Mobile Phones App to Promote Daily Physical Activity:
Theoretical Background and Design Process
Gilles Kermarrec
1
, Yannick Guillodo
2
, Damien Mutambayi
2
and Léo Ballarin
2
1
European Research Center for Virtual Reality and Research Center for Education,
Learning and Didactics, European University of Brittany, France
2
Coaching Sport Santé Company, 2920 Brest, France
Abstract. Considering advances from research and technologies concerning
physical activity and health, this chapter presents the C2S’s Project (Coaching
Sport Santé). C2S is a French start-up aiming at designing a device for promot-
ing Daily Physical Activity (DPA). Based on Self-Determination, Self-Esteem
Self-Regulation theories, and on the Trans-theoretical Model of Behaviour
Change, a mobile phone App was developed including pedometer technology.
The app offer a five step-strategy aimed at taking in account a) initial or normal
everyday steps counts, b) individual motivational factor, and c) personally-
adapted feedbacks.
1 Introduction
Benefits of physical activity for improving health are well established. Regular physi-
cal activity is associated with enhanced health and reduced risk of mortality factors,
including cardiovascular disease,
ischemic stroke, non–insulin-dependent, diabetes,
colon cancers,
osteoporosis, depression,
and fall-related injuries (for an review see
[1]).
Therefore, a survey of EU countries demonstrated that two thirds of the adult
population did not reach recommended levels of physical activity (http://
www.who.int/whr/2002/en). In contrary, the prevalence of a sedentary lifestyle has
been established in the European Space (e.g. in the 15 Member States of the European
Union, [2]). Sedentary lifestyle has been defined according to various criteria: the
number of hours that individuals spend sitting down in a typical day, the number of
hours expended walking or in other specific physical activities, or how many times a
week they participated in an activity that induced sweating [3]. Recently Europeans
have been identified as high-risk populations; thus, the European Union’s council
recommendation of 26 Nov 2013 on promoting health enhancing physical activity
called for monitoring of physical activity levels across member states. The Determi-
nants of Diet and Physical Activity (DEDIPAC) European knowledge hub
(www.dedipac.eu) organizes a major workshop on physical activity and sedentary
behaviour surveillance and assessment in may 2015.
Considering these advertising, and advances from research and technologies, this
chapter presents the C2S’s Project (Coaching Sport Santé). C2S is a French start-up
aiming at designing tools for promoting Daily Physical Activity (DPA). Especially, an
interdisciplinary team of exercise psychologist, doctor and health experts, managers
and engineers collaborated in designing a physical activity smartphone application.
Guillodo Y., Ballarin L., Mutambayi D. and Kermarrec G.
Mobile Phones App to Promote Daily Physical Activity: Theoretical Background and Design Process.
DOI: 10.5220/0006157001130124
In European Project Space on Computational Intelligence, Knowledge Discovery and Systems Engineering for Health and Sports (EPS Rome 2014), pages 113-124
ISBN: 978-989-758-154-0
Copyright
c
2014 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
113
Based on Self-Determination, Self-Esteem Self-Regulation theories, and on the Trans-
theoretical Model of Behaviour Change, a device including a mobile phone App was
developed to promote Daily Physical Activity (DPA).
The purpose of this chapter is to summarize reviews about physical activity inter-
ventions, to provide a framework for increasing DPA, and to present our App’s design
process and its outcomes.
2 Changing for Daily Physical Activity: Advances from Research
Recommendations in order to benefit from regular physical activity are well-known:
30 minutes of moderate-intensity activity on 5 or more days per week, or 20 minutes
of vigorous-intensity activity on 3 or more days per week. Activities that expend 3- to
6-fold the energy expenditure of sitting at rest (3 to 6 metabolic equivalents or METs,
1 MET=3.5 ml O2•kg-1•min-1) are defined as moderate (walking), those that expend
more as vigorous, and less as light intensity (running) [4]. Strategies and interventions
to promote DPA are problematic. Several reviews have been conducted in this area
and provided us with guidance for our project. The conclusions can be summarized
into three points.
