A Proposed Framework for Supporting Behaviour Change by

Translating Personalised Activities into Measurable Benefits

Maurice Mulvenna

, Adrian McCann

, Maurice O’Kane

, Barry Henderson

, Karen Kirby

and Deirdre McCay

TRAIL Living Lab, School of Computing & Mathematics, University of Ulster, Newtownabbey, U.K.

Biomedical Sciences Research Institute, University of Ulster, Jordanstown, U.K.

C-TRIC (Clinical Translational Research and Innovation Centre), Western Health and Social Care Trust,

Altnagelvin Hospital, Derry, U.K.

Psychology Research Institute and School of Psychology, University of Ulster, Northland Road, Londonderry, U.K.

Western Health and Social Care Trust, Altnagelvin Hospital, Derry, U.K.

Keywords: Healthcare, Wellbeing, Social Media, Mobile, Social Networks, Usability, e-Health Applications,

Personalised Services, Behaviour Change.

Abstract: The aim of this position paper is to examine the case for supporting behaviour change in pre-diabetic obese

people in order to improve their health. The paper sets out the background and motivation for supporting

behaviour change before outlining the relevant literature in this health and wellbeing area. The paper then

explores the feasibility of SmartLife - a patient-driven application involving healthcare practitioners and

peer support interaction with a focus on failure-free, positive reinforcement, patient empowerment and

wellbeing.

1 INTRODUCTION

Obesity significantly increases the risk of

developing various life-threatening diseases,

including type 2 diabetes, hypertension, coronary

heart disease, stroke and certain cancers

(http://www.iotf.org/). The worldwide incidence of

obesity in adults is estimated to exceed 300 million

people (http://www.who.int/nut), with countries like

the USA having the highest recorded prevalence of

more than 30% adults being obese

(http://www.cdc.gov/nchs). In Europe, among the 19

Member States for which data are available, the

proportion of overweight and obese people in the

adult population varied in 2008/09 between 36.9%

and 56.7% for women and between 51% and 69.3%

for men (Eurostat, 2011). In the United Kingdom

(UK), the proportions of obesity for women was

recorded as 23.9% and as 22.1% for men, equivalent

to around 14.5 million UK adults. The prevalence of

obesity has more than doubled in the last 25 years in

the UK. In England, nearly a quarter of adults and

about 10% of children are now obese, with a further

20–25% of children overweight. In Northern Ireland,

59% of adults are either overweight (36%) or obese

(23%). This obesity percentage equates to 326,000

adults in Northern Ireland. Foresight’s (2007)

extrapolations suggest that we can anticipate some

40% of Britons being obese by 2025. By 2050, the

UK could be a mainly obese society (DHSSPS,

2012).

2 BACKGROUND

The benefits attributed to healthy diet and increased

physical activity levels (both psychological and

physiological) are often overlooked in favour of

‘weight loss’, as the primary objective or goal. In

light of the increasing prevalence of obesity and

obesity related chronic disease and ill-health, it is

plausible that the prioritising of weight loss, and the

constant barrage of negative weight loss messages

and reinforcement, has had a detrimental impact on

any motivation to change and/or continue ‘healthy’

lifestyle practices among at risk individuals and the

population in general.

306

Mulvenna M., McCann A., O’Kane M., Henderson B., Kirby K. and McCay D..

A Proposed Framework for Supporting Behaviour Change by Translating Personalised Activities into Measurable Beneﬁts.

DOI: 10.5220/0004505803060311

In Proceedings of the 4th International Conference on Data Communication Networking, 10th International Conference on e-Business and 4th

International Conference on Optical Communication Systems (ICE-B-2013), pages 306-311

ISBN: 978-989-8565-72-3

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

The challenges faced by individuals is that they

often perceive themselves as one of the causes of

their situation, and may find it difficult to reach out

to ask for help and advice, advice they anticipate

they will find difficult to follow. For healthcare

organisations, there is often a struggle to provide

effective care for overweight and obsess individuals,

pre-diabetic and diabetes patients. Where lifestyle-

orientated as opposed to pharmacological

interventions are needed, it is often difficult for

healthcare organisations to articulate effective

advice that amounts to more than a need for patients

to simply lose weight.

