www.ulster.ac.uk/nicheat the core of nutrition researchniche
Northern Ireland Centre for Food and Health
A Proposed Framework For Supporting Behaviour Change By Translating Personalised
Activities into Measurable Benefits
Background § Our aim is to examine the case for suppor2ng behaviour change in pre-‐diabe2c
obese people in order to improve their health. § In the sec2ons of this poster, we set out the:
§ Objec2ves, background and mo2va2on for suppor2ng behaviour change
§ Relevant literature in this health and wellbeing area § Feasibility of SmartLife -‐ a person-‐driven applica2on involving
healthcare prac22oners and peer support interac2on
Objec6ves The ambi2on of our proposed framework is to: bring together experts in different disciplines to address a common problem; that of contributory factors to obesity and the development of type 2 diabetes among these at-‐risk individuals
The innova2on focus is on novel approaches to change behaviour facilitated through a soGware solu2on that is accessed by users via their social media, for example, Facebook. We also focus on failure-‐free, posi2ve reinforcement, person empowerment and wellbeing. Healthcare professionals can also use the framework, to monitor their pa2ents or clients and assess behaviour change.
Review of literature Obesity is claimed to be the world's largest single cause of mortality and morbidity in the 21st Century. Major contributors to the obesity epidemic include: -‐ Economic -‐ Technological and social changes (e.g., promote a sedentary lifestyle with easy
access to low-‐cost, calorie dense, high-‐fat food ) § The management of obesity, diabetes and other chronic diseases is based on the
interac2on between ini2a2ves and resources on the part of pa2ents, rela2ves, and healthcare professionals.
§ A modern pa2ent centred approach to care has evolved from an acute-‐care paradigm where treatment now supports pa2ents in gradually becoming their own treatment experts, and thus the balance in shared responsibili2es is shiGing over 2me to pa2ents and their families (Brink et al. 2002).
§ Informa2on technology has also undergone rapid development impac2ng significantly on social life and modes of communica2on while technical advances have provided a founda2on for proac2ve health systems that use informa2on from mul2ple sources for support aimed at improved health and avoidance of health risks (Eysenbach, 2008).
§ The possibility for informal and self-‐directed informa2on seeking by individuals, implying that the individual is in command of what informa2on should be sought and why it is important (Eysenbach, 2008) has helped drive a con2nuously greater propor2on of online health-‐related informa2on, created and maintained by individuals other than healthcare professionals, such as other pa2ents (Eysenbach, 2008).
§ The eHealth resolu2on WHA58.28, approved in 2005 by the World Health Assembly, stresses the importance of eHealth (WHO, 2005) – urging member states to develop eHealth services and create long-‐term strategic plans for development and specific implementa2on.
§ Although modern treatment of diabetes includes individualised educa2on, intense mul2ple-‐dose treatment regimens, ac2ve self-‐control, and new insulin and insulin delivery technologies, a large propor2on of pa2ents are s2ll at risk of acute and/or long-‐term complica2ons.
§ Internet-‐based interven2ons may improve access to health services, pa2ent educa2on, and quality of care, and have also been reported to influence pa2ents’ health care u2lisa2on, behaviour, a\tudes, knowledge, skills, and, to some extent, metabolic control (Jackson et al. 2006; McMahon et al. 2005; Blonde & Parkin, 2006).
References 1. Blonde, L., Parkin, C.G. (2006). Internet resources to improve health care for pa2ents with diabetes. Endocrine
Prac2ce. 2006;12 Suppl 1(suppl 1):131–7. 2. Brink, S.J., Miller, M., Moltz, K.C. (2002). Educa2on and mul2disciplinary team care concepts for pediatric and
adolescent diabetes mellitus. Journal of Paediatric Endocrinology and Metabolism. 15(8):1113–30. 3. Büchner, A.G, Mulvenna, M.D, (1998) Discovering Internet Marke2ng Intelligence Through Online Analy2cal
Web Usage Mining, ACM SIGMOD Record, 27(4): 54-‐61, ACM. 4. Teysenbach, G. (2008). Medicine 2.0: social networking, collabora2on, par2cipa2on, apomedia2on, and
openness. Journal of Medical Internet Research. 10(3):e22. 5. Fisher, J.D. and Fisher, W.A. (1992). Changing AIDS-‐Risk Behaviour. Psychological Bulle2n, 111:455-‐474. 6. Jackson, C.L., Bolen, S., Branca2, F.L., Bams-‐Turner, M.L., Gary, T.L. (2006). A systema2c review of interac2ve
computer-‐assisted technology in diabetes care. Interac2ve informa2on technology in diabetes care. Journal of General Internal Medicine. 21(2):105–10.