2.1 Several Types of Interventions for the Promotion of Physical
Activity
Kahn et al., [5] produced a systematic review of interventions for the promotion of
physical activity. Three categories of interventions have been distinguished:
- Informational approaches to change knowledge and attitudes about the benefits;
especially in the self-regulation theory, knowledge about PA and health are a key
component of the behavioural change mechanism. Knowledge help people to
identify new goals and goals lead to behavioural strategies.
- Behavioural approaches to teach people the skills necessary for both successful
adoption and maintenance of behaviour change. Especially studies including goal
setting, self-monitoring, self-assessment, specific feedbacks showed that behav-
ioural change in DPA could be achieved.
- Environmental and policy approaches to change the structure of physical and
organizational environments to provide safe, attractive, and convenient places for
physical activity. Especially, interpersonal setting is often thought to have poten-
tial for motivation (cooperation and competition) and social support are effective
in increasing PA level.
Behavioural approaches and individually adapted health behaviour change programs
consist of the most successful way. There is strong evidence that this kind of face-to-
face PA programs are effective in increasing level of physical activity. Thus, face-to-
face interventions are considered to be the optimal means for changing health-related
behaviour.
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2.2 Findings of Research on PA Interventions
Hillsdon et al., [6] summarized the evidence from sixteen systematic reviews and
meta-analyses. Their ‘review of reviews’ provided a summary of the findings of re-
search on interventions aiming at promoting physical activity for adults.
Evidences suggested that short-term change is achievable, and that use of a moti-
vational and behaviour change theory will help. For instance, intervention could be
based on various social cognitive theory of motivation (e. g., self-efficacy theory,
self-regulation theory) or on the trans-theoretical model of change. Nevertheless, in
many studies evidences were not consistent, or the research method could be criti-
cized because PA was assessed thanks to declarative and self-administered question-
naires, such as the “International Physical Activity Questionnaire”.
Moreover, the authors pointed out there are no consistent evidence for changes in
workplace settings despite the fact that the importance of promoting physical activity
through organisations is frequently pointed out. Especially the workplace, while tar-
geted extensively in North America, has shown inconsistent involvement in physical
activity promotion especially in European Space. Nevertheless, the workplace can
offer large numbers of individuals and larger companies use to offer an infrastructure
to support health promotion initiatives. Considering that adults spend about one quar-
ter of their time at their place of work during their working lives, walking may be the
best way to increase DPA, so that we suggested that pedometer technology could be
relevant for the C2S project.
2.3 Pedometers: Furnishing a Realistic Measure for DPA
Biddle and Mutrie [7] produced a synthesis of the literature in which the use of pe-
dometers is considered an efficient motivational tool. Using pedometers is not new,
and studies showed they are accurate to count steps and assess PA [8]. Then, re-
searchers have pointed out the effect of pedometers on motivation and PA [9]. Even
the presence of pedometers alone could increase walking steps, and feedbacks from
pedometers seem to be relevant information in order to involve motivation and DPA
[10]. Therefore, Biddle and Mutries [7] pointed that in other studies walking steps did
not increase significantly. In one of their studies they demonstrated that pedometers
provided a short-term effect, but that this effect was not evident in the long term.
Thus, all over the world, campaigns promoted the idea that 10,000 steps a day are
required for health, and pedometers seems to be a reliable technological support for
assessing DPA and providing feedbacks to people. Therefore, reported an overview
of 32 studies Biddle and Mutries pointed that 10,000 steps could be too low or too
high objectives for some people (active or sedentary individuals), so that the 10,000
steps goal might lead to reduce motivation, especially if people do not feel able to
reach this goal.
In accordance with these authors, we suggested that pedometers measures could
involve PA programs’ efficiency, because they allow to promote more adapted or
personalized step-goals.
