MOBILE APPLICATION SUPPORTED LIFESTYLE

INTERVENTION TO LOWER PROSTATE CANCER RISK

Luuk P. A. Simons

and J. Felix Hampe

Computer Science, Delft University of Technology, Mekelweg 4, Delft, Netherlands

Institute for IS research, Koblenz University, Koblenz, Germany

Keywords: Smart phone, Mobile application, Lifestyle intervention, Health, Motivation, Patient Support, Prostate

Cancer, Service design, Design research.

Abstract: There is an existing Health (e)Coach Solution for supporting intensive lifestyle changes, which may help

reduce cancer progression risks in men with low grade prostate cancer. An important challenge is to support

and motivate healthy behaviors for the long term (4 years). Smart phones are increasingly used also in this

age group. And mobile apps offer significant opportunities for personalized health behavior monitoring and

support. Our overall proposition is that an mApps suite, as an extension to an existing online dashboard with

automated emails and interpersonal coach sessions, appears promising for improving long term health

behavior support. That is, if three conditions are met: 1) Using best of breed mApps from the market

(benefits like ease-of-use, continuity, customer support); 2) creating easy and meaningful score conversions

(from mApps to personal dashboard); 3) using automated emails as glue between three key aspects personal

progress/dashboarding, user attention and motivation, mApp usage.As methodological approach, this paper

focuses on two phases from a design research cycle: requirements analysis and a preliminary design solution

exploration. In the analysis phase, two questions are addressed: What are effective lifestyle intervention

components according to literature? What are solution properties that may enhance motivation and improve

health behaviors? In the solution exploration phase our design question is how a proposed mApp extension

may likely add value to the existing Health (e)Coach solution.

1 INTRODUCTION

This paper bridges the two worlds of health and ICT

(Information & Communication Technology). After

the methodology introduction, the first part of the

paper explores the extent of potential benefits from

extensive lifestyle interventions for prostate cancer

patients. The second part analyzes requirements for

a proposed extension with smart phone apps in

relation to an existing health (e)Coach solution. This

is partly based on literature and partly on interviews

with the respective health solution provider. Finally,

we describe a preliminary solution.

1.1 Propositions

In summary, our overall proposition is that a smart

phone applications (mApps) suite, as an extension to

an existing online dashboard with automated emails

(i.e. push notification) and interpersonal coach

sessions, appears promising for improving long term

health behavior support for low grade prostate

cancer patients.

This builds on four sub-propositions: 1) A gain

may be achieved in quantity and quality of life for

low grade prostate cancer by enhancing existing

treatments with an intensive healthy lifestyle

intervention. 2) An existing health (e)coach

program, which uses personal e-dashboarding,

intensive health education, interpersonal coaching

and automated personal progress emails, offers

promising results in terms of health beliefs, health

behaviors and health results (Simons and Hampe

2011). Still, more value could be added by bringing

the health experiences and feedback even closer to

the users. 3) Adding a portfolio of best of breed

existing smart phone apps may help improve health

awareness, quality of health beliefs, help improve

health behaviors, increase transparency, fun and

motivation, as well as long term healthy lifestyle

adherence. 4) This rests, however, on a number of

conditions: a) Using best of breed existing smart

phone applications from the market. This brings

443

P. A. Simons L. and Felix Hampe J..

MOBILE APPLICATION SUPPORTED LIFESTYLE INTERVENTION TO LOWER PROSTATE CANCER RISK.

DOI: 10.5220/0003872704430448

In Proceedings of the International Conference on Health Informatics (HEALTHINF-2012), pages 443-448

ISBN: 978-989-8425-88-1

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

benefits like attractiveness, ease-of-use, low cost

implementation, flexible adaptation, continuity, and

high quality customer support per application. b)

Creating easy and meaningful conversions from the

mApps sub-scores to the health progress scores in

the personal dashboard. For example: How many

calories have been burned with intensive exercise

this week? Or: How may fibers or fats have been

consumed this week? The mobile applications in the

portfolio must be selected to provide these types of

sub-scores which can then be translated into the

overall health behavior progress scores in the

personal dashboard. c) Using automated emails as

glue between three key aspects of the solution:

facilitating personal progress feedback (based on the

e-dashboarding), increasing user health attention and

motivation, and automated feedback or compliments

on mApp usage. In other words: using the mApps

must not be a stand-alone activity. It should visibly

increase the value of the personal dashboard and

increase health behavior motivation. Whether

patients already are active mApp users or not, the

weekly email notifications they receive should

integrate and explain their personal e-dashboard

scores (and when active: mApp scores).