The opportunity is to devise a communication

facility between obese and individuals in a pre-

diabetes state and the organisations responsible for

their health. The authors propose SmartLife - a

framework underpinned by personalised advice to

the user that is ‘failure-free’. In other words, rather

than the user being informed that they have missed

some target in their interactions with the system,

positive enforcement will be provided. The positive

reinforcement advice provided will take cognisance

of the user’s personal information, including weight,

levels of sedentary versus active behaviour and diet.

Such advice will be presented in the context of

‘wellbeing’ rather than being weight

loss/maintenance oriented, seeking to induce

positive behaviour change.

In our proposed framework, we consider the

customer as either the individual or the organisation

responsible for promoting and/or caring for the

health of the individual. We propose a framework

that will focus on ‘wellbeing’ and ‘peer support’

through the utilisation of a social media interface

similar to Facebook. This will be designed to

motivate individuals to be more proactive with their

health behaviours, whilst avoiding the potentially

detrimental focus on ‘weight loss’ messages and

dogma. By using the user’s personal information it is

anticipated the software will house bespoke

personalisation algorithms that translate the

activities into wellbeing related benefits that are

measurable, tangible and suitable for communication

to friends and family via social media. Users will

interact with the system using social media the data

will also be available on a custom built portal for

healthcare professionals to access. While the

designers aim to avoid the completion of a

questionnaires-like format to measure benefits, the

software will seek to quantify physiological and

psychological benefits by incorporating factors such

as glycaemic control and lipid profile (available via

routine medical assessment and check-up) combined

with a monitoring of social interaction activities with

peers, family and friends. The business model for

the concept is based on a model of ‘free to users’,

but funded by the healthcare providers.

The ambition in 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. Our

innovation is to focus on novel approaches to change

behaviour facilitated through a software solution that

is accessed by users via their social media, for

example, Facebook. Healthcare professionals will

also use the framework, to monitor their patients or

clients and assess behaviour change.

3 REVIEW OF THE

LITERATURE

Obesity is claimed to be the world's largest single

cause of mortality and morbidity in the 21st Century.

The major contributors to the obesity epidemic

are the economic, technological and social changes,

which appear to promote a sedentary lifestyle with

easy access to low-cost, calorie dense, high-fat food

acting as the key factors fuelling this epidemic.

Researchers and health professionals have trialled

and tested all sorts of interventions to tackle the

obesity explosion, however, evidence questions the

effectiveness of these interventions (Cheetham et al.,

2004). Previous research has demonstrated the

efficacy of intensive lifestyle intervention in

preventing progression of pre-diabetes to diabetes

(Tuomilehto et al., 2001); (Knowler et al., 2002).

However, interventions that have been effective in a

clinical trial setting have proven difficult to

implement in routine clinical practice because the

patient support required is often resource intensive.

There is therefore a need to develop efficacious and

cost effective interventions to support lifestyle

modification for at-risk individuals.

There are many considerations as to why some

interventions fail, and a number relate to the way in

which health information/advice is traditionally

delivered. To help people become aware of their

health risks, health professionals need to clearly

inform their ‘patient’, in plain ‘lay man’s terms’,

what will happen if they cannot change their

lifestyle. This sometimes involves telling the patient

that they are at risk of type 2 diabetes and its

complications such as diabetic retinopathy,

neuropathy leading to amputations, nephropathy

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leading to kidney disease, heart disease - to include

stroke and myocardial infarction. The health

professional, in some ways, has an ethical obligation

to do this, as they must fully inform their ‘patient’ of

the risk and consequences of their precarious health

situation. Although this is carried out in a skilled

way, highlighting the severe consequences of

obesity, it can serve as another negative reminder of

the sad situation in which, they find themselves.

