Engels, R. C., & Granic, I. (2017, October). In Extended Abstracts Publication of the Annual Symposium on Computer-Human Interaction in Play (pp. 453-461). ACM.

    Author: Joanneke Weerdmeester

    Upload date: 10-15-2017

  • DEEP: A Biofeedback Virtual Reality Game for Children At-risk for Anxiety

    van Rooij, M., Lobel, A., Harris, O., Smit, N., & Granic, I. (2016). CHI'16 Extended Abstracts, May 07-12, 2016, San Jose, CA, USA

    Author: Marieke van Rooij

    Upload date: 05-07-2016

Project team

Joanneke Weerdmeester title=
Joanneke Weerdmeester
Reseacher and consultant at GEMH Lab

Behavioural scientist, lecturer, consultant, gamer, dungeon master, language enthusiast, and lover of all things geeky. Passionate about creating and validating interventions and interactive experiences that can help us understand and manage our well-being in a playful and meaningful way.

Function

Freelance Consultant

Contact

E-mail Joanneke

Isabela Granic title=
Isabela Granic
Director of GEMH Lab

Professor and Chair of the Developmental Psychopathology department in the Behavioural Science Institute; writer; voracious podcast consumer; mother of two upstanding little gamers

Function

Professor at McMaster's University

Contact

E-mail Isabela

Rutger Engels title=
Rutger Engels

Function

CEO at Trimbos Institute / Professor Developmental Psychopathology Utrecht University

Contact

E-mail Rutger

Marieke van Rooij title=
Marieke van Rooij

Assistant prof. and data geek at the GEMH lab, dynamical modelling, personalisation, wants to put the I back into AI, news junkie, cat lover.

Function

Assistant Professor

Contact

E-mail Marieke

Sources

All sources

Dedeepya, P., Nuvvula, S., Kamatham, R., & Nirmala, S. V. (2014). Behavioural and physiological outcomes of biofeedback therapy on dental anxiety of children undergoing restorations: a randomised controlled trial. Eur Arch Paediatr Dent, 15(2), 97-103. https://doi.org/10.1007/s40368-013-0070-3

Gilbert, C. & Moss, D (2003). Biofeedback and biological monitoring. Handbook of mind-body medicine in primary care: Behavioral and physiological tools, 109-122.

Goessl, V. C., Curtiss, J. E., & Hofmann, S. G. (2017). The effect of heart rate variability biofeedback training on stress and anxiety: a meta-analysis. Psychol Med, 47(15), 2578-2586. https://doi.org/10.1017/S0033291717001003

Gross, J. J. (2002). Emotion regulation: Affective, cognitive, and social consequences. Psychophysiology, 39(3), 281-291. https://doi.org/10.1017.S0048577201393198

Hammond, D. C. (2005). Neurofeedback treatment of depression and anxiety. J Adult Dev, 12(2-3), 131-137. https://doi.org/10.1007/s10804-005-7029-5

Hammond, D. C. (2007). What is neurofeedback? J Neurother, 10(4), 25-36. https://doi.org/10.1300/J184v10n04_04

Kazdin, A. E. (2014). Moderators, mediators and mechanisms of change in psychotherapy. In W. Lutz & S. Knox (Eds.), Explorations in mental health. Quantitative and qualitative methods in psychotherapy research (pp. 87-101). Routledge/Taylor & Francis Group.

Kever, A., Pollatos, O., Vermeulen, N., & Grynberg, D. (2015). Interoceptive sensitivity facilitates both antecedent-and response-focused emotion regulation strategies. Pers Individ Dif, 87, 20-23. https://doi.org/10.1016/j.paid.2015.07.014

Lehrer, P. M., Vaschillo, E., & Vaschillo, B. (2000). Resonant frequency biofeedback training to increase cardiac variability: Rationale and manual for training. Appl Psychophysiol Biofeedback, 25(3), 177-191. https://doi.org/10.1023/A:1009554825745

Parnandi, A., & Gutierrez-Osuna, R. (2017). Physiological modalities for relaxation skill transfer in biofeedback games. IEEE J Biomed Health Inform, 21(2), 361-371. https://doi.org/10.1109/JBHI.2015.2511665

Richardson, K. M., & Rothstein, H. R. (2008). Effects of occupational stress management intervention programs: a meta-analysis. Journal of occupational health psychology, 13(1), 69-93. https://doi.org/10.1037/1076-8998.13.1.69

Schoenberg, P. L., & David, A. S. (2014). Biofeedback for psychiatric disorders: a systematic review. Applied psychophysiology and biofeedback, 39(2), 109-135.

Schwartz, M. S., & Andrasik, F. (2017). Biofeedback: A practitioner's guide (M. S. Schwartz & F. Andrasik, Eds. 4th. ed. ed.). Guilford Publications.

Tolin, D. F., Davies, C. D., Moskow, D. M., & Hofmann, S. G. (2020). Biofeedback and neurofeedback for anxiety disorders: a quantitative and qualitative systematic review. In Y.-K. Kim (Ed.), Anxiety disorders. Rethinking and understanding recent discoveries. (pp. 265-291). Springer Nature Singapore, Pte Ltd. . https://doi.org/10.1007/978-981-32-9705-0

Wheat, A. L., & Larkin, K. T. (2010). Biofeedback of heart rate variability and related physiology: A critical review. Applied psychophysiology and biofeedback, 35(3), 229-242.

Yucha, C., & Montgomery, D. (2008). Evidence-based practice in biofeedback and neurofeedback. Wheat Ridge, CO: AAPB.

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