Furthermore, this channel mixing increases

awareness and it may motivate non-users to start

using mApps by showing the benefits this generates.

1.2 Design Research Cycle

Our research approach is based on Information

Systems Engineering. It uses the design research

cycle of Vaishnavi and Kuechler (2004) with the

enhancements towards a pluralistic view as

discussed in Frank (2006). Thus we describe the first

two stages of the design cycle (Vaishnavi and

Kuechler, 2004) in this paper. That is: problem

analysis and a motivated suggestion for a design

solution for the problem. For the service concept

design and service implementation only initial

evaluation results are available, a large scale

evaluation is missing. Thus we present research in

progress. Nonetheless, we propose the general

positions and the examplification along the prostate

cancer service platform for discussion and

improvement to the research community.

2 LIFESTYLE IMPACTS

2.1 Large Differences Worldwide

There are large incidence differences worldwide for

several of our common cancers: lung cancer,

colorectal cancer, children’s cancers, as well as

breast cancer and prostate cancer. For prostate

cancer, there is a 100-fold difference in age-

corrected incidence rates. These vary from

0,5/100.000 persons per year in Qidong County in

China in 1997 to around 125/100.000 persons per

year in the USA.

These differences are strongly correlated with an

affluent (Western) lifestyle and diet. Degree of

physical activity, stress and environmental factors

likely play a role, but the hypothesis that diet has an

independent effect is supported by migration studies

which show that Asians who maintain an Asian food

pattern through adolescence while living in the West

have better cancer protection than those who have

adopted Western foods (Wu, 2002).

2.2 Lifestyle Factors

The World Health Organization defines health as

consisting of physical, mental and social health. And

each of these components has an effect on prostate

cancer incidence and mortality. Below we review

studies on four aspects: social support, stress,

physical activity and food.

2.2.1 Social Support

Furthest away from the field of well-grounded

biological pathways is the empirical data regarding

social support and cancers. (Various immune-,

hormonal-, neural- and also behavioral mechanisms

have been proposed, but this field is still young.) On

the one hand there have been several long term

prospective studies over the past decades which have

shown correlations between degree of social support

early in life and cancer incidence and mortality years

later. For example the Alameda study measured

degree of social support among Alameda County

residents and found significantly raised cancer risks

and mortality of all sites during the 17-year follow

up period (Berkman, 1995); (Reynolds and Kaplan,

1990). They found it to be an independent and more

powerful predictor than age, gender, socioeconomic

status and health behaviors. Also marital status has

an impact on five year survival for almost every

category of age, gender and stage of various cancers

(Goodwin, 1987). This was also found specifically

for prostate cancer (Krongrad, 1996). These effects

have been confirmed in recent meta-analyses:

Across 87 controlled studies, having high levels of

perceived social support, larger social network, and

being married were associated with decreases in

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relative risk for mortality of 25%, 20%, and 12%,

respectively. There were stronger associations for

leukemia/lymphomas and breast cancer, but not

enough studies for other cancers to differentiate

effect sizes (Pinquart and Duberstein, 2010). And as

a generic health effect: across 148 studies, the effect

size was OR = 1.50 (95% CI 1.42 to 1.59), 50%

more likelihood of survival with stronger social

relationships, a finding consistent across age, sex,

initial health status, cause of death, and follow-up

period (Holt-Lunstad, 2010).