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2.4 Conclusions
Research advances are particularly relevant to design intervention in DPA. There was
strong evidence that motivational support through social cognitive motivation frame-
work, self-regulation theory, or trans-theoretical model for behavioural change,
should increase DPA program effectiveness. Interventions should target behaviour
change by personalized and adapted interventions. Therefore, Interventions aiming at
increasing DPA are still problematic because:
a) Information about PA and health are relevant but few healthcare professionals are
trained to promote PA’s effects
b) PA program Intervention is efficient only if it is individually adapted or when
people is face-to-face
c) In most of countries it seems to be hard to change DPA in workplace settings
d) There was insufficient evidence that technology-based support interventions effec-
tively increased physical activity
Finally, the C2S project tried to take in account these advances. The global project is
described on the web, and many informational resources on PA and health are provid-
ed (www. agircontrelasedentarite.org). The C2S Project included a promotion initia-
tive, called “Challenging sedentary lifestyle”, gathering together many companies or
workplaces settings. Previous research showed that promoting DPA should consider
the workplace setting. Workplace could be an interpersonal setting which has poten-
tial for DPA changes, only if companies are members or partners of the project. In
2015, 20 local companies (in the west of France) and 318 employees participated
voluntarily in this ride.
The global project and the challenge need efficient technological support. A mo-
bile phone App (www.bouge-application.fr) was designed in order to deliver an indi-
vidually adapted program. The design process was theoretically based on motivational
and behavioural change frameworks. These frameworks and their implications for the
program will be presented in the second section.
The mobile phone application includes pedometer technology and may offer effi-
cient strategies aiming at taking into account a) initial or normal everyday steps
counts, b) individual motivational factor, and c) personally-adapted feedbacks. The
design process will be presented in the third section.
3 Enhancing Daily Physical Activity: Impact of Psychological
Factors
The development of exercise psychology has led to the proliferation of theories, pri-
mary tested in social and health psychology. Thus psychological factors of physical
activity have been studied extensively and helped us understand why people are moti-
vated or not (“amotivated”) and why they adopt a physically active lifestyle or not
(sedentary). The study of human motivation has been central to exercise psychology.
Vallerand and colleagues [11] offered an operational definition of motivation, consid-
ering some the following behavioural indicators: the initiation, the direction, the per-
sistence, the intensity, and continued motivation. These components of a motivated
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behaviour could be influenced by social and cognitive factors.
More precisely, considering this perspective and previous empirical studies we
chose to take in account many models of motivation and behaviour in an exercise
setting. They were supposed to lead to principles for DPA program and to guide the
App’s design process. Thus each model we chose can be considered as a blend of
theoretical and practical support for our strategy and device. Consequently, our inter-
vention strategy consisted of five steps (see figure 1), including diagnosing, initiating,
monitoring, maintaining and evaluating. Each step has to be theoretically based, in
order to insure the all-strategy reliability.
3.1 Diagnosing Attitude towards Behaviour Change: The
Trans-Theoretical Model
The first model we took in account was the trans-theoretical model (TTM) of behav-
iour change. The TTM is not a model of motivation, but it as been classified as a
stage-based behavioural model [7]. The TTM was developed as a comprehensive
theory of behaviour change and was initially applied to smoking cessation [12]. The
TTM has been applied to physical activity, it could be considered as a precious tool
aiming at diagnosing the attitudes towards PA. The stages are [13]:
- Pre-contemplation: no intention to start physical activity
- Contemplation: considering starting physical activity
- Preparation: beginning a limited program of exercise
- Action: engaging in regular physical activity for less than six months
- Maintenance: engaging in regular physical activity for more than six months.
Studies [13] showed that TTM is a modest predictor of exercise.
Therefore, these stages are useful to diagnose if individuals are ready or not to ac-
cept the program; they should lead designers or practitioners to adapt their program.
In the TTM, the processes of change are the strategies used to progress along the
stages of change. The processes are divided into cognitive (thinking) and behavioural
(doing) strategies so that self-regulation theories should constitute a complementary
resource for modelling changes in DPA.