Such negative information may serve to add further

anxiety and worry, to the already existing layer of

anxiety/depression, which potentially contributed to

their already unhealthy lifestyle and level of

overweight /obesity. For instance, research has

shown that such psychological distress can influence

binge eating episodes, drinking more alcohol to

cope, with depressive symptoms leading to even

further inactivity and sedentary behaviour, shown

also to be linked with the onset of type 2 diabetes for

example (Golden et al., 2008); (Knol et al., 2006).

These factors are said to create a vicious cycle,

which serves to entrap the person into their current

unhealthy ‘obese’ state. As health complications

begin to manifest, so too do the negative vicious

psychological and behavioural lifestyle cycles.

In an attempt to avoid the negative cycle and

further support patients and reinforce positive health

messages health professionals, have used

‘motivational interviewing’ and psychological

constructs such as the ‘stages of change model’ to

frame the approach to their work have been used.

However, the efficacy of these interventions is

unclear (Kirk et al., 2004; 2009). Interventions

involve some health education, which by its nature,

will have to fully inform the person of the

threatening situation they are in, followed by a phase

of contemplation and sometimes support with the

hope that this will instil action – an approach which

works for some people, but not all.

The management of obesity, diabetes and other

chronic diseases is based on the interaction between

initiatives and resources on the part of patients,

relatives, and health care professionals. A modern

patient centred approach to care has evolved from an

acute-care paradigm where treatment now supports

patients in gradually becoming their own treatment

experts, and thus the balance in shared

responsibilities is shifting over time to patients and

their families (Brink et al. 2002). In recent decades,

healthcare practitioners have made efforts to

enhance peer-to-peer support and learning with

activities such as group education, mailing list

discussion groups, and chat rooms (Gage et al. 2004;

Murphy et al., 2007); (Viklund et al., 2007).

Information technology has also undergone rapid

development impacting significantly on social life

and modes of communication while technical

advances have provided a foundation for proactive

health systems that use information from multiple

sources for support aimed at improved health and

avoidance of health risks (Eysenbach, 2008). Such

systems are increasingly connected to the world

around them through the use of portable devices,

such as laptops and cell phones which allows

increased user participation in developing and

managing content. This has changed the nature and

value of the information, and expanded the

possibility for informal and self-directed information

seeking by individuals, implying that the individual

is in command of what information should be sought

and why it is important (Eysenbach, 2008).

Furthermore, A continuously greater proportion of

online health-related information is created and

maintained by apomediation from individuals other

than healthcare professionals, such as other patients

(Eysenbach, 2008).

The eHealth resolution WHA58.28, approved in

2005 by the World Health Assembly, stresses the

importance of eHealth (WHO, 2005). The resolution

urges member states to make a range of efforts to

develop eHealth services for all health sectors and

create long-term strategic plans for development and

specific implementation, such as reaching

communities and vulnerable groups with services

appropriate to their needs (WHO, 2005).

Although modern treatment of diabetes includes

individualised education, intense multiple-dose

treatment regimens, active self-control, and new

insulin and insulin delivery technologies, a large

proportion of patients are still at risk of acute and/or

long-term complications (The Diabetes Control and

Complications Trial, 1993). For patients with

diabetes, Internet-based interventions may improve

access to health services, patient education, and

quality of care, and have also been reported to

influence these patients’ health care utilisation,

behaviour, attitudes, knowledge, skills, and, to some

extent, metabolic control (Jennett et al., 2003);

(Jackson et al., 2006); (McMahon et al., 2005);

(Blonde and Parkin, 2006). Improved quality of life

has also been reported, but overall, there has been

little focus on patient perspectives in clinical studies

(Verhoeven et al., 2007).

