Horizon CDT Research Highlights

Research Highlights

Enchanted Objects for Health Behaviour Change

  Yitong Huang (2014 cohort)   uk.linkedin.com/in/huangyitong

1. Introduction

There is an increasing number of technologies, including wearable gadgets, dedicated to increasing the physical activity and fitness level of their users. But in my PhD, I am looking beyond “gadgets” and trying to extend the ecosystem of health persuasive technology [1] to everyday mundane objects "enchanted" [2] by embedded sensing and computing technologies. To explore potential design and social issues around such applications, which I believe will be popularised in the consumer market within a decade, I am building the case of an enchanted object-based system that persuades office workers to take more regular active work breaks.

2. Research gap

The Behaviour Change Wheel [3], together with the Behaviour Change Technique (BCT) Taxonomy (v1) [4] is considered the most current comprehensive framework/tool for unpacking behaviour change challenges and deriving theory-informed interventions. A number of digital interventions to increase physical activities have been developed using the model. A group of researchers at UCL are also improving the toolkit by establishing a link between mechanism of change and choice of BCTs. However, what is still lacking is an understanding of the interaction between mode of delivery and choice of BCTs. So as part of the theoretical contributions of my PhD, I will explore difference between using an enchanted object and an app to deliver BCTs like self-monitoring and prompts/cues.

On the other hand, most of current engineering/computing/tech-industrial projects exploring the potential of IoT in promoting healthy living are focused on creating high end products with little reference to previous research in health or behavior science. There is a need for bringing the rigour of evidence-based practice to designing IoT-based health behaviour change products.

3. Potential value

UbiComp can enhance Health Behaviour change in at least three aspects: scalable personalised persuasion, time-intensive repeated measures and just-in-time intervention harnessing context-aware algorithms. So I believe IoT will become the trend of persuasive technology in the near future. Once some technology becomes a trend, its hardware and software features will be rapidly-evolving (just think about health and fitness apps now). However, a number of theoretical considerations, HCI design issues and concerns in terms of social acceptability will remain valid. Those are the things I am trying to study now.

4. External partner

Throughout my PhD, I will work with Unilever UK, which is not only a leading fast moving consumer goods (FMCG) company, but also an organisation with an interest in bringing together digital technology and behavioural science to promote sustainable and healthy living among consumers.

5. Methodology

For the intervention design, I am applying the Behaviour Change Wheel [3] and Theoretical Domain Framework [5] and drawing on health science methods such as systematic literature search and review, diary methods, semi-structured interviews, framework analysis, and process evaluation [6]. As for technology design, I am applying HCI methods such as rapid prototyping, technology probe and Wizard-of-Oz.

6. Research questions

  1. What activities/contexts can and cannot be captured by sensors attached to products, infrastructure, wearables respectively?
  2. How feasible and acceptable is it to deliver behaviour change interventions to reduce sedentary behaviours in office workers using "enchanted object" [2]? What are the pros and cons for this mode of delivery compared with screen-based digital media?

References

  1. B. Fogg, “A behavior model for persuasive design,” Proc. 4th Int. Conf. Persuas. Technol. - Persuas. ’09, p. 1, 2009.

  2. D. Rose, Enchanted Objects: Design, Human Desire, and the Internet of Things. Simon and Schuster, 2014.

  3. S. Michie, M. M. van Stralen, and R. West, “The behaviour change wheel: A new method for characterising and designing behaviour change interventions.,” Implement. Sci., vol. 6, no. 1, p. 42, 2011.

  4. S. Michie, M. Richardson, M. Johnston, C. Abraham, J. Francis, W. Hardeman, M. P. Eccles, J. Cane, and C. E. Wood, “The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: Building an international consensus for the reporting of behavior change interventions,” Ann. Behav. Med., vol. 46, no. 1, pp. 81–95, 2013.

  5. S. D. French, S. E. Green, D. A. O’Connor, J. E. McKenzie, J. J. Francis, S. Michie, R. Buchbinder, P. Schattner, N. Spike, and J. M. Grimshaw, “Developing theory-informed behaviour change interventions to implement evidence into practice: a systematic approach using the Theoretical Domains Framework.,” Implement. Sci., vol. 7, no. 1, p. 38, Jan. 2012.

  6. G. F. Moore, S. Audrey, M. Barker, L. Bond, C. Bonell, W. Hardeman, … J. Baird, (2015). Process evaluation of complex interventions: Medical Research Council guidance. BMJ (Clinical Research Ed.), 350(mar19_6), h1258.

Publications

  1. Huang, Y., Skatova, A., Bedwell, B., Rodden, T., Shipp, V., & Bertenshaw, E. (2015). Designing for Human Sustainability. In Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct - MobileHCI ’15 (pp. 1042–1045). New York, New York, USA: ACM Press. http://dl.acm.org/citation.cfm?id=2794323
  2. Skatova, A., Bedwell, B., Shipp, V, Huang, Y., Young, A., Rodden, T. (2016). The Role of ICTin Office Work Breaks CHI'16, San Jose, CA, USA. http://dl.acm.org/citation.cfm?doid=2858036.2858443
  3. Huang Y. (2016). How to Design Internet of Things to Encourage Office Workers to Take More Regular Micro-Breaks In: Proceedings of the European Conference on Cognitive Ergonomics. 32:1-32:3
  4. Huang, Y., Benford, S., Hendrickx, H., Treloar, R., and Blake, H. (2017). Office Workers’ Perceived Barriers and Facilitators to Taking Regular Micro-breaks at Work: A Diary-Probed Interview Study. PERSUASIVE '17. Lecture Notes in Computer Science (LNCS). 10171. Springer, Cham. 149-161

This author is supported by the Horizon Centre for Doctoral Training at the University of Nottingham (RCUK Grant No. EP/L015463/1) and Unilever UK Ltd.