3.2 Initiating and Monitoring Behavioural Change: The Role of
Self-regulation Components
Aiming at understanding the initiation and the monitoring of behaviour, early at-
tempts in exercise psychology favoured theories of perceived control. One of the most
popular is the self-regulation theory advocated by Flavell [14]. Thus, goals, strategies,
metacognition and knowledge are considered as components within the self-
regulation process. Goals are considered as internal specific or general representations
of a desired state: people could try to involve daily steps, or to be more active; some-
times they want to please a parent or the doctor, or to take care of themselves. Re-
searchers interested in self–regulation showed that goals depend on prior knowledge
about the concerned domain, and on metacognition.
Knowledge about PA and health (sometimes researchers called them beliefs) de-
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termines motivation and behaviour towards PA. If someone knows that walking is the
most reliable way to well being, he might adopt goal to change his sedentary behav-
iour. Then, self-regulation theory describes a relationship between goals and behav-
ioural strategies: people whose goals are to enhance their DPA would adopt strategies
to walk everyday. Strategies are means or solutions that people imagine, or that
coaching should offer in order to reach a goal (e.g., walking during you’re phoning;
walking to get the next bus stop). These strategies are supposed to help people to
monitor and involve DPA.
Metacognition is simply defined as cognition about self [14]. People engaging in
metacognition will internally design knowledge about their own capabilities, and their
own skills. If someone knows that he is not able to walk more than 5,000 steps a day,
he spontaneously might not adopt a goal up to 10,000 steps a day. In contrary, if a PA
program is addressed to him, and seems too difficult, too high, he simply would give
up. Thus, metacognition is a precious component when designers want to select ap-
propriate goals and strategies in exercise settings [15]. In this perspective pedometers
should be helpful tools for people to know their own real DPA, and lead them to
adopt a relevant goal.
Complementary, when one wants to initiate PA, goal setting theory, and the self-
determination theory are also well-known resources. Research shows that motivation
for physical activity is likely to be more robust if environment offers choices and self-
determination rather than external control. This conducted us to consider that the
program should offer alternative goals. Individuals should be invited to choose the
best goals for themselves, or the most motivating one.
3.3 Maintaining Active Behaviour: Interest of Achievement Motivation
Because goals are personal representations, people are usually motivated through
various types of goals. According to the Achievement Motivation Theory goals and
behaviour could be referred to mastery – oriented or performance – oriented elements.
Closely related to the issue of Goal Achievement Motivation Theory, the climate, or
the relationships, within the exercise environment [16]. Perceptions of the motiva-
tional climate within a workplace or a training group can be classified as “mastery” or
“performance”. A mastery climate is one in which the participants perceive that self-
improvement is the most important. A “performance” climate is one where partici-
pants are often compared with each other or with normatively superior performance
(e.g. 10,000 steps a day).
A meta-analysis of climate studies across all physical activity settings quantified
the links between climates and outcomes [16]. The overall effects from fourteen stud-
ies involving over 4,000 participants showed a large effect for mastery climate on
positive outcomes and a moderate effect for performance climate on negative out-
comes.
Because feedbacks in a device are important elements of a perceived climate, this
line of research provides an important rationale for designing PA setting. Mastery
oriented feedbacks or performance oriented feedbacks should be addressed to partici-
pant depending to their personal motivation orientation or to their physical self-
esteem.
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3.4 Evaluating Outcomes of DPA Intervention
Contemporary self-esteem theory proposes that our global view of ourselves (“global
self- esteem”) is underpinned by perceptions of specific domains of our lives, such as
social, academic and physical domains. Based on this approach and on Fox previous
work [17], Ninot et al., [18] has developed an operational measure of physical self-
perceptions and its self-perception subdomains of sport competence, perceived
strength, physical condition, and attractive body. Self – esteem theory proposed that
everyday events are likely to affect more specific perceptions of self, such as the be-
lief that one can walk 10,000 steps a day, which may eventually contribute to en-
hanced self-perceptions of physical condition or even physical self-worth. Self-
perceptions could be important psychological constructs guiding general motivated
behaviour, when people have to initiate PA. Self-perceptions can also be viewed, such
as consequences or outcomes of a PA program.
