=Paper=
{{Paper
|id=Vol-3067/paper2
|storemode=property
|title= A persuasive system to improve physical activities of older adults
|pdfUrl=https://ceur-ws.org/Vol-3067/paper2.pdf
|volume=Vol-3067
|authors=Houssem Aloulou,Hamdi Aloulou,Bessam Abdulrazak,Ahmed Hadj Kacem
|dblpUrl=https://dblp.org/rec/conf/tacc/AloulouAAK21
}}
== A persuasive system to improve physical activities of older adults ==
https://ceur-ws.org/Vol-3067/paper2.pdf
A persuasive system to improve physical activities
of older adults
Houssem Aloulou 1, Hamdi Aloulou 1, Bessam Abdulrazak2, Ahmed Hadj Kacem 1
1
University of Sfax, ReDCAD Research Laboratory, Sfax, Tunisia
2
University of Sherbrooke, Québec, Canada
Abstract
Being physically active is enjoyable and safe for all age groups including for the older adults.
In fact, regular physical activity improves fitness, strength and feeling better. Each person will
inevitably experience the deterioration of his functional abilities as he gets older, and the
sedentary behavior represents the greatest risk having a great effect on their health. In fact,
older adults are the most likely to adopt a sedentary lifestyle and convincing them to change
this behavior is not generally a simple mission. In this work, we propose a persuasive system
to improve physical activities among older adults. Our approach is based on persuasive and
motivation theories. Also, it takes account of physical and mental capacities of the older adult,
his actual location, thanks to location awareness tools, and current weather conditions using an
open weather awareness data API. To be able to determine the best moment to request an
activity for an older adult, we use semantic modeling and reasoning.
Keywords 1
Older adult, Physical activity, Motivation, Persuasion, Location awareness, Weather
awareness, Semantic modeling, Semantic reasoning.
1. Introduction
The development in health care around the world is keeping people alive for longer. Therefore, the
ratio of older adults in the global population is increasing rapidly according to the World Health
Organization (WHO) [1].
Physical activity is any bodily movement produced by skeletal muscles that increases heart rate and
breathing and requires energy expenditure. Since the dawn of time, humans have recognized the
importance of physical activity to stay in shape and prevent morbidity. Nevertheless, with the
technological advancement and the widespread use of machines in recent decades, more and more
efforts are needed to promote physical activity among all age groups and especially among older adults.
These latter are the most likely to adopt a sedentary lifestyle, which accelerates their transition to the
age of dependency. Sedentary lifestyle also increases sociological problems and the risk of getting
several chronic diseases such as high blood pressure, obesity, diabetes, lipid disorders, cardiovascular
diseases, depression, and anxiety. These chronic diseases are now the leading causes of death in all
regions of the world [1]. The WHO recommends exercising regularly to maintain optimal health.
Because more physical activity provides greater health benefits, many efforts around the world aim
to raise awareness of older adults about the importance of doing regular physical activity. According to
the Canadian Physical Activity Guidelines for older adults, to achieve health benefits, and improve
functional abilities, adults aged 65 years and older should accumulate at least 150 minutes of moderate
to vigorous intensity aerobic physical activity per week, in bouts of 10 minutes or more [2].
Tunisian Algerian Conference on Applied Computing (TACC 2021), December 18–20, 2021, Tabarka, Tunisia
EMAIL: houssem.aloulou@gmail.com (H. Aloulou); hamdi.aloulou@redcad.tn (H. Aloulou); bessam.abdulrazak@usherbrooke.ca (B.
Abdulrazak) ; ahmed.hadjkacem@fsegs.usf.tn (A. Hadj Kacem)
©️ 2020 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
In the present work, our goal is to prevent sedentary lifestyles among older adults and to promote
their physical activities without coercion or deception. Older adults must be well motivated to change
their behavior and move more. Motivation serves as the guiding force behind all human behaviors. It is
a state-of-mind, filled with enthusiasm and energy. It is a force inside or outside the body that energizes,
directs, and maintains goal-oriented behaviors [3]. Hence, motivation could encourage older adults to
change behavior and to engage in health-oriented behaviors. In fact, there exist many behavioral change
methodologies which use persuasive methods to change subjects’ behaviors. These methodologies are
stimulated by cognitive and social psychology.
Our proposed approach applies these methodologies to promote physical activities among older
adults. To ensure the success of our persuasion technique, we take into consideration the older adult’s
health profile and his preferred activities. To have a contextualized persuasion, our proposed
methodology takes also account of the current location of the person and the current weather conditions.