On the other hand, there is the question how

effective psycho-social interventions are. There was

initial enthusiasm based on successful interventions

(Spiegel, 1989); (Fawzy, 1993), but larger RCTs

have not been able to replicate these results

(Kissane, 2007). Still, it is interesting that in one

study, both control and treatment groups had half the

mortality risk of those who declined to participate in

the study (Boesen, 2007). And another study showed

that those who reduced their degree of depression in

the first year had improved survival, irrespective of

being in the control or treatment group (Giese-

Davis, 2011). An important complexity in this field

is that seeking support has become very normal, and

cancer patients may do so independent of a formal

support group. For example, even the simple yes/no

answer to the question ‘Do you have someone to talk

to in the 3 months after your diagnosis?’ correlated

with a 30% increase (for ‘yes’) in survival after 7

years (Maunsell, 1995). And a review of the psycho-

oncological literature concluded (Garssen, 2004)

that one of the most consistent findings is that: the

more hopelessness and helplessness are experienced,

the more unfavorable the cancer progression is

(Watson 1999); (Goldberg, 1996); (Schulz 1996).

2.2.2 Stress

A next potential factor is the effect of chronic

stress. Potential pathways run via increased cell

aging and and telomere shortening (Epel, 2004);

(Puterman, 2010), increased DNA damage and

hampered DNA repair (Flint, 2007), reduced

immune function (Segerstrom, 2004), increased

levels of inflammatory cytokines (Bower, 2007), and

stress-induced activation of the sympathetic nervous

system (SNS) and hypothalamic–pituitary–adrenal

(HPA) axis which results in the production of

catecholamines and cortisol, which have direct

effects on epithelial cell growth and tumor

vascularization (McGregor, 2009). Besides, there are

higher order mechanisms like stress-induced

depression (for example, depression raised mortality

in men for melanoma, colon and prostate cancer

with 67%: Almeida 2010), reduced self-efficacy and

self-care (Miller, 2001) or the 90% increased cancer

risk due to low perceived quality of life (Flensborg-

Madsen, 2011). For an overview of biological

mechanisms, see McGregor (2009). Next, one study

found that men who experienced high levels of

stress were more than three times as likely to have

elevated PSA levels (Prostate Specific Antigen) than

were men who experienced low levels of stress

(Stone, 1999). And using the breast/prostate cancer

analogy, another large study showed that African

American women who experienced more emotional

stress due to discrimination (on the job, on the street

and by the police) had a 48% increased risk of

developing cancer after six years (Taylor, 2007).

In terms of interventions, cognitive-behavioral

therapy (Philips, 2008) and well as yoga

(Raghavendra, 2009) and meditation programs

(Biegler, 2009) have resulted in lower cortisol

levels, as well as improved mental health and quality

of life (Nidich, 2009); (Beard, 2011); (Chambers,

2011). Survival impacts are not always clear or

made explicit. When they do appear they seem

dependent on improvements in relation to depression

(Giese-Davis, 2011) hopelessness (Garssen, 2004) or

quality of life (Flensborg-Madsen, 2011); (Spiegel

2011).

2.2.3 Physical Activity

Two different effects exist between physical activity

and cancer. The first effect is that sedentary behavior

increases cancer risk, independent of BMI (Body

Mass Index) or other activity. Sedentary behavior is

associated with adverse cardio-metabolic and cancer

mortality; in a review of 18 cancer studies has been

associated with increased colorectal, endometrial,

ovarian, and prostate cancer risk (Lynch, 2010). The

second effect is that vigorous exercise helps reduce

cancer risk. Already in the College Study, running

for over 40 years and following 50.000+

participants, a more than 30% reduction in cancer

mortality risk due to physical exercise across all

cancers was found, including prostate cancer when

exercise is heavy (Paffenbarger, 1986). As one

hypothesized pathway, heavy exercise decreases

testosterone, which in turn is linked to lower prostate

cancer risk.

The EPIC study found an inverse association

between advanced prostate cancer risk and

occupational physical activity - which is inversely

correlated with inactivity throughout the day - but

not with leisure activity (Johnsen, 2009). A study

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specifically designed for investigating the impact on

survival of higher physical activity after prostate

cancer diagnosis, found 46% lower overall mortality

with increased activity and a 61% lower prostate

cancer mortality for those men who had 3 or more

hours weekly of vigorous exercise compared with

less than 1 hour weekly (Kenfield, 2011). Men

exercising vigorously before and after diagnosis had

the lowest risk. And a study focusing on degree of

progression found that men who walked briskly for

3 h/wk or more had a 57% lower rate of progression

than men who walked at an easy pace for less than 3

h/wk (Richman, 2011). Other advantages from

physical activity for prostate cancer survivors are

improved muscular fitness, physical functioning,

fatigue, and quality of life (Thorsen, 2008).