Finally both of Physical – Self Esteem Scale and TTM of behaviour change fur-
nished guides to implement the evaluation stage of the five-step intervention strategy.
3.5 Conclusions
The C2S Project aimed at implementing a technological solution, more specifically a
mobile phone application, based on advances from research in exercise psychology.
Fig. 1. The Five-Steps Strategy: a rationale for the App design process.
The program was considered as a set of personalized walking goals, behavioural
strategies and knowledge about PA and health, and daily-individualized feedbacks.
The question for the designer of a DPA program is how to deliver these information
or artefacts to individuals? The whole strategy and its backgrounds are summarized in
figure 1. These rational have been presented to the designers at the beginning of the
design process.
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4 Delivering a Personalized Physical Activity Program: A Design
Process
Despite an explosion of mobile phone applications concerning PA, few have been
based on theoretically derived constructs in order to promote health behaviours and
reduce sedentary behaviour [19].
During the period from September 2013 – May 2014, the interdisciplinary team
undertook initial app design, programming, and iterative user testing. Following these
activities, initial app was developed and feedbacks from potential users were ob-
tained. The Android smartphone platform was used. The smartphone battery life suf-
ficiently to allow continuous accelerometer data capture throughout the day. The data
collected via the smartphone's built-in accelerometer were transmitted to the project's
local servers each evening for data storage and to allow researchers to monitor the
quality of data while the design progressed. Feedbacks from users and ergonomic
analysis lead to involve the design. During the period from September 2014 – January
2015, a second version of the app, called MOVE (“BOUGE” in French language),
was developed, and was able to be commercialized. MOVE delivered an 8-weeks
program aiming at involving DPA
The 5-steps intervention strategy was implemented within the design of the App.
4.1 Diagnosing
The initial session is used to provide instruction on the general use of the App, and to
collect data including age, size, weight and gender. Especially, attitudes towards PA
and Physical Self-Esteem are diagnosed. The user has to answer the Physical-Self
Inventory (PSI-6), a six-item questionnaire developed and validated by Ninot et al.,
[18]. The PSI-6 is a short version of a previously validated questionnaire, the PSI-25,
adapted from the Physical Self-Perception Profile [18]. PSI-6 contains one item for
global self-esteem (GSE), one item for physical self-worth (PSW), and one item for
each of the four sub-domains identified by Fox and Corbin [17]: physical condition
(PC), sport competence (SC), attractive body (AB) and physical strength (PS). This
questionnaire was proven to reproduce the factorial structure of the corresponding
multi-items inventories [18] and to possess the same hierarchical properties. Each
item is a simple declarative statement, to which participants was invited to respond
using an analogic visual scale.
Attitude towards PA and behaviour change is measured using the stage of exercise
behaviour change scale, adapted from Cardinal [20]. Users are asked to place them-
selves in one the five stages. During this first week, descriptions of the physical activ-
ity recommendations for health and sedentary lifestyle risks are available on a single
screen.
The first week of the 12-weeks program is used as a baseline or a testing period
for delivering an adapted program. Users are requested to continue with their normal
physical activity and sedentary behaviours during the baseline week. The main screen
of the app provides the user’s current daily number of steps.
At the end of this initial week, the program can be personalized and users receive
goals and advices.
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Fig. 2. User’s profile on a screen.
4.2 Initiating and Monitoring
At the beginning of each week, users receive specific goal setting, which emphasized
walking steps increase. For each week a distal goal is assigned depending both based
on the score or number of walking steps the user reached at the end of previous week
(e.g., 30 000 steps a week), and on his psychological profile (i.e., Physical Self-
Esteem score). Depending on previous data, 5, 10, 15, 20% enhancement in weekly
walking steps was used as references points. Participants were provided with three
goal options of varying difficulty (e.g., 33 000 steps, or 34 500 steps, or 36 000 steps).