This intelligence is guaranteed thanks to the use of semantic modeling and reasoning, which from
different types of information, it would be able to decide the best moment to trigger the desired
behavior.
Following, section 2 presents a detailed state of the art of existing behavior change techniques. In
section 3, we expound our methodology to promote physical activities of older adults. Then, in
section 4, we present the validation of the methodology. Finally, we end this article with a conclusion.
2. State of the art
Aging of people is caused by different types of factors: biological factors, environmental factors,
and behavioral factors [4]. Several scientific research have shown that being active is useful for
everyone, regardless of age [5] and regardless of its intensity. In fact, it has shown more recently that
daily living activities have a positive effect on health outcomes [6].
In this work, our objective is to stimulate older adults to change behavior and promote physical
activities. Change is the synonym of modification and alteration. It is defined as the progress from one
condition to another. A change in a person's behavior is a change in his habits or in his way of
behaving [7]. To have a successful behavior change, the older adult must be aware of the importance
of physical activities and must be well motivated to do it.
In [8], motivation is defined as “the set of forces encouraging an individual to engage in a given
particular behavior to achieve a goal or perform an activity. It is the combination of several concepts
that relates to both cognitive (internal) and environmental (external) factors”. Motivation is frequently
described as being either “Extrinsic” or “Intrinsic” [9]:
● Intrinsic motivation: it arises from within the individual. It is the motivation to do an activity
for its own sake. For example, solving a complicated crossword puzzle purely for personal
gratification. The highest level of intrinsic motivation is labeled “Optimal experience” [10].
● Extrinsic motivation: it arises from outside of the individual. It is the motivation to do an
activity to attain some external goal and often involve social-environmental factors including
rewards, trophies, money, social recognition, praise, competition, and surveillance. Over time,
some of these goals can be internalized and the person no longer feels that they come from
outside and tends to become an Intrinsic motivation.
Various behavior change theories used motivation as an essential element. Our methodology takes
advantage of several existing behavior change theories to have a successful persuasion which triggers
the desired behavior at the right time and place and when the person is well motivated to do it. In [11],
Fogg demonstrated in his behavior change model FBM that 3 conditions must converge at the same
time for a behavior to be realized: sufficient “Motivation” and “Capacity” to do the requested behavior
and a well-chosen moment to “Trigger” the behavior (physical location, emotions, availability,
proximity, etc.) when the person is most open to persuasion (Kairos factor) and thanks to the availability
and portability of mobile devices (convenience factor).
Bandura proposed the “Social Cognitive Theory” [12]. He argues that people are motivated by
external forces. This theory is formed by a triad of three interacting factors: personal factor, behavioral
factor, and environmental factor [13]. These factors are controlled by behavior change variables like:
● Self-efficacy: Person’s confidence in his ability to perform the behavior requested of him.
● Outcome expectations: Person must be aware of the expected consequences of a behavior.
● Self-monitoring: Empower the person by self-controlling in carrying out the requested
behaviors.
● Reinforcement: any event that strengthens or increase the likelihood of a behavior.
The relation between the attitude and the behavior of a person was explained in the “Theory of
Reasoned Action [14]. According to this theory, a person’s belief is made from several background
factors: individual factors (personality, emotions, values, etc.), social factors (age, level of education,
culture, etc.), and factors information (knowledge, experience, etc.). These beliefs form the person’s
perception and then his intention to perform voluntary requested behavior.
The “Theory of Planned Behavior” [15] is an improvement of the theory of reasoned action. It
stipulates that the behavior is determined by the intention, formed by the values/beliefs of the person
and social norms, and the sense of ability and self-efficacy to adopt a requested behavior. This theory
is used in a very wide range of situations like smoking, road safety, sharing content on social media and
the approval of the use of new technologies. In fact, the acceptance of technology can be defined as
“The approval, favorable reception and continued use of newly introduced devices and systems.” [16].
In our research work, we have the mandate to propose the use of a non-intrusive mobile application
which must be acceptable and appreciated by participating older adults. The “Technology Acceptance
Model” [17] [18] [19] is an adaptation of the Theory of Planned Behavior for the system information
domain. It models how to convince users to accept a new technology. According to this theory, two
elements make it possible to determine the intention of a person to use or not a technology: Perceived
Utility and Perceived Ease-of-use. Perceived Utility is directly affected by Perceived Ease-of-use.