2.2.4 Dietary Factors

One of the best known factors between lifestyle, diet

and cancer is obesity. This link has been reviewed

extensively in the WCRF Research report (WCRF,

2007). Hypothesized pathways include: pro-

inflammatory and angiogenic effects of adipose

tissue, increased oxidative stress on cells in obese

people, and increased blood serum levels in obese

people of insulin, glucose and lipids, which all tend

to promote cancer cell growth. For various cancers,

increased serum levels of insulin, glucose and lipids

as caused by dietary fat, have been shown to

increase tumor growth and aggressiveness,

independent of BMI. For prostate cancer the

evidence is still sparse. Glycemic load appears to

have limited impact (Nimptsch, 2011), but some

protective effects from low fat diets have been found

(Aronson, 2010); (Kobayashi, 2008).

The obesity evidence is ‘convincing’ (WCRF

2007) for cancers of the oesophagus, pancreas,

colorectum, breast (postmenopause), endometrium

and kidney. The link between obesity and prostate

cancer is not free of controversy however. Several

recent studies suggest that obesity increases the risks

of prostate cancer aggressiveness and decreases the

risks in relation to low grade cancers (Gong, 2006);

(Freedland, 2008). Freedland et al go on to suggest

that obesity is biologically associated with increased

risk, although this is obscured owing to

hemodilution of prostate-specific antigen (PSA) and

larger prostate size (which causes cancer-

underestimations during diagnosis). This biological

link was confirmed in another large study showing

that men who lost weight reduced their prostate

cancer risk and those with high BMI were at

increased risk for aggressive prostate cancer

(Rodriguez, 2007).

Chronic inflammation is also relevant: the

(modified) Glasgow Prognosic Score, built on CRP

(C-Reactive Protein) and albumin measurements,

but also other inflammation-based prognostic scores,

predict cancer survival, independent of age, sex,

tumor stage and for all tumor sites. This includes

common cancers like colorectal, breast, lung and

prostate cancer (Proctor 2011-1, Proctor 2011-2).

This may be a protective link from which

fruits/vegetables (Cohen, 2000); (Hodge 2004) and

flaxseed/omega 3 PUFA here, besides reducing

testosterone and androgens (Demark-Wahnefried,

2001; 2008). Recently it has been found that also

aggressive prostate cancer may be attenuated with

leafy (-34%) and high carotenoid vegetables (-29%)

and promoted (+64%) with high glycemic load foods

(Hardin, 2011). Inflammation and CRP levels can be

reduced via diet (Middleton 1998), as well as via

physical activity (Ford, 2002); (Wegge, 2004) and

stress reduction (Fang, 2010); (Oh, 2010).

Furthermore, healthy diet can also help reduce

depression (Akbaraly, 2009); (Jacka, 2010);

(Beezhold, 2010).

Most people are not aware that increased blood

cholesterol levels also indicate an increased cancer

risk, besides increased heart disease risk. This has

been shown for several cancers. For prostate cancer

there are indications that lower cholesterol levels

reduces incidence of the more advanced stages of

prostate cancer (Platz, 2009). Unfortunately,

pathways are still unclear. Still, diet can create large

improvements in cholesterol levels, as can physical

activity and stress management.

Western diets (rich in animal foods and low in

fiber) also tend to raise testosterone levels (Ross,

1994); (Habito, 2001) just like they raise estrogen

levels in women (Campbell, 2006). And increased

serum testosterone is a known prostate cancer risk

factor.

A fifth dietary factor is IGF-1, in concert with a

wider growth factor family which promote cancer

growth. For a review of 194 publications, see Pollak

2008. High circulating levels of IGF’s and low

levels of its binding protein IGFPB-3 are associated

with increased risk of several cancers, including

those of the breast, colorectum (Ma, 2001), lung

(Yu, 1999) and prostate (Chan, 2002); (Chan, 1998).