These choice options were given based on the self-determination and goal-setting
theory principles.
Whenever he wants, the user can see on the same screen his just-in-time score, the
score for previous days, and the target at the end of the week.
In addition to having access to some “help” as part of this app, users participants
can edit a set of behavioural strategies. On a specific screen, written solutions for
increase DPA are listed and the user is invited to choose some of them. Twice a day
brief health information and knowledge about benefits of PA (e.g., 1 minutes for PA =
10 minutes for life) are displayed.
Thus, goals, knowledge and strategies are supposed to stimulate self-regulation be-
haviour aiming at initiating and monitoring DPA.
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Fig. 3a and 3b. User’s daily current screens.
4.3 Maintaining
It was attempted that personalized feedback delivered by the app aim maintain moti-
vation and PA. Balance sheets are provided in the middle of the fourth, the eighth and
the eleventh week of the program. An email is sent to the user including graphs and
encouragements or advices. Feedbacks’ content depends on scores and on psycholog-
ical profile. Thus they can be mastery – oriented (e.g., Congratulations! An increase
of 15% over the previous weeks! Go on! You walk for your health!), or performance
– oriented (Congratulations! You’ve reached 50 000 steps a week! You’re now con-
sidered as an active person!).
Fig. 4. User’s balance sheet.
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4.4 Evaluating
In line with previous research in exercise psychology, pedometers are reliable for
furnishing a realistic and objective measure about everyday walking steps. Such an
on-going evaluation is supposed to impact motivation and behaviour control. Users
perceived the gap between the goal they have chosen and their own DPA. Conse-
quently, self-regulation mechanisms consist in imagining solutions, imitating pairs’
behaviour, seeking for advices. The app helps people in taking in charge their own
behaviour.
Finally, as soon as the program is closed, users receive a final balance sheet and
advices for future. This constitutes a milestone in our 5-steps strategy; when someone
is able to evaluate his own progress, it was hypothesized that his own self-perception
would enhance. Thus at the end of the program, users are asked to answer the Physi-
cal Self-Esteem. If users observe increases concerning both of DPA and Physical
Self-Esteem, they would get confidence in the device effectiveness. These psycholog-
ical effects would favour continued motivation for DPA.
5 Perspectives
Benefits of Physical Activity are attempted for adults in the European Space. The C2S
Project including a web resource, a ride for companies called “Challenging sedentary
lifestyle”, and the MOVE App, is a medical, technologic and scientific project. Thus,
an empirical study (200 participants in experimental group vs 100 participants in
control group) has been conducted to assess the effect of the program on DPA. Re-
sults could have important implications for advancing the field of PA sciences, and
will be precious to involve the design of the App. Moreover collected data on daily
PA or behaviour changes in a workplace setting will be stored and should be useful
for health institutions.
References
1. O'Donovan, G. , Blazevich, A., Boreham, C., Cooper, A.H., Crank, H., Ekelund, U., Fox,
K.R., Gately, P., Giles-Corti, B., Gill, J.M.R., Hamer, M., McDermott, I., Murphy, M.,
Mutrie, N., Reilly, J.J., Saxton, J.M. and Stamatakis, E. : The ABC of Physical Activity for
Health: A consensus Statement from the British Association of Sport and Exercise Scienc-
es. J. of Sports Sc. 28, 6 (2010) 573-591
2. Blair SN. : Physical Inactivity: the Biggest Public Health Problem of the 21st Century. Br.
J. Sport. Med. 43 (2009) 1–2
3. Varo, J.J., Martinez-Gonzalez, M-A.: Current Challenge in the Research About Physical
Activity and Sedentary Lifestyle. Rev Esp Cardiol. 60 (2007) 231-233
4. Williams, P.T. and Thompson, P.D.: Walking vs Running for Hypertension Cholesterol,
and Diabete Risk Reduction. Art. Thomb. Vasc. Biol. 33, 5, (2013) 1085-1091.