Among the research studies that have applied the Technology Acceptance Model, we can cite [20],
it was applied to examine the behavior and degree of acceptance of e-commerce by older adults in the
United States. Questionnaires were distributed to people aged between 52 and 87 years. The
Technology Acceptance Model was used and adapted to examine the impact of Ease-of-use, Utility,
and Trust on the acceptance of e-commerce. Ease of use has a significant impact on utility and trust has
an impact on ease of use and utility.
Senior Technology Acceptance and Adoption Model [21] was developed to predict factors
influencing the adoption of mobile phones by older adult users. Three phases to guarantee a successful
application of this model:
● Objectification phase: The user establishes his “intention” to use the mobile phone from a
“User context” point of view influenced by “Social factors”, “Perceived usefulness”, and
“Ease of learning and use”.
● Incorporation phase: Characterized by a process of “Testing” and “Exploration”. At the end
of this phase, the “Utility” is confirmed or infirmed. If the “Utility” is confirmed for the
user, that means that the motivation was successful and that it leads to a real “Intention to
use” of this technology.
● Acceptance and adoption phase: The adoption and full use of mobile phones by the older
adult. Acceptance is a prerequisite for adoption, but adoption involves behavior change,
giving technology use a place in someone’s life.
The Senior Technology Acceptance and Adoption Model was used in various research works. For
example, in [22] and [23], authors tested the model, empirically using a questionnaire survey, to
understand the acceptance of Gerontechnology by the oldest Chinese in Hong Kong . In fact, the
Gerontechnology is an interdisciplinary field that combines “Gerontology”, which is a field of study
that focuses on aging, its consequences and its implication, and “Technology”, which creates ergonomic
technological environments to assist older adults in activities of daily life, housing, mobility and
transport, communication and autonomy, health and self-esteem, work, and leisure.
3. Methodology
Engaging in more physical activity results in more health benefits. To promote health and improve
functional ability, older adults aged 65 years and older should do at least 150 minutes of moderate to
vigorous physical activities per week in sessions of at least 10 minutes.
Transition from a sedentary lifestyle to an active lifestyle requires targeting an optimal motivation
of older adults.
In a previous work [24], we proposed a personalized and customized persuasion strategy to promote
older adults’ physical activity. Defined persuasion theory was based on some behavior change theories
especially on Fogg’s behavior model (FBM) [11]. In addition, our persuasion strategies are adapted for
each participant. In fact, it uses the health and personal profile of each older adult to be sure of the
ability of the older adult to do the requested behavior even before asking it. This keeps the motivation
of the participant who will find the requested tasks easy and within his capabilities.
In the present work, we broaden our approach by relying on additional methods of behavior change
and by being aware of the current context of the older adult. It is certain that the context-awareness of
physical and psychological state of the older adult are essential to have successful persuasion strategies.
But taking in consideration its surrounding state is also crucial to ensure more relevant notifications to
trigger a desired behavior.
To succeed in defining an effective and sustainable persuasion strategy, able to be maintained and
improved, our persuasive approach to promote physical activity of older adults has three principal
stages: The pre-persuasion, the persuasion, and the post-persuasion.
Figure 1: Persuasion stages
3.1. Pre-persuasion stage: Form older adult’s profile
Each new participant willingly provides some information by answering questions when registering
on our platform. The collected data concerns:
● Personal profile: Name, Family name, e-mail, gender, address, marital status, level of study,
current job, etc.
● Health state: To take into consideration the older adult’s past and current health history,
strengths, and vulnerabilities before suggesting an activity. To draw an overall overview of
the health state of a participating older adult, we mainly used the HUI-3 index (Health Utility
Index – Mark 3) [25] which is a generic health profile and preference-based system for
measuring health status, for reporting health-related quality of life, and producing utility
scores, to model the health profile. The HUI-3 classification system comprises 8 attributes:
Vision, Hearing, Speech, Ambulation, Dexterity, Emotion, Cognition, and Pain. Each with
5 or 6 levels of ability/disability. The value “1” means that the person does not have any
health problems for the attribute. The more the value tends towards the greatest value of the
attribute (5 or 6), the more the state of health of the elderly person for this attribute is
deteriorated.