IGF-1 levels are relatively high in the West, and our

meats and dairy products have seen their IGF-1

levels double over the past decades, whereas IGF-1

has been shown to reach the receptor sites in the gut

in its biologically active form (EU Scientific

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Committee, 1999). Blood levels of IGF-1 are

influenced via diet in multiple ways: most notably

via milk, as shown in cohort studies in men (WCRF,

2007); Ma, 2009) and women (Norat, 2007) as well

as experimentally: for example a Danish study found

a 30% increase in circulating IGF-1 levels when

increasing daily milk consumption from 200 ml to

600 ml daily. Besides IGF-1 increases from dairy

and more mildly from other animal proteins, IGF-1

reductions were found to correlate with increased

vegetable intake (Gunnell, 2003); Norat, 2007).

As a further connection between diet and cancer,

there are the anti-angiogenic properties of foods.

The research groups of Folkman and Li have

categorized many food items according to anti-

angiogenic strength. It turns out that many foods

high in micronutrients (like berries, vegetables,

fruits, spices) also potently block the growth of

blood vessels towards microtumors. See food items

http://www.standup2cancer.org/node/3950?page=1

and effect sizes being compared to anti-cancer drugs

www.ted.com/talks/william_li.html. Hence, the

microtumors will not become full blown tumors.

The anti-angiogenic effect sizes appear similar to

several of the recent FDA approved anti-angiogenic

drugs, based on the zebrafish vessel formation tests

(He, 2009).

On the level of specific dietary product groups

and their effects on prostate cancer, the WCRF

(2007, p 306-308) reports the following:

 On the basis of 20 studies on pulses (legumes)

and 10 studies on soy and soy products: ‘Most

studies showed decreased risk with increased intake.

Meta-analysis of case-control data produced

evidence of an association with legume intake, with

a clear dose-response relationship.’

 Ten studies investigated processed meat: ’All

cohort studies reported increased risk with higher

intake; and most case-control studies also showed

this effect.’

 25 Studies investigated milk and dairy and 38

studies investigated milk: ‘Most of the studies

showed increased risk with increased intake. Meta-

analysis of cohort data produced evidence of a clear

dose-response relationship between advanced/

aggressive cancer risk with milk intake and between

all prostate cancer risk and milk and dairy intake.’

The WCRF report mentions 2 pathways between

milk and prostate cancer: via the IGF axis, and via

downregulation of bioactive vitamin D, thereby

increasing cell proliferation in precancerous cells.

 23 Studies investigated dietary calcium (marker

for dairy intake): ‘Most [of the 9] cohort studies

showed in creased risk with increased calcium

intake; case control studies were inconsistent. Meta-

analysis of cohort data showed an increased risk of

27% per g/day; [and] an increased risk of 32% per

g/day [for advanced or aggressive prostate cancer]’

 On the basis of 10 studies measuring dietary

selenium and 23 studies measuring in vivo selenium

levels: ‘Most studies, including those reporting

separately on advanced/aggressive prostate cancer,

showed decreased risk with increased intake.’

 On the basis of 42 studies on foods containing

lycopene: ‘Most of the studies showed decreased

risk with increased intake. Meta-analysis [ .. ]

showed a 4% decreased risk per 10 microgram

lycopene/liter serum.’

 Foods containing vitamin E, in 38 studies: ‘Most

studies showed decreased risk with increased

intake.’

2.2.5 Summary

In summary, social support, stress, physical activity

and foods each may have positive influences on

mental and physical health. A clinical study with

low grade prostate cancer patients is in preparation

where these factors will be targets for a lifestyle

intervention.

3 REQUIREMENTS &

SOLUTION CONCEPT

Elsewhere (Simons and Hampe, 2011) an existing

health (e)coach solution is described which supports

intensive lifestyle change addressing each of the four

lifestyle components: social support, stress, physical

activity and food. This solution strongly builds on

empowering patients to improve their health:

“Health is what happens between doctor’s visits.”

The clinicians and the solution provider are

interested in adding an mApp portfolio to improve

closeness and feedback to the patients.

The purpose of this section is to formulate a

preliminary requirements and solution properties

list. Requirements are extracted from literature as

well as from two interviews with the solution

provider (health coach and innovation manager).