5. Kahn, E. B., Ramsey, L. T., Brownson, R. C., Heath, G. W., Howze, E. H., Powell, K. E.,
Stone, E. J., Rajab, M. W. and Corso, P.: The Effectiveness of Interventions to Increase
Physical Activity: A Systematic Review. Am. J. of Pre. Med. 22 (2002) 73–107.3.
6. Hillsdon, M., Foster, C., Naidoo, B. and Crombie, H.: A Review of the Evidence on the
123
Mobile Phones App to Promote Daily Physical Activity: Theoretical Background and Design Process
123
Effectiveness of Public Health Interventions for Increasing Physical Activity Amongst
Adults: A Review of Reviews. London: Health Development Agency (2003).
7. Biddle, S. J. H. & Mutrie, N.: Psychology of Physical Activity. Determinants, Well-being
and Intervention. 2
nd
Edition, Routledge, New-York and London (2008).
8. Crouter, S., Schneider, P., Karabulut, M. And Basset, J.: Validity of 10 Electronic Pedome-
ters for Measuring Steps, Distance, and Energy Cost. Med. Sc. In Sp. and Ex. 35, 8 (2003)
1455–60.
9. Rooney, B., Smalley, K., Larson, J. and Havens, S.: Is knowing Enough? Increasing Physi-
cal Activity by Wearing a Pedometer. Wis. Med. J. 102, 4 (2003) 31–6
10. Stovitz, S., VanWormer, J., Center, B. and Bremer, K.: Pedometers as a Means to Increase
Ambulatory Activity For Patients Seen at a Family Medicine Clinic. J. Am. B. of Fam.
Prac. 18 (2005) 335–43
11. Vallerand, E.L., Pelletier, R.J., and Ryan, L.G.: Motivation and Education: the Self-
Determination Perspective. The Ed. Psy. 26 (1991) 325-346
12. Prochaska, J. O. and DiClemente, C. C.: Transtheoretical Therapy: Toward a More Integra-
tive Model of Change. Psychotherapy: Th. Res. and Prac. 19 (1982) 276–88
13. Callaghan, P. Khalil, E. and Morres, I.: A Prosective Evaluation of th Transtheoretical
Model of Change Appled to Exercise in Young People. Int. J. of Nurs. St. 47 (2010) 3-12
14. Flavell, J. H. Cognitive monitoring. In: Dickson, W. P. (Ed.): Children’s oral communica-
tion skills. New York: Academic Press (1981)
15. Kermarrec, G., Todorovitch, J. and Fleming, D.: Investigation of the Self - Regulation
Components Students Employ in the Physical Education Setting. J. of Teach. in Phys. Ed.
2, 23 (2004) 23-142
16. Ntoumanis, N. and Biddle, S. J. H.: A Review of Motivational Climate in Physical Activity.
J. of Sp. Sc. 17 (1999) 643–65
17. Fox, K.H. and Corbin, C.B.: The Physical Self-Perception Profile: Development and pre-
liminary validation. J. of Sp. and Ex. Psy. 11, (1989) 408-430
18. Ninot, G., Fortes, M., and Delignières, D.: Validation of a Shortened Assessment of Physi-
cal Self in Adults. Perc. And Mot. Skills 103 (2006) 531-542.
19. King, A.C., and al.: Harnessing Different Motivational Frames via Mobile Phones to Pro-
mote Daily Physical Activity and Reduce Sedentary Behaviour in Aging Adults. Plos One
8, 4 (2013) 1-8
20. Cardinal, B.J.: Construct Validity of Stages of Change for Exercise Behaviour. Am. J. of
Health Prom. 12, 1 (1997) 68-74
124
EPS Rome 2014 2014 - European Project Space on Computational Intelligence, Knowledge Discovery and Systems Engineering for Health
and Sports
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