● Preferred activities: The proposed activities for every participating older adult can belong
to one of the following types. Some activities are daily living. For example: personal
hygiene, dressing room, feeding, ambulation, preparing meals, washing the dishes and
clothes, etc. Some other activities relate to physical exercises whether individually or with
other colleagues to break isolation and have a kind of friendly competition.
This helps our persuasive theory to draw relatively clearly the profile of the participant, his physical
and mental capabilities, and his preferred activities.
3.2. Persuasion stage: Motivate older adult to change behavior
There is no doubt that regular physical activity is very useful for all age groups including older
adults. For this reason, it is recommended to stay active even when getting older. Even though many
older people have physical limitations, that doesn't mean they won't be able to be active, sure as far as
possible!
Indeed, there are always ways to adapt physical activity, for example: Doing exercises sitting on a
chair, doing exercises in the swimming pool for those at risk of falling, creating a safer environment for
a person who has suffered from a stroke, etc. What is important is to keep moving while being careful.
Our goal is to keep the motivation of participating older adults at its highest level based on the
different behavioral theories cited in our state of the art. The table below contain some of behavior
change elements used in our approach. For each, we cite some examples and how it is implemented in
our persuasive system.
Table 1
Some of adopted behavior change techniques
Element of Example Implementation
persuasion
Intrinsic Cooperation: Several older Offering activities that are done in group such
motivation adults with similar profiles and as: walking outdoor with friends.
preferences can cooperate in
carrying out collective group
activities.
Intrinsic Acknowledgement: to make Periodically, congratulate the participant who
motivation older adult feel good about his achieves good performance.
effort in promoting his physical
activity.
Reinforcement Training to be able to well To finally be able to take long walks, the older
accomplish the requested adult can start by taking short walks in the
behavior. neighboring streets.
Ability Only suggest activities that are Semantic reasoning to suggest activities
possible to do based on the health profile.
Utility Show the benefits of doing the Well-formulated notifications to explain the
requested physical activity and importance of physical activity on mental and
possible drawbacks if not. physical health.
Trust Having credibility and expertise Notifications contain quotes taken from
will give increased power of official sources and with scientific merit.
persuasion
Perceive ease Simplifying the mobile App to A mobile App is always available, responsive,
of use be easy to use by older adults and easy to access, has greater opportunity
to persuade.
Outcome Make it possible to be aware of Demonstrate the benefits that will be derived
expectations the expected consequences of a from performing this behavior.
behavior
3.2.1. Contextual data
A very good motivation leads to a successful influence of attitudes and behaviors change only if
timing and context are well chosen. In [26], Fogg has demonstrated that new computing capabilities,
especially network and mobile technologies, offer additional potential to persuade people by offering
suggestions:
• At the opportune moment (the Kairos factor): thanks to the mobility and connectivity of new
IT systems, and
• Easily (the Convenience factor): since a computing device is always available and close to
the user and its use is fast and easy without requiring a delay.
Contextual data based on “location awareness”
The location awareness refers to the capability of a device, like a smartphone, to determine its
location in terms of coordinates [27]. This allows to identify the user’s location through mobile devices
with location technology and provide the required application services based on the location. In recent
years, many portable devices have been equipped with built-in GPS location services.
To be able to geolocate the older adult, we have used the “android.location2” API which uses
Android location based services and its related services to determine the location of the older adult’s
smartphone.
This API is so accurate to the point of being able to have the full address of the current position:
geographic coordinates (latitude and longitude), building number, street name, city, country, and the
postal code. Our Android app receives regular updates on the person’s current location from
“android.location” API. For example, knowing the name of the city or the name of the borough where
the older adult is currently located will allow to suggest activities sensitive to the current location.
Contextual data based on “weather awareness”
To access weather’s data of the older adult’s current location, our mobile app uses an Open Weather
Map API3 allowing to access current weather data worldwide. Data provided by this API comes from
various sources such as global and local weather models, satellites, radars, and a large network of
weather stations.
Knowing the name of the city where the older adult is currently located will allow the possibility of
offering activities that consider the current weather conditions in addition to the physical and mental
state of the older adult.
3.3. Post-persuasion
To be considered as successful persuasion strategy, a new behavior must be preserved for a long
time as several older adults may adopt the new proposed behavior for a limited period and they give up
after a certain time. This can be explained by the fact that preserving a behavior or attitude requires a
lot of effort, energy, and time, etc. For this reason, the older adult will continue receiving notifications
on their smartphone to encourage them to maintain their new behavior and to consolidate it.