Changing people’s health-related behaviour is

the goal of our framework. This will involve helping

individuals to understand the short, medium and

longer-term consequences of health-related

behaviour; and helping them to feel positive about

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the benefits and value of health-enhancing

behaviours and changing their behaviours. To do

this, it will be important for our framework to

recognise and incorporate how individual’s social

contexts and relationships may affect their

behaviour- a fundamental aspect of helping people

plan changes in their lifestyle. In line with the

National Institute for Health and Care Excellence

(NICE, UK) recommendations SmartLife will seek

to assist individuals in making easy sustainable steps

over time as well as identifying and planning for

situations that might undermine the positive changes

individuals are trying to make (NICE, 2011).

Alongside quantitative physiological measures it

is the ambition of the designers to incorporate and

assess additional psychological factors which are

acknowledged to influence behaviour change

including, habits, beliefs, translating intention into

action, automatic attitudes versus self-reported

attitudes, and moral climate within the framework

(Maio et al., 2007).As part of this task, it is

anticipated 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/situation

specific advice while simultaneously facilitating

peer support and communication. Developing

SmartLife in the guise of a psychosocial model will

require the inclusion of monitors and triggers to

detect factors such as habits, beliefs and attitudes.

The challenge will be to remain flexible in order to

continually assess each individual’s unique

disposition (both physiological and psychological)

allowing for ad hoc feedback and support. A key

innovation will be the use of a bespoke

personalisation algorithm that translates an

individual’s activities into quantifiable measurable

benefits (Mulvenna et al., 2000); (Büchner and

Mulvenna, 1998).

Low income people and families are over-

represented within the obese, pre-diabetes and type 2

diabetes populations. Research has demonstrated

that successful management of modifiable risk

factors in patients with type 2 diabetes can be

achieved in a way that is independent of socio-

economic position (O’Kane et al., 2010). A long-

term ambition of SmartLife is to target such low

income at-risk population and Stead (2006) suggests

that products and services can be successfully

marketed to low-income consumers by various

means. We will examine such approaches and of key

importance is ‘value-brand’ – suggesting for

SmartLife to be truly effective ‘as a value brand it

needs to offer low-income consumers real

[quantifiable] benefits’ (Davidson, 2000). As we

seek to identify real user benefits, the development

and evolution of SmartLife will further explore this

value-brand concept.

4 DISCUSSION AND PROPOSED

METHODOLOGY

We know that the major contributors to the obesity

epidemic are the economic, technological and social

changes, which appear to promote a sedentary

lifestyle. Technology is one of the factors which

have hastened the obesity epidemic in the first

instance, and our premise in the proposed

framework is that it is technology which may assist

to hastily reverse said damage. This is why we

propose to use social media to develop specialised

health applications to support the positive cognitive

behavioural change and associated lifestyle practices

and health implications. Scientific results have

proven the efficacy of this method in communicating

using a cognitive behavioural therapy approach (van

Bastelaar, 2011). The efficacy of the cognitive

behavioural theories we are using to design our

social media approach have previously been

demonstrated and we can also draw upon the

literature concerning community-based participatory

research engaging with people at-risk of type 2

diabetes (Vivian, 2010). The designers believe that

the SmartLife framework will be an intervention that

goes beyond information campaigns to

simultaneously inform, support, shift motivation and

provide the necessary skills to lead to behaviour

change (Fisher and Fisher, 1992).

The methodology for future work is grounded on

an approach which is validated across the different

disciplines involved, encompassing psychology,

social informatics, social media, dietetics as well and

health and wellbeing knowledge. The methodology

is to devise a framework where people can self-

measures are obtained based on the recency,

frequency and wellbeing value of the interventions

and mediated messages between the system, health

and wellbeing advisors in the system and the users

themselves.

5 CONCLUSIONS

In summary, the proposed framework will draw

upon the expertise and experience of a multi-

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disciplinary team and devise a solution that uses

social media, identifies real benefits for users, based

upon the use of a personalised assessment profile.

The advice will be ‘failure-free’, based on a positive

wellbeing perspective, and focus on changing

people’s health-related behaviour.

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