7. Maio, G., Manstead, A., Verplanken, B. et al. (2007). Lifestyle Change. Evidence Review. Foresight Tackling Obesi2es: Future Choices. hmp//www.foresight. gov.uk
8. McMahon, G.T., Gomes, H.E., Hickson-‐Hohne, S., Hu Tang, M.J., Levine, B.A., Conlin, P.R. (2005). Web-‐based care management in pa2ents with poorly controlled diabetes. Diabetes Care. 28(7):1624–9.
9. Mulvenna, M.D., Anand, S.S., & Büchner, A.G., (eds.), (2000) Personaliza2on on the Net using Web Mining, Communica2ons of the ACM Special Sec2on, 43(8):122-‐125, ACM.
10. Na2onal Ins2tute for Health and Clinical Excellence (2011). Centre for Clinical Prac2ce, Quality Standards Programme for Diabetes in adults. Na2onal Ins2tute for Health and Clinical Excellence. hmp://www.nice.org.uk/media/FCF/87/DiabetesInAdultsQualityStandard.pdf
11. World Health Organiza2on Regional Office for Europe. (2005). [accessed:28-‐02-‐2013]. World Health Assembly resolu2on on eHealth (WHA58.28) hmp://apps.who.int/gb/ebwha/pdf_files/WHA58/WHA58_28-‐en.pdf
Conclusions In summary, the proposed SmartLife framework will draw upon the exper2se and experience of a mul2-‐disciplinary team and devise a solu2on that uses social media, and iden2fies real benefits for users, based upon the use of a personalised assessment profile. The advice will be ‘failure-‐free’, based on a posi2ve wellbeing perspec2ve, and focus on changing people’s health-‐related behaviour.
Discussion and proposed methodology § The goal of our framework is health-‐related behaviour change.
§ To achieve this, the framework seeks to help individuals understand the short, medium and longer-‐term consequences of health-‐related behaviour; and helping them to feel posi2ve about the benefits and value of health-‐enhancing behaviours and changing their behaviours.
§ Integral to achieving this is a framework capable of recognising and incorpora2ng how individual’s social contexts and rela2onships may affect their behaviour-‐ a fundamental aspect of helping people plan changes in their lifestyle ( Na2onal Ins2tute for Health and Care Excellence ([NICE], UK, 2011).
§ Alongside quan2ta2ve physiological measures it is the ambi2on of the designers to incorporate and assess addi2onal psychological factors which are acknowledged to influence behaviour change including, habits, beliefs, transla2ng inten2on into ac2on, automa2c a\tudes versus self-‐reported a\tudes, and moral climate within the framework (Maio et al. 2007).
§ As part of this task, it is an2cipated that the framework’s design will take into account the social dialogue nuances prevalent between the users of the SmartLife system, helping to provide more personalised and context/situa2on specific advice while simultaneously facilita2ng peer support and communica2on.
§ A key innova2on will be the use of a bespoke personalisa2on algorithm that translates an individual’s ac2vi2es into quan2fiable measurable benefits (Mulvenna et al. 2000; Büchner & Mulvenna, 1998).
§ The of the SmartLife framework is to formulate an interven2on that goes beyond informa2on campaigns to simultaneously inform, support, shiG mo2va2on and provide the necessary skills to lead to behaviour change (Fisher & Fisher, 1992).
§ The methodology for future work is grounded on an approach which is validated across the different disciplines involved, encompassing psychology, social informa6cs, social media, diete6cs as well and health and wellbeing knowledge.
§ The methodology is to devise a framework where people can self-‐register to self-‐manage their wellbeing, and implicit measures are obtained based on the 2me, frequency and wellbeing value of the interven2ons and mediated messages between the system, health and wellbeing advisors in the system and the users themselves.
Corresponding author: Maurice Mulvenna Email: [email protected]
Maurice Mulvenna1, Adrian McCann2, Maurice O’Kane3, Barry Henderson3, Karen Kirby4 and Deirdre McCay5 1TRAIL Living Lab, School of Computing & Mathematics, University of Ulster, UK 2Biomedical Sciences Research Institute, University of Ulster, UK 3C-TRIC (Clinical Translational Research and Innovation Centre), Western Health and Social Care Trust, Altnagelvin Hospital, UK 4Psychology Research Institute and School of Psychology, University of Ulster, UK 5Western Health and Social Care Trust, Altnagelvin Hospital, UK
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