4. Validation
The availability and portability of smartphones make it possible to reach participating older adults
at any place and time. We developed a full persuasion system called “ActiveSenior”, a first version of
2
https://developer.android.com/reference/android/location/package-summary
3
https://openweathermap.org/
it was presented in a previous work [24]. “ActiveSenior” is made on the one hand of a front-end part
which contains mobile App activities and on the other hand of a back-end part used to define the server
App holding services in relation to the initial user.
Participating older adults interact directly with the front-end application, while the server App is
connected to a database, containing data of each participant (his personal profile, his health state, his
preferred activities, and his current context) and an ontology for decision making with semantic
reasoning of defined rules.
Interaction between the front-end application and the back-end application is done through php
requests and with automated notifications sent via the Firebase4 service.
Before triggering a behavior change or a physical activity, our back-end application will try to ensure
the success of the persuasion technique. We have therefore extended our ontology so that it will be able
to take into account the current contexts of location and weather of the older adult.
Hence, we added two sub-classes of the class “Environment”: “City” and “Weather”, an Object
Property: “personHasWeather”, and several Data Properties to handle location and weather data such
as: “temperatureValue”, “weatherStatusDesc”, “windSpeedValue”.
All gathered information about the older adult’s current city
weather conditions is presented in our mobile App. The
information presented in the activity of the mobile App are: the
name of the country and the city (obtained thanks to the use of
“android.location” API), the current temperature and the
temperature felt, minimum temperature and maximum temperature
of the day, weather condition and its description, humidity
percentage, wind speed and its direction, air pressure, the sunrise
time and the sunset time.
We have defined inference rules to be used by our ontology in the server side of our persuasive
system. Inference rules allow to the reasoner to generate new intelligent knowledge. This latter enable
to decide the best time and location to trigger a notification suggesting a suitable activity to the older
adult taking into consideration his health and mental profile.
So, we have defined several rules to be used by the reasoner to decide to most suitable strategy.
Below 2 examples of defined rules:
Rule 1:
[RuleForWalkingOutdoor: (?u pre:personHasPreferredTopic pre:walking)
(pre:walking pre:topicRequestAbility ?a) (?u pre:personHasAbilityLevel ?cl)
(?cl pre:levelHasCorrespondingAbility ?a) (?cl pre:levelValue ?v) lessThan(?v,
3) (pre:walking pre:topicRequestLocation ?loc) (?u pre:personDetectedIn ?h) (?h
pre:placeRepresentLocation ?loc) (?u pre:personHasWeather ?w) (?w
pre:temperatureValue ?temp1) moreThan(?temp1, 20) (?w pre:weatherStatusDesc
4
https://firebase.google.com/
?d1) equal(?d1, "Clear") (pre:walking pre:topicHasPersuasionStrategy ?s) ->
Debug(?u, ?s) (?u pre:personMotivatedByPersuasionStrategy ?s)]
This rule asks an older adult to take a walk outside (activity WalkingOutDoor) only if all the
following conditions are validated: the older adult has good health profile (the Health Utilities Index is
<3) allowing him to go out to walk, the weather is clear (weatherStatus = "Clear") and the temperature
is more than 20°C (temperatureValue >20).
Rule 2:
[RuleForHousework: (?u pre:personHasPreferredTopic pre:housework)
(pre:housework pre:topicRequestAbility ?a) (?u pre:personHasAbilityLevel ?cl)
(?cl pre:levelHasCorrespondingAbility ?a) (?cl pre:levelValue ?v) lessThan(?v,
4) (pre:housework pre:topicRequestLocation ?loc) (?u pre:personDetectedIn ?h)
(?h pre:placeRepresentLocation ?loc) (pre:housework
pre:topicHasPersuasionStrategy ?s) (?u pre:personHasWeather ?w) (?w
pre:temperatureValue ?temp1) lessThan(?temp1, 20) (?w pre:weatherStatusDesc
?d1) equal(?d1, "Rain") (pre:housework pre:topicHasPersuasionStrategy ?s) ->
Debug(?u, ?s) (?u pre:personMotivatedByPersuasionStrategy ?s)]
This rule asks an older adult to housework if it is raining (weatherStatus = "Rain"), the temperature
is less than 20°C (temperatureValue <20), and health profile (the Health Utilities Index is <4).
To assess “ActiveSenior” App, we carried out an experiment with 8 older adults (4 females and 4
males), all aged more than 60 years. We installed “ActiveSenior” App in the smartphone of each
participant and helped him to create his own profile with all required information. The following table
shows some of information of personal and health profiles of participating older adults. Rows present
data of each older adult. We have chosen to hide the names of participating older adults and replace
them with OAn, with n between 1 and 8, to ensure data confidentiality. Columns contain the age, the
gender, and attributes of Health Utilities Index 2 and 3 (HUI-2 and HUI-3).
Table 2
Some information of personal and health profiles of participating older adults
ID Age Gender Cognition Dexterity Emotion Hearing Pain Speech Vision Walking
OA1 62 F 1 1 1 1 2 1 1 1
OA2 83 M 3 2 2 1 4 1 2 5
OA3 60 F 1 1 2 1 2 1 1 2
OA4 70 M 1 1 2 1 2 1 1 2
OA5 68 M 1 1 2 1 2 1 2 2
OA6 67 M 3 4 3 1 5 1 3 3
OA7 73 F 1 1 1 3 2 1 2 2
OA8 61 F 1 1 1 1 2 1 1 2
The back-end framework of our persuasive system considers the health profile of each participant.
For example, the value 5 of the walking attribute of older adult OA2 shows that he suffers from walking
problems. OA6 has dexterity problem with severe pain that prevent most activities. OA1, OA3, and
OA8 have relatively a good physical shape according to their ages.
To choose the most suitable activity for an older adult, the reasoning engine verify the ability of the
older adult to do the desired physical activity while being aware of the actual location and the actual
weather conditions. The table below gives some of received notifications following the use of the
semantic reasoning engine and based on health state, weather current description and temperature:
Table 3
Examples of context-aware received notifications
Older Health Weather Proposed
Temperature Received notification
Adult profile description activity
“Walking may be the best form of
physical exercise for seniors.
Packed with health benefits,
Good 26 °C
OA1 Clear Walking walking is the friendliest physical
shape ( > 20 °C)
exercise. It has a low risk of
injury, and it’s easy to get started
with.”
Good 28 °C “It’s time to take action. Walk and
OA8 Clouds Walking
shape ( > 20 °C) enjoy life!”
“A clean and organized home is a
beautiful home. It eliminates the
Good risk of developing allergies and
OA3 Raining 15 °C Housework
shape asthma; it also reduces stress, and
it is extremely vital to your mental
health.”
Walking 24 °C Water the “Water is vital for the survival of
OA2 Clear
problems ( > 20 °C) plants all yours plants”
“You are lucky to have a balcony
Dexterity 25 °C Sit in the in your apartment, you can breathe
OA6 Clear
and Pain ( > 20 °C) balcony fresh air without leaving your
home.”
“Regular upkeep of a home in
terms of cleanliness and tidiness
Good
OA1 Raining 14 °C Housework reduces stress and it is extremely
shape
vital to your physical and mental
health.”
The notifications faithfully translate the rules defined for the semantic engine of the server-side
application of our persuasion system. Indeed, according to the obtained results, we can notice that our
system proposed the physical activity “Walking” for participant older adults OA1 and OA8. Both have
a relatively good profile health and are in good shape whether it is actually “Clear” or “Cloudy” and it
feels more than 20 °C.
Older adults OA1 and OA3 have the ability to go out and take a walk. But given the bad weather
outside, they received notifications requesting them to stay at home and to do housework.
Participant OA2 suffers from walking problems. He can’t walk for a long time and distance.
Considering his state of health, we ask him to water the plants to enjoy the beautiful day and to breathe
fresh air, without going too far from his home.
Finally, even if the current weather is fine and the temperature is mild enough to go out and enjoy
the beautiful weather, older adult OA6, who have dexterity and pain problems, received a notification
inviting him to sit in the balcony. In fact, asking him to go out could present a danger for his safety.
5. Conclusion
In this paper we detailed our approach to improve older adults’ physical activities. Our work is based
on several existing behavioral change methodologies and persuasion strategies which were detailed in
the state of the arts. Through this work, we have improved persuasion strategies’ usefulness and
efficiency. This was accomplished by incorporating end-users’ profiles and contextual location and
weather data in our reasoning engine. We have validated our method through several defined scenarios
showing the impact of the user profile and the contextual information on the persuasion strategy’s
decision system.
Acknowledgments
This work was partially supported by the LABEX-TA project MeFoGL: ”Méhodes Formelles pour
le Génie Logiciel”.
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