The latter interviews also led to the formulation of

the preliminary mApp based solution concept.

3.1 Requirements

According to the meta-study of Jimison et al., (2008)

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a number of requirements must be fulfilled to create

ICT solutions that enhance the value for patients: 1)

Ease of use, 2) Perceived usefulness, 3) Relevant

information loop: perceived as having health

relevance by the patients, 4) Embedding in a

treatment cycle: interaction with health providers to

decide on the course of action following the

information which has been generated, 5) Delivered

on technology that patients use every day.

Based on the health providers’ interviews, a

central goal in this intensive lifestyle intervention is

health empowerment and involvement. Related

requirements are: 6) Improving transparency and

awareness of health effects from lifestyle behaviors,

7) Improving quality of health beliefs, 8) Increasing

fun and attractiveness of tracking health behaviors,

9) Increasing motivation for health behaviors.

From the supply side of the health (e)coach

provider, the following requirements were

mentioned: 10) Operational quality and reliability

(customer service of mApps, reliability, continuity,

ease of use), 11) Low cost implementation and

flexibility (simple to test, adopt and discard mApps,

thus gradually improving the portfolio), 12) Creating

meaningful conversion scores from mApps into

existing e-dashboard, 13) Information flows

integration (from mApp to e-dashboard to coach and

vice versa).

3.2 Preliminary Solution Concept

In relation to user needs, key elements of the

prospected solution are ‘closeness’, attractiveness

and relevance: everyday interfaces are to be used,

like email and smart phones. Also fun and

attractiveness are important, hence the provider

choice for selecting mApps from the most popular,

existing mApps. In Aug 2011, smart phone

penetration in the Netherlands was 42% http://on

line.wsj.com/article/BT-CO-20110804-717179.html.

In the age group of 60-70 years (core of this patient

group) penetration was 20+% and rapidly rising.

Also for this age group, smart phones may become a

dominant personal ICT platform (in close

competition with email, internet and telephone),

because of their attractiveness, 24x7 closeness, and

intuitive user interfaces.

In terms of functionality, for each health factor

(food, physical activity, stress, social support) one or

several mApps are selected. Table 1 gives an

overview of the functionality and design rationale.

The selected mApps are offered and supported as

a portfolio, with a list of recommended mApps, a

‘runner up of the month’ that is recommended to try

out, with a Dutch user manual, and with meta-data

generated weekly for the patients (delivered in an

automated email) to stimulate mApps usage and

show mApps benefits which have been experienced

by several of the users, to the rest of the patient

group. When patients open their e-dashboard, they

see references to the mApps portfolio. And when

they enter their weekly health behaviors in the e-

dashboard, they see the options to enter mApp

generated values.

Table 1: Preliminary Functionality and Rationale.

Functionality Design rationale

Everyday smartphone & mailbox use.

Increase ease of use and

‘closeness’

Portfolio of mApp support options:

stress, exercise, food, group support.

Something useful for

everyone

Selected mApps are managed as

portfolio, including user manual.

Manage and monitor mApps

use. And explain value

adding in relation to e-

dashboarding and coaching

activities.

Explicit links into dashboard Æ if

XYZ calories burned: input that

value; input from week food report:

fibers etc.

Visualize cross-referencing

and mutual roles of e-

dashboard versus mApps

portfolio.

Explicit references in dashboard to

mApps: pictures, explanations and

dropdowns: ‘input value from App’.

Visualize options for mApps

use, and trigger non-users to

consider using mApps.

Using weekly low intrusion mails

(including reports from mHealth data

captured.)

Give progress feedback, add

relevance, increase

awareness.

4 CONCLUSIONS

Based on the preceding argument, our conclusion is

as follows: An mApps suite, as an extension to an

existing online dashboard with automated emails

and interpersonal coach sessions, appears promising

for improving long term health behavior support.

This rests on the sub-propositions summarized on

page 1. Furthermore, we expect that in the coming

ten years mApps will revolutionize health self-

management, as well as transform the roles and

activities of health providers. They will increasingly

become coaches of (information- and mApp-)

empowered patients that “make health happen in

between doctor’s visits”.

--Truncated – Reference list available